Publications

2018

  1. Thomas McCoy, Robert Frank & Tal Linzen. Revisiting the poverty of the stimulus: hierarchical generalization without a hierarchical bias in recurrent neural networks. To appear in Proceedings of the 40th Annual Conference of the Cognitive Science Society.
  2. Marten van Schijndel & Tal Linzen. Modeling garden path effects without explicit hierarchical syntax. To appear in Proceedings of the 40th Annual Conference of the Cognitive Science Society.
  3. Tal Linzen & Brian Leonard. Distinct patterns of syntactic agreement errors in recurrent networks and humans. To appear in Proceedings of the 40th Annual Conference of the Cognitive Science Society.
  4. Hall, Kirsten R.; Crichton, Devin; Marriage, Tobias; Zakamska, Nadia L.; Mandelbaum, Rachel;  “Downsizing of star formation measured from the clusterred infrered background correlated with quasary” http://adsabs.harvard.edu/abs/2018arXiv180408632H
  5. Bera I, Klauda JB. Molecular Simulations of Mixed Lipid Bilayers with Sphingomyelin, Glycerophospholipids and Cholesterol. J Phys Chem B. 2017;121:5197-208.
  6. Tan Z, Khakbaz P, Chen Y, Lombardo J, Yoon JM, Shanks JV, Klauda JB, Jarboe LR. Engineering Escherichia coli membrane phospholipid head distribution improves tolerance and production of biorenewables. Metabolic Engineering. 2017;44:1-12.
  7. Wang E, Klauda JB. Examination of Mixtures Containing Sphingomyelin and Cholesterol by Molecular Dynamics Simulations. J Phys Chem B. 2017;121:4833-44.
  8. Bera I, Klauda JB. Structural Events in a Bacterial Uniporter Leading to Translocation of Glucose to the Cytosol. J Mol Biol. 2018. https://doi.org/10.1016/j.jmb.2018.06.021
  9. Guros N, Balijepalli A, Klauda JB. Membrane Influence a-Hemolysin Ion Conductance. Biophys J. 2018; Submitted.
  10. Khakbaz P, Klauda JB. Investigation of phase transitions of saturated phosphocholine lipid bilayers via molecular dynamics simulations. Biochim Biophys Acta, Biomembr. 2018;1860:1489-501.
  11. Leonard AN, Pastor RW, Klauda JB. Parameterization of the CHARMM All-Atom Force Field for Ether Lipids and Model Linear Ethers. Journal of Phyiscal Chemistry B. 2018;122:6744-54.
  12. Wang E, Klauda JB. Models for the Stratum Corneum Lipid Matrix: Effects of Ceramide Concentration, Ceramide Hydroxylation, and Free Fatty Acid Protonation. The journal of physical chemistry B. 2018;Submitted.
  13. Wang E, Klauda JB. Structural Properties of Ceramide Bilayers, Ceramide Multilayers and Ethanol Permeation. Biochim Biophys Acta, Biomembr. 2018;Submitted.
  14. Wilusz, D. C., C. J. Harman, and W. P. Ball (2017), Sensitivity of Catchment Transit Times to Rainfall Variability Under Present and Future Climates, Water Resources Research, 53(12), 10231–10256, doi:10.1002/2017WR020894.
  15. Harman, C. J., D. Wilusz, StorAge Selection functions as a subgrid parameterization of groundwater transport in watersheds – progress and challenges, Computational Methods in Water Resources meeting, Saint-Malo, France, 3-7 June 2018
  16. Kim, M., Harman, C. J., and Troch, P. A. (2017). H21O-01: Does age matter? Controls on the spatial organization of age and life expectancy in hillslopes, and implications for transport parameterization using rSAS, American Geophysical Union, Fall Meeting, 11-15 Dec 2017.
  17. Wilusz, D. C., Harman, C. J., Ball, W. P., Maxwell, R. M., and Buda, A. R. (2017b). H23E-1742: What Can Catchment Transit Time Distributions Tell Us About Runoff Mechanisms? Exploring “AgeEquifinality“ with an Integrated Surface-Groundwater Model. American Geophysical Union, Fall Meeting, 11-15 Dec 2017.
  18. Wilusz, D. C.}, Maxwell, R. M., Buda, A., Ball, W. P., C. J. Harman, (2017) How Does Spatial Variability in Rainfall and ET Affect Catchment Flow Velocities?, Gordon Research Seminar, June 24-25, Bates College, Lewiston, ME
  19. -C. Lu, N.P. Daphalapurkar, A.K. Knutsen, J. Glaister, D.L. Pham, J.A. Butman, J.L. Prince, P.V. Bayly, and K.T. Ramesh, “A 3D Computational Head Model and the Importance of the Falx and Tentorium in Mild TBI,” Annals of Biomedical Engineering, submitted for publication.
  20. El Mir, C., Ramesh, K.T., and Richardson, D.C., “A new hybrid framework for simulating hypervelocity asteroid impacts and gravitational re-accumulation,” Icarus, submitted for publication.
  21. Madouh, F.A. and Ramesh, K.T., “Shear anisotropy in mTBI: a white matter constitutive model,”Journal of Biomechanics, submitted for publication.
  22. Ganpule, N.P. Daphalapurkar and K.T. Ramesh, “Effect of bulk modulus in computational predictions of mild TBI,” Shock Waves, Vol. 28, No. 1, pp. 127-139, 2018. DOI 10.1007/s00193-017-0791-z.
  23. Badr HS , AK Dezfuli, BF Zaitchik and CD Peters-Lidard (2017) Regionalizing Africa: Patterns of Precipitation Variability in Observations and Global Climate Models. Journal of Climate. DOI: 10.1175/JCLI-D-16-0182.1
  24. Bakker C, BF Zaitchik, S Siddiqui, BF Hobbs . . . & CL Parker (2018) Shocks, seasonality, and disaggregation: Modelling food security through the integration of agricultural, transportation, and economic systems. Agricultural Systems, 164, 165-184.
  25. Nie, W., Zaitchik, B. F., Rodell, M., Kumar, S. V., Anderson, M. C., & Hain, C. (2018) Groundwater Withdrawals Under Drought: Reconciling GRACE and Land Surface Models in the United States High Plains Aquifer. Water Resources Research. https://doi.org/10.1029/2017WR022178
  26. Lu, Y. (UMD undergraduate student senior thesis, now graduated), Ballouz, R.-L. (postdoc, JAXA), Richardson, D.C. 2018. “Exploring Shear-free Ringlet Formation with Direct Simulations of Saturn’s B Ring”, Astronomical Journal, in review.
  27. Ballouz, R.-L., Richardson, D.C., Morishima, R. (UCLA/JPL scientist) 2017. “Numerical Simulations of Saturnʼs B Ring: Granular Friction as a Mediator between Self-gravity Wakes and ViscousOverstability”, Astronomical Journal 153:146 (10pp)
    [http://iopscience.iop.org/article/10.3847/1538-3881/aa60be/meta]
  28. -L. Ballouz, Numerical Simulations of Granular Physics in the Solar System (University of Maryland, College Park, 2017), Doctoral dissertation
  29. Morishima, R., Spilker, L., Ballouz, R.-L., Richardson, D.C. 2016. “N-body ray-tracing modeling of Saturn’s rings for analysis of UVIS/VIMS optical depths and CIRS temperatures”, American Astronomical Society, DPS meeting #48, id.121.1
  30. Ballouz, R., Richardson, D.C., Morishima, R., Spilker, L., Lu, Y. 2016. “Numerical Simulations of Saturn’s B-Ring: Granular Friction as a Mediator between Self-Gravity and Viscous Overstability”, American Astronomical Society, DPS meeting #48, id.114.08
  31. Yu A, Lau AY. Energetics of glutamate binding to an ionotropic glutamate receptor. J Phys Chem B. 2017; 121(46):10436–10422.
  32. Yu A, Salazar H, Plested AJR, Lau AY. Neurotransmitter funneling optimizes glutamate receptor kinetics. Neuron. 2018; 97(1):139–149.
  33. Lau AY. Enhanced sampling of glutamate receptor ligand-binding domains. Neurosci Lett. In press.
  34. Yu A, Lau AY. Glutamate and glycine binding to the NMDA receptor. Structure. 2018; 26(7):1035–1043.
  35. Yu A, Ph.D. thesis, 2017, Computational investigations of ionotropic glutamate receptor ligand binding and conformational change.
  36. Phelan, J. P.; Lang, S. B.; Compton, J. S.; Kelly, C. B.; Dykstra, R.; Gutierrez, O.*; Molander, G. A. Redox-Neutral Photocatalytic Cyclopropanation via Radical/Polar Crossover. J. Am. Chem. Soc. 2017, 140, 8037-8047. https://pubs.acs.org/doi/10.1021/jacs.8b05243
  37. Cabrera-Afonso, M. J.; Lu, Z.-P.; Kelly, C.; Lang, S.; Dykstra, R.; Gutierrez, O.*; Molander, G. Engaging Sulfinate Salts via Ni/Photoredox Dual Catalysis Enables Facile Csp2–SO2R Coupling. Chem. Sci. 2018, 9, 3186-3191. http://pubs.rsc.org/en/content/articlepdf/2018/sc/c7sc05402e
  38. Wes, L.; Zhou, J.; Lei, L.; Gutierrez, O.* Mechanism of Nakamura’s Iron-Catalyzed Asymmetric Cross- Coupling Reaction: The Role of Spin in Controlling Selectivity. J. Am. Chem. Soc. 2017, 139, 16126-16133. https://pubs.acs.org/doi/pdf/10.1021/jacs.7b06377
  39. Osvaldo Gutierrez. Selective Iron-Catalyzed C-C Bond Formations: Insights from Calculations and Experiment. 2nd International Symposium of Organic Reaction Mechanisms, May 15-17, 2018. Peking University Shenzhen, China.
  40. Madeline Rotella. Mechanism of Iridium-Catalyzed Regio- and Enantioselective Fluorination of Secondary Allylic Trichloroacetimidates: An Experimental and Computational Study. Stereochemistry Gordon Research Conference. July 22-27, 2018. Salve Regina University, Newport , RI.
  41. Lee, Wes. Computational Studies on the Mechanism of Bisphosphine-Iron Catalyzed C-C Cross-Coupling Reactions. Stereochemistry Gordon Research Conference. July 22-27, 2018. Salve Regina University, Newport , RI.
  42. Liu, Lei. Synthesis of Radical-Clock α-Halo-Esters as Mechanistic Probes for Bisphosphine Iron-Catalyzed Cross-Coupling Reactions. Stereochemistry Gordon Research Conference. July 22-27, 2018. Salve Regina University, Newport , RI.
  43. Keith Arora-Williams, Olesen SW, Scandella B, Kyle Delwich, Sarah Spencer, Elise Myers, Sonali Abraham, Alyssa Sooklal, Sarah Preheim. Dynamics of microbial populations mediating biogeochemical cycling in a freshwater lake. In Review
  44. Andrea Fraser, Yue Zhang, Claire Wayner, Sarah Preheim. Dynamics and functional potential of stormwater microorganisms colonizing sand filters. Water, In Review
  45. Preheim SP., Arora-Williams K., Holder C., Gnanadesikan A. 2018. Application of DNA- and RNA-sequence based techniques to inform biogeochemical models of the Chesapeake Bay dead-zone. Chesapeake Bay Research and Modeling Symposium, Annapolis, MD (Talk)
  46. Preheim SP. 2018. Frequency and impact of transitions between microbial populations mediating biogeochemical cycling in a freshwater lake. Mid-Atlantic Microbiome Meeting. College Park, MD (Talk)
  47. Preheim SP. 2017. Dynamics of Microbial Diversity and Biogeochemical Processes in the Chesapeake Bay Dead-Zone. Ecological Society of America, General Meeting. Portland, OR (Talk)
  48. Preheim SP. 2017. Modeling the dynamics of biogeochemical processes and bacterial diversity in anoxic aquatic environments. Society for Industrial Microbiology and Biotechnology Annual Meeting, Denver CO (Talk)
  49. Kendall EA, Schumacher SG, Denkinger CM, Dowdy DW. Estimated clinical impact of the Xpert MTB/RIF Ultra cartridge for diagnosis of pulmonary tuberculosis: a modelling study. PLoS Med. 2017 Dec 14;14(12):e1002472. doi: 10.1371/journal.pmed.1002472.
  50. Kendall EA, Brigden G, Lienhardt C, Dowdy DW. Would pan-tuberculosis treatment regimens be cost-effective? Lancet Respir Med, 2018 May 30. pii: S2213-2600(18)30197-8. doi: 10.1016/S2213-2600(18)30197-8.
  51. Salvatore PP, Proaño A, Kendall EA, Gilman RH, Dowdy DW. Linking individual natural history to population outcomes in tuberculosis. J Infect Dis. 2017; 217(1): 112-121. DOI: 10.1093/infdis/jix555
  52. Salvatore PP. Projecting MDR-TB in South Africa and Vietnam: How the evolution of drug resistance can shape the future of tuberculosis. Poster presentation, American Society of Tropical Medicine and Hygiene 66th Annual Meeting. Baltimore, MD, November 5-9, 2018
  53. Salvatore PP. Projecting the future of MDR-TB epidemics in South Africa and Vietnam: the role of transmission efficiency. The Annual Scientific Meeting of the Center for Tuberculosis Research at Johns Hopkins University. Baltimore, MD, June 12, 2018.
  54. Kendall E. “MDR-TB Elimination: What Will It Cost?,” Symposium talk, 48th World Union Conference on Lung Health, Guadalajara, Mexico, October 2017
  55. Kendall E. Mathematical Modeling to Guide Programmatic Decisions about the Use of New Tuberculosis Drugs, Regimens, and Diagnostics PhD Dissertation, Graduate Training Program in Clinical Investigation, June 2018
  56. Shrestha, S., Hill, A. N., Marks, S. M., Dowdy, D. W. “Comparing drivers and dynamics of tuberculosis (TB) in California, Florida, New York and Texas.” American Journal of Respiratory and Critical Care Medicine, 2017; 196(8):1050-1059.
  57. Shrestha, S., Chihota, V., White, R. G., Grant, A. D., Churchyard, G. J., Dowdy, D. W. “Impact of targeted tuberculosis vaccination among mining population in South Africa: A model-based study.” American Journal of Epidemiology, 2017;186(12):1362-1369.
  58. Shrestha S, “Modeling tuberculosis transmission in four US states.” National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention Epidemiologic and Economic Modeling Agreement (NEEMA), Centers for Disease Control and Prevention (CDC), Atlanta, GA, Oct 30-31, 2017;
  59. Shrestha S. TB Modelling and Analysis Consortium (TB MAC)/ World Health Organization (WHO) Annual Meeting: Country-level modeling & TB Case Detection, Glion, Switzerland, Sep 18-22, 2017; [invited talk]
  60. Kasaie, P., Berry, S.A., Shah, M.S., Rosenberg, E.S., Hoover, K.W., Gift, T.L., Chesson, H., Pennington, J., German, D., Flynn, C.P. and Beyrer, C., 2018. Impact of providing pre-exposure prophylaxis for HIV at clinics for sexually transmitted infections in Baltimore City: an agent-based model. Sexually transmitted diseases.
  61. Perry, A., Kasaie, P., Dowdy, D.W. and Shah, M., 2018, January. What will it take to reduce HIV incidence in the United States: A mathematical modeling analysis. In Open forum infectious diseases (Vol. 5, No. 2, p. ofy008). US: Oxford University Press.
  62. McKenney, J., Chen, A., Hoover, K.W., Kelly, J., Dowdy, D., Sharifi, P., Sullivan, P.S. and Rosenberg, E.S., 2017. Optimal costs of HIV pre-exposure prophylaxis for men who have sex with men. PloS one, 12(6), p.e0178170.
  63. P Kasaie, H Sohn, E Kendall, GB Gomez, A Vassall, M Pai, DW Dowdy √ Simulation Conference (WSC), 2017 Winter, 1097-1108, 2017
  64. P Kasaie, L Buyon, DW Dowdy Projecting the impact of pre-exposure prophylaxis for HIV prevention in the context of gonorrhea and chlamydia infection
    Simulation Conference (WSC), 2017 Winter, 4590-4591, 2017
  65. ????????????/(J. Phys. Chem. C, 2018, 122, 12148-12157, J. Org. Chem. 2017, 82, 13440, two doctoral dissertations). Several other MARCC-enabled publications are in preparation.
  66. Seo, J. H., Eslami, P., Caplan, J., Tamargo, R., and Mittal, R., “A Highly Automated Computational Method for Modeling Intracranial Aneurysm Hemodynamics,” Frontiers of Physiology, Vol. 9, pp. 681, 2018.
  67. Seo, J. H., Cadieux, F., Mittal, R., Deem, E. A., and Cattafesta, L. N., “Effect of Synthetic Jet Modulation Schemes on the Reduction of a Laminar Separation Bubble,” Physical Review Fluids, Vol. 3, Iss. 3, 033901, 2018.
  68. Seo, J. H. and Mittal, R., “Flow Physics and Frequency Scaling of Sweeping Jet Fluidic Oscillators,” AIAA Journal, Vol. 56(6), pp. 2208-2219, 2018
  1. Zhu, C., Seo, J. H., and Mittal, R., “Computational Modelling and Analysis of Haemodynamics in a Simple Model of Aortic Stenosis,” Journal of Fluid Mechanics, 2018, accepted.
  2. Wu W., Seo J.H., Meneveau C., and Mittal R. “Response of a Laminar Separation Bubble to Zero-Net Mass Flux Actuation”, 2018 Flow Control Conference, AIAA AVIATION Forum, (AIAA 2018-4018).
  3. Dou,, Rips, A. Welsh, N., Seo, J. H., & Mittal, R. “Flow-Induced Flutter of Hanging Banners: Experiments and Validated Computational Models”, 2018 Fluid Dynamics Conference, AIAA AVIATION Forum, (AIAA 2018-3081)
  4. Menon K., and Mittal R. “Computational Modelling and Analysis of Aeroelastic Flutter”, 2018 Fluid Dynamics Conference, AIAA AVIATION Forum, (AIAA 2018-3080)
  5. Seo, J. H., Salazar, E., and Mittal, R. “Internal Fluid Dynamics and Frequency Scaling of Sweeping Jet Fluidic Oscillators,” Bulletin of the American Physical Society, 70th Annual Meeting of the APS Division of Fluid Dynamics, November 19-21, 2017, Denver, Colorado.
  6. Seo, J. H., Zhu, C., Dou, Z., Resar, J., and Mittal, R. “Fluid Dynamics of Thrombosis in Transcatheter Aortic Valves,” Bulletin of the American Physical Society, 70th Annual Meeting of the APS Division of Fluid Dynamics, November 19-21, 2017; Denver, Colorado
  7. Zhu, C., Seo, J.H., and Mittal, R. “Hemodynamics of Aortic Stenosis and Implications for Non-invasive Diagnosis via Auscultation,” Bulletin of the American Physical Society, 70th Annual Meeting of the APS Division of Fluid Dynamics, November 19-21, 2017, Denver, Colorado.
  8. Dou, Z., Seo, J. H., & Mittal, R. “Flow-induced Flutter of Heart Valves: Experiments with Canonical Models.” Bulletin of the American Physical Society, 70th Annual Meeting of the APS Division of Fluid Dynamics, November 19-21, 2017, Denver, Colorado.
  9. Menon, K., Katz, J., and Mittal R. “Computational Modeling and Analysis of Aeroelastic Wing Flutter.” Bulletin of the American Physical Society, 70th Annual Meeting of the APS Division of Fluid Dynamics, November 19-21, 2017, Denver, Colorado.
  10. Bailoor, S., Yaghoobian, N., Turner, S., Mittal, R. “Aerodynamics of Ventilation in Termite Mounds”, Bulletin of the American Physical Society, 70th Annual Meeting of the APS Division of Fluid Dynamics, November 19-21, 2017, Denver, Colorado.
  11. Zhu, C., Seo, J.H., Resar, J., and Mittal, R. “Exploring the Physics of Transvalvular Hemodynamic with Simple Aortic Valve Models,” In 18th U.S. National Congress for Theoretical and Applied Mechanics 2018 June.
  12. Zhu, C., Seo, J.H., and Mittal, R. “An Efficient Graph Partitioned Immersed Boundary Method for Applications in Biofluid Dynamics,” In 8th International Conference from Scientific Computing to Computational Engineering 2018 July.
  13. Menon K., and Mittal R. “Computational Modelling and Analysis of Aeroelastic Flutter”, 2018 Fluid Dynamics Conference, AIAA AVIATION Forum, (AIAA 2018-3080)
  14. Dou,, Rips, A., Welsh, N., Seo, J. H., & Mittal, R. “Flow-Induced Flutter of Hanging Banners: Experiments and Validated Computational Models”, 2018 Fluid Dynamics Conference, AIAA AVIATION Forum, (AIAA 2018-3081)
  15. Rips, A., and Mittal, R. “Flow-Induced Flutter of Multiple Inverted Flags for Improved Energy Harvesting.” Bulletin of the American Physical Society, 70th Annual Meeting of the APS Division of Fluid Dynamics, November 19-21, 2017, Denver, Colorado.
  16. E. Valentine, S.M. Koohpayeh, W.A. Phelan, T.M. McQueen, P.F.S. Rosa, Z. Fisk, N. Drichko An effect of Sm vacancies on the hybridization gap in topological Kondo insulator candidate SmB6 Physica B: Condensed Matter 536, 60-63 (2018) [Full PDF, arXiv:1712.01325]
  17. Wu, W.A. Phelan, L. Liu, J.R. Morey, J.A. Tutmaher, J.C. Neuefeind, M. Feygenson, A. Huq, D.W. Tam, B.A. Frandsen, B.A. Trump, C. Wan, S.R. Dunsiger, T.M. McQueen, Y.J. Uemura, C.L. Broholm Incommensurate magnetism near quantum criticality in CeNiAsO arXiv:1707.09645 (2017) [arXiv:1707.09645]
  1. T. Tran, J. Panella, J.R. Chamorro, J.R. Morey, T.M. McQueen Designing Indirect-Direct Bandgap Transitions in Double Perovskites Mater. Horiz. 4, 688-93 (2017)
    [Cs2AgInCl6.cif, Cs2AgSbCl6.cif]
  2. Meslier V., M. C. Casero, M. Daily, J. Wierchos, C. Ascaso, O. Artieda, P.R. McCullough, and J. DiRuggiero. 2018. Fundamental drivers for endolithic microbial community assemblies in the hyperarid Atacama Desert. Env Microbiol 20:1765-1781 PMID:29573365
  3. Gelsinger, D. and J. 2018. Transcriptional landscape and regulatory roles of small non-coding RNAs in the oxidative stress response of the haloarchaeon Haloferax volcanii. 200:e00779-17 PMID:29463600
  4. Uritskyi G.V., J. DiRuggiero and James Taylor. MetaWRAP – a flexible pipeline for genome-resolved metagenomic data analysis. bioRxiv doi: https://doi.org/10.1101/277442
    (in press)
  5. A paper from this project entitled “A Comprehensive Evaluation of the Genetic Architecture of Sudden Cardiac Arrest” was recently accepted for publication in the European Heart Journal. Mitchell, F. Ashar, SCD CHARGE Working Group, N. Sotoodehnia, D. Arking. “A Comprehensive Evaluation of the Genetic Architecture of Sudden Cardiac Arrest” Johns Hopkins MD-GEM Genetics Research Day. Baltimore, MD. February 9 2018.
  6. Gang GJ, Siewerdsen JH, Stayman JW, “Task-driven optimization of CT tube current modulation and regularization in model-based iterative reconstruction,” Physics in Medicine and Biology, 62(12) 4777-97 (May 2017)
  7. Gang GJ, Siewerdsen JH, and Stayman JW, “Task-driven optimization of fluence field and regularization for model-based iterative reconstruction in computed tomography”, IEEE Transactions on Medical Imaging (Special Issue on Low-Dose CT), 36(12), 2424-35 (December 2017)
  8. Tilley II S, Jacobson M, Ciao Q, Brehler M, Sisniega A, Zbijewski W, Stayman JW, “Penalized-likelihood reconstruction with high-fidelity measurement models for high-resolution cone-beam CT imaging,” IEEE Transactions on Medical Imaging, 37(4), 988-999 (April 2018)
  9. Tilley II S, Zbijewski W, Stayman JW, “High-Fidelity Modeling of Shift-Variant Focal-Spot Blur for High-Resolution CT,” in Int’l Mtg. Fully 3D Image Recon. in Radiology and Nuc. Med., Xi’an, China, 2017, 752-9.
  10. Gang GJ, Wang W, Mathews A, and Stayman JW, “Task-Driven Imaging on an Experimental CBCT Bench: Tube Current Modulation and Regularization Design,” Int. Conf. Fully Three-Dimensional Image Reconstr. Radiol. Nucl. Med., Xi’an, China, June 18-23, 2017, 708-14.
  11. Gang GJ, Stayman JW, “Joint Optimization of Fluence Field Modulation and Regularization for Multi-Task Objectives,” Proc. SPIE Medical Imaging Houston, TX, 10573, 10157313-1-6, February 2018.
  12. Tilley II S, Zbijewski W, and Stayman JW, “A general reconstruction algorithm for model-based material decomposition,” Proc. SPIE Medical Imaging Houston, TX, 10573, 1015731E-1-7, February 2018.
  13. Gang GJ, Mao A, Siewerdsen JH, Stayman JW, “Implementation and Assessment of Dynamic Fluence Field Modulation with Multiple Aperture Devices,” International Conference on Image Formation in X-Ray Computed Tomography, (Salt Lake City, Utah, US), May 20-23, 2018, 47-51.​
  14. Tilley II S, Sisniega A, Siewerdsen JH, and Stayman JW, “High-Fidelity Modeling of Detector Lag and Gantry Motion in CT Reconstruction,” International Conference on Image Formation in X-Ray Computed Tomography, (Salt Lake City, Utah, US), May 20-23, 2018, 318-322.
  15. Langmead B†, Wilks C, Antonescu V, Charles R. Scaling read aligners to hundreds of threads on general-purpose processors. Bioinformatics. 2018 Jul 18. doi:10.1093/bioinformatics/bty648. [advance access]
  16. Wilks C†, Gaddipati P, Nellore A, Langmead B†. Snaptron: querying splicing patterns across tens of thousands of RNA-seq samples. Bioinformatics. 2018 Jan 1;34(1):114-116.
  17. Langmead B†. A tandem simulation framework for predicting mapping quality. Genome Biology. 2017 Aug 10;18(1):152.
  18. Chakraborty and S. Ghosh, “Hyperdynamics Accelerated Concurrent Atomistic-Continuum Model for Developing Crack Propagation Models in Elastic Crystalline Materials”, Computational Materials Science, (accepted for publication), 2018.
  19. Pinz, G. Weber, W. Lenthe, M. Uchic, T. M. Pollock and S. Ghosh, “Microstructure and Property Based Statistically Equivalent RVEs for g-g’ Subgrain Microstructures of Ni-based Superalloys”, Acta Materialia, Vol. 157, No. 15, pp. 245-258, September 2018.https://doi.org/10.1016/j.actamat. 2018.07.034
  20. Yaghmaie and S. Ghosh, “Computational modeling of finite deformation piezoelectric material behavior coupling transient electrical and mechanical fields”, Journal of Computational Physics, Vol. Vol. 373, pp. 148–170, 2018.https://doi.org/10.1016/j.jcp.2018.06.070
  21. Bagri, G. Weber, J.-C. Stinville, W. Lenthe, T. Pollock, C. Woodward and S. Ghosh, “Microstructure and property-based statistically equivalent representative volume elements for polycrystalline Ni-based superalloys containing annealing twins “, Metallurgical and Materials Transactions A, (in press).
  22. Cheng, J. Shen, R. Mishra and S. Ghosh, “Discrete twin evolution in Mg alloys using a novel crystal plasticity finite element model”, Acta Materialia, Vol. 149, pp. 142-153, 2018. doi.org/10.1016/ j.actamat. 2018.02.032
  23. V. Kubair, M. Pinz, K. Kollins, C. Przybyla and S. Ghosh, “Role of exterior statistics-based boundary conditions for property-based statistically equivalent RVEs of polydispersed elastic composites”, Journal of Composite Materials, (in press). DOI: 10.1177/0021998318758498
  24. Li, Z. Zhu, L. Fang, S. Guo, U. Erturun, Z. Zhu, J. E. West, S. Ghosh, S. H. Kang, “Analytical, numerical, and experimental studies of viscoelastic effects on the performance of soft piezoelectric nanocomposites”, Nanoscale, Vol.  9, pp. 14215 – 14228, 2017. doi: 10.1039/C7NR05163H
  25. Azdoud, J. Cheng and S. Ghosh, “Wavelet-enriched adaptive crystal plasticity finite element model for polycrystalline microstructures”, Computer Methods in Applied Mechanics and Engineering, Vol. 327, No. 1, pp. 36-57, December 2017, doi.org/10.1016/j.cma.2017.08.026.
  26. A. Bronkhorst and S. Ghosh, “Integrated Computational Structure-Material Modeling of Deformation and Failure under Extreme Conditions”, International Journal of Fracture, Vol. 208, No. 1-2, pp. 1-3, 2017, doi:10.1007/s10704-017-0253-8.
  27. Ghosh and J. Zhang, “Elastic crack propagation model for crystalline solids using a self-consistent coupled atomistic-continuum framework”, International Journal of Fracture, Vol. 208, No. 1-2, pp. 171-189, 2017, doi: 10.1007/s10704-017-0232-0.
  28. Ghosh and C. A. Bronkhorst, “Foreword “, Computational Mechanics, Vol. 61, No. 1-2, pp. 1=2, 2018,doi:10.1007/s00466-017-1506-0.
  29. Ghosh and J. Cheng, “Adaptive multi-time-domain subcycling for crystal plasticity FE modeling of discrete twin evolution “, Computational Mechanics, Vol. 61, No. 1, pp. 33-54, 2018, doi:10.1007/s00466 -017-1421-4.
  30. Azdoud and S. Ghosh, “Adaptive wavelet-enriched hierarchical finite element model for polycrystalline microstructures”, Computer Methods in Applied Mechanics and Engineering, vol. 321, pp. 337-360, July 2017, doi:10.1016/j.cma.2017.04.018.
  31. Behrou R., Ranjan R., and Guest J.K. (submitted). Adaptive topology optimization for incompressible flow problems with mass flow constraints. Computer Methods in Applied Mechanics and Engineering
  32. Behrou R., Gaynor A.T., and Guest J.K. (2018). Projection-based overhang constraints: Implementing an efficient adjoint formulation for sensitivity analysis. Proceedings of ASME 2018 International Design Engineering Technical Conferences (IDETC), Quebec City, Canada
  33. Osanov M., Guest J.K. (2017). Topology Optimization for Additive Manufacturing Considering Layer-based Minimum Feature Sizes, Proceedings of ASME 2017 International Design Engineering Technical Conferences (IDETC), Cleveland, OH.
  34. Guest J.K. Topology optimization of manufacturable architected materials and components. ARPA-e Machine Learning-Enhanced Energy-Product Development Workshop, Washington, D.C., June, 2018 (Invited Speaker).
  35. Guest J.K., Hemker K.J., Congdon E., Storck S. Topology Optimization and Characterization of Additively Manufactured Components . NASA LaRC Seminar Series, Hampton, VA, May, 2018 (Invited Speaker)
  36. Guest J.K. Topology Optimization of Architected Materials with Application-Specific Tailored Properties, Design for Mechanical Behavior of Architectured Materials via Topology Optimization Symposium, 2018 TMS Annual Meeting, Phoenix, AR, March, 2018 (Invited Speaker).
  37. Osanov M., Guest J.K. Topology Optimization for Photopolymer-based Additive Manufacturing, WCSMO12, Braunschweig, Germany, June, 2017.
  38. Osanov M., Guest J.K. (2017). Topology Optimization for Additive Manufacturing Considering Layer-based Minimum Feature Sizes, IDETC 2017, Cleveland, OH, August, 2017
  39. Behrou R., Guest J.K. Topology optimization of incompressible flow problems. 2018 Engineering Mechanics Institute Conference, Boston, MA, May, 2018
  40. Behrou R., Gaynor A.T., Guest J.K. Topology Optimization with Overhang Constraints: Eliminating the Need for Support Structures in AM. 2018 Engineering Mechanics Institute Conference, Boston, MA, May, 2018
  41. Osanov M., Guest J.K. Large Scale Topology Optimization for Additive Manufacturing. 2018 Engineering Mechanics Institute Conference, Boston, MA, May, 2018.
  42. Divya Mohan, Daniel L. Wansley, Brandon M. Sie, Muhammad S. Noon, Alan N. Baer, Uri Laserson & H. Benjamin Larman, “PhIP-Seq Characterization of Serum Antibodies Using Oligonucleotide Encoded Peptidomes” (accepted at Nature Protocols)
  43. Tory P. Johnson,* H. Benjamin Larman,* Myoung-Hwa-Lee, Stephen S. Whitehead, Jeffrey Kowalak, Camilo Toro, Juyun Kim1, Arline Faustin, Carlos Pardo, Sanjay Kottapalli, Jonathan Howard, Daniel Monaco, James Weisfeld-Adams, Craig Blackstone, Steven Galetta, Matija Snuderl, William A. Gahl, Ilya Kister & Avindra Nath, “Fatal Case of Chronic Dengue Encephalitis Presenting as Progressive Dementia” (under review)
  44. Daniel Monaco, Sanjay Kottapalli, Tiezheng Yuan, Florian Breitwieser, Danielle Anderson, Limin Wijaya, Kevin Tan, Wan Ni Chia, Kai Kammers, Mario Caturegli, Kathleen Waugh, Marian Rewers, Lin-Fa Wang, H. Benjamin Larman, “Deconvoluting Virome-Wide Antiviral Antibody Profiling Data” bioRxiv, 2018
  45. Tiezheng Yuan, Divya Mohan, Uri Laserson, Ingo Ruczinski, Alan Baer, H. Benjamin Larman, “Improved Analysis of Phage ImmunoPrecipitation Sequencing (PhIP-Seq) Data Using a Z-score Algorithm” bioRxiv, 2018
  46. https://www.ncbi.nlm.nih.gov/pubmed/29790966
  47. https://www.ncbi.nlm.nih.gov/pubmed/28794021
  48. Sisniega, J. W. Stayman, J. Yorkston, J. H. Siewerdsen, W. Zbijewski, “Motion Compensation in Extremity Cone-Beam CT Using a Penalized Image Sharpness Criterion,” Physics in Medicine and Biology, 62 (9), 3712, 2017
  49. Cao, A, Sisniega, M. Brehler, JW. Stayman J. Yorkston,  J.H.Siewerdsen, W. Zbijewski, ” Modeling and Evaluation of a High-Resolution CMOS Detector for Cone-Beam CT of the Extremities,”  Medical Physics 45, 114–130, 2018.
  50. A Sisniega, G Thawait, D Shakoor, J H Siewerdsen, S Demehri, W Zbijewski, “Motion Compensation in Dedicated Extremity Cone-Beam Computed Tomography: Feasibility Study – A Technical Note,”  Radiology, 2018, in preparation.
  51. Cao, A, Sisniega, M. Brehler, J.W. Stayman J. Yorkston,  J.H.Siewerdsen, W Zbijewski, “High-resolution extremity cone-beam CT with a CMOS detector: Task-based optimization of scintillator thickness,” SPIE Medical Imaging, Orlando, FL, 1013210-1013210-6, March 2017.  doi:10.1117/12.2255695
  52. Cao, M. Brehler, A, Sisniega, S. Tilley II, M. M. Shiraz Bhurwani, J.W. Stayman J. Yorkston, J.H.Siewerdsen, W Zbijewski, “High-resolution extremity cone-beam CT with a CMOS detector: evaluation of a clinical prototype in quantitative assessment of bone microarchitecture,” SPIE Medical Imaging, Houston, TX,105730R, March 2018,  doi:10.1117/12.2293810
  53. G Thawait, A Sisniega, D Shakoor, J W Stayman, J H Siewerdsen, W Zbijewski, S Demehri, “Effect of motion compensation on the image quality of cone beam CT scans in musculoskeletal setting,”  RSNA Annual Meeting 2017
  54. Q Cao, A Sisniega, J W Stayman, J Yorkston, J H Siewerdsen, W Zbijewski, “Quantitative extremity cone-beam CT using model-based polyenergetic reconstruction,”  RSNA Annual Meeting 2018
  55. Wu, J. Lee, C. Meneveau and T. Zaki, “Application of a self-organizing map to identify the turbulent-boundary-layer interface in a transitional flow” (2018), Phys. Rev. Fluids (submitted
  56. A. Martínez-Tossas and C. Meneveau, “Filtered lifting line theory and application to the actuator line model” (2018), J. Fluid Mech. (submitted).
  57. Wu, H.H. See, C. Meneveau & R. Mittal, “Response of a Laminar Separation Bubble to Zero-Net Mass Flux Actuation” (2017), abstract accepted at the 2018 AIAA Aviation and Aeronautics Forum and Exposition.
  58. J.A.M. Stevens, L.A. Martinez-Tossas, & C. Meneveau, “Comparison of wind farm large eddy simulations using actuator disk and actuator line models with wind tunnel experiments” (2018), Renewable Energy 116, 470-478.
  59. Sadique, X.I.A. Xiang, C. Meneveau & R. Mittal: “Aerodynamic properties of rough surfaces with high aspect–ratio roughness elements – Effect of aspect–ratio and arrangements” (2017), Bound. Layer Met. 163, 203-224.
  60. Hameduddin, C. Meneveau, T.A. Zaki and D.F. Gayme, “Geometric decomposition of the conformation tensor in viscoelastic turbulence” (2017), J. Fluid Mech. 842, 395-427.
  61. Shapiro, J. Meyers, C. Meneveau & D. Gayme, “Dynamic wake modeling and state estimation for improved model-based receding horizon control of wind farms”, IEEE Control Systems Society Conference Management System (ACC), 2017 (pp. 709-716).
  62. Gray, H., Bouwer, E., Young, C. “Antimicrobial and Multi-drug Resistance in Wastewater Bacterial Communities”. Environmental Health and Engineering Seminar.
    Environmental Health and Engineering Departmental Annual Retreat, January 2018
  63. Gray, H., Bouwer, E., Young, C. “Identifying antimicrobial and multi-drug resistance in bacterial wastewater communities, with conventional techniques and a novel microfluidic droplet approach”. Gordon Research Conference: Water, June 2018.
  64. Gray, H., Bouwer, E. “Antimicrobial Resistance in Wastewater: Detecting, Tracing and Characterizing Superbugs in Baltimore and Peru”. Engineering Innovations Lecture, July 2018.
  65. Gray, H., Bouwer, E., Young, C. “Antimicrobial and multidrug resistance in Wastewater in Baltimore, MD and Iquitos, Peru IGERT Colloquium”. IGERT: Water, Climate, and Health Final Symposium, June 2018.
  66. Gray, H., Bouwer, E., Young, C. “Antimicrobial and Multi-drug Resistance in Wastewater Bacterial Communities”. Environmental Health and Engineering Seminar. Environmental Health and Engineering Departmental Seminar, February 2018.
  67. J. Dagdigian, “Theoertical investigation of rotationally inelastic collisions of CH(X2Pi) with hydrogen atoms,” J. Chem. Phys. 146, 224308 (2017)
  68. J. Dagdigian, “Interaction of C2H with molecular hydrogen: Ab initio potential energy surface and scattering calculations,” J. Chem. Phys. 148, 024304 (2018).
  69. J. Dagdigian, “Collisional excitation of ArH+ by hydrogen atoms,” Mon. Not. R. Soc. Astron. Soc. 477, 802 (2018).
  70. J. Dagdigian, “Applications of quantum statistical methods to the treatment of collisions,” Adv. Chem. Phys. 163, 1-43 (2018).
  71. Lee I, Rasoul BA, Holub AS, Lejeune A, Enke RA, Timp W. Whole genome DNA methylation sequencing of the chicken retina, cornea and brain. Sci Data. 2017 Oct 10;4:170148. PMCID: PMC5634322
  72. Luo R, Zimin A, Workman R, Fan Y, Pertea G, Grossman N, Wear MP, Jia B, Miller H, Casadevall A, Timp W, Zhang SX, Salzberg SL. First Draft Genome Sequence of the Pathogenic Fungus Lomentospora prolificans (Formerly Scedosporium prolificans). G3. 2017 Nov 6;7(11):3831–3836. PMCID: PMC5677167
  73. Tamma PD, Fan Y, Bergman Y, Sick-Samuels AC, Hsu AJ, Timp W, Simner PJ, Prokesch BC, Greenberg DE. Successful Treatment of Persistent Burkholderia cepacia Complex Bacteremia with Ceftazidime-Avibactam. Antimicrob Agents Chemother [Internet]. 2018 Apr;62(4). Available from: http://dx.doi.org/10.1128/AAC.02213-17 PMCID: PMC5913954
  74. Simner PJ, Antar AAR, Hao S, Gurtowski J, Tamma PD, Rock C, Opene BNA, Tekle T, Carroll KC, Schatz MC, Timp W. Antibiotic pressure on the acquisition and loss of antibiotic resistance genes in Klebsiella pneumoniae. J Antimicrob Chemother [Internet]. 2018 Apr 10; Available from: http://dx.doi.org/10.1093/jac/dky121 PMCID:PMC6005101
  75. Timp, W., “Applications of modification detection in nanopore sequencing,”, Invited Talk Boston University Seminar, May 2018
  76. Gilpatrick, T., “Cas9 targeted enrichment for nanopore profiling of methylation at known cancer drivers,” Plenary Talk, London Calling, May 2018
  77. Lee, I., “Simultaneous methylation and chromatin accessibility profiling on breast cancer cells,” Talk, London Calling, May 2018
  78. Fan, Y. “Bacterial sequencing and assembly for analysis of antibiotic resistance genes and mutations,” Talk, Sequencing Finishing and Analysis in the Future (SFAF), May 2018
  79. Timp, W., “Applications of modification detection in nanopore sequencing,”, Biology of Genomes Nanopore Workshop, May 2018
  80. Lee, I., “Simultaneous methylation and chromatin accessibility profiling on breast cancer cells,” Talk, CSHL Nuclear Organization & Function, May 2018
  81. Pashakhanloo F, Herzka DA, Halperin H, McVeigh ER, Trayanova N. Role of 3-Dimensional Architecture of Scar and Surviving Tissue in Ventricular Tachycardia: Insights From High-Resolution Ex Vivo Porcine Models. Circ Arrhythm Electrophysiol. 2018 Jun;11(6):e006131. doi: 10.1161/CIRCEP.117.006131.
  82. Misra S, Zahid S, Prakosa A, Saju N, Tandri H, Berger RD, Marine JE, Calkins H, Zipunnikov V, Trayanova N, Zimmerman SL, Nazarian S. Field of view of mapping catheters quantified by electrogram associations with radius of myocardial attenuation on contrast-enhanced cardiac computed tomography. Heart Rhythm. 2018 Jun 2. pii: S1547-5271(18)30564-2. doi: 10.1016/j.hrthm.2018.05.031. [Epub ahead of print]
  83. Dhamala J, Arevalo HJ, Sapp J, Horácek BM, Wu KC, Trayanova N, Wang L. Quantifying the uncertainty in model parameters using Gaussian process-based Markov chain Monte Carlo in cardiac electrophysiology. Med Image Anal. 2018, 48:43-57. doi: 10.1016/j.media.2018.05.007. [Epub ahead of print]
  84. Boyle PM, Hakim JB, Zahid S, Franceschi WH, Murphy MJ, Vigmond EJ, Dubois R, Haïssaguerre M, Hocini M, Jaïs P, Trayanova N, Cochet H. Comparing Reentrant Drivers Predicted by Image-Based Computational Modeling and Mapped by Electrocardiographic Imaging in Persistent Atrial Fibrillation. Front Physiol. 2018 Apr 19;9:414. doi: 10.3389/fphys.2018.00414. eCollection 2018. Trayanova N, Boyle PM, Nikolov PP, Personalized Imaging and Modeling Strategies for Arrhythmia Prevention and Therapy, Curr Opin Biomed Eng. 2018 Mar;5:21-28. doi:10.1016/j.cobme.2017.11.007.
  85. Yuniarti AR, Setianto F, Marcellinus A, Hwang HJ, Choi SW, Trayanova N, Lim KM. Effect of KCNQ1 G229D Mutation on Cardiac Pumping Efficacy and Reentrant Dynamics in Ventricles: Computational Study, Int J Numer Method Biomed Eng. 2018 Feb 27. doi: 10.1002/cnm.2970. [Epub ahead of print]
  86. Boyle PM, Karathanos T, Trayanova N. Cardiac Optogenetics: 2018, JACC: Clin Electrophys. 2018, DOI: 10.1016/j.jacep.2017.12.006
  87. Cochet H, Dubois R, Yamashita S, Al Jefairi N, Berte B, Sellal  JB, Hooks D, Frontera A, Amraoui S, Zemoura A, Denis A, Derval N, Sacher F, Corneloup O, Latrabe V, Clément-Guinaudeau S, Relan J, Zahid S, Boyle PM, Trayanova N, Bernus O, Montaudon M, Laurent F,  Hocini M, Haïssaguerre M, Jaïs P, Relationship Between Fibrosis Detected on Late Gadolinium-Enhanced
    Cardiac Magnetic Resonance and Re-Entrant Activity Assessed With Electrocardiographic Imaging in Human Persistent Atrial Fibrillation, JACC: Clin Electrophys.
    4, 2018, http://dx.doi.org/10.1016/j.jacep.2017.07.019 (accompanied by an editorial).
  88. Boyle PM, Murphy MJ, Karathanos TV, Zahid S, Blake RC 3rd, Trayanova N. Termination of re-entrant atrial tachycardia via optogenetic stimulation with optimized spatial targeting: insights from computational models, J Physiol. 2018 Jan 15;596(2):181-196.
  89. Kang C, Badiceanu A, Brennan JA, Gloschat C, Qiao Y, Trayanova N, Efimov IR. β-adrenergic stimulation augments transmural dispersion of repolarization via modulation of delayed rectifier currents IKs and IKr in the human ventricle. Sci Rep. 2017 Nov 21;7(1):15922.
  90. Heikhmakhtiar AK, Ryu AJ, Shim EB, Song KS, Trayanova N, Lim KM. Influence of LVAD function on mechanical unloading and electromechanical delay: a simulation study. Med Biol Eng Comput. 2018 56:911-921. doi: 10.1007/s11517-017-1730-y.
  91. Kim YS, Yuniarti AR, Song KS, Trayanova N, Shim EB, Lim KM. Computational analysis of the effect of mitral and aortic regurgitation on the function of ventricular assist devices using 3D cardiac electromechanical model. Med Biol Eng Comput. 2018 May;56(5):889-898. doi: 10.1007/s11517-017-1727-6.
  92. Kim CH, Song KS, Trayanova N, Lim KM. Computational prediction of the effects of the intra-aortic balloon pump on heart failure with valvular regurgitation using a 3D cardiac electromechanical model, Med Biol Eng Comput. 2018 May;56(5):853-863. doi: 10.1007/s11517-017-1731-x.
  93. Deng D, Murphy MJ, Hakim JB, Franceschi WH, Zahid S, Pashakhanloo F, Trayanova N, Boyle PM. Sensitivity of reentrant driver localization to electrophysiological parameter variability in image-based computational models of persistent atrial fibrillation sustained by a fibrotic substrate, Chaos. 2017 Sep;27(9):093932. doi: 10.1063/1.5003340.
  94. Cerrone M, Montnach J, Lin X, Zhao YT, Zhang M, Agullo-Pascual E, Leo-Macias A, Alvarado FJ, Dolgalev I, Karathanos TV, Malkani K, Van Opbergen CJM, van Bavel JJA, Yang HQ, Vasquez C, Tester D, Fowler S, Liang F, Rothenberg E, Heguy A, Morley GE, Coetzee WA, Trayanova N, Ackerman MJ, van Veen TAB, Valdivia HH, Delmar M.Plakophilin-2 is required for transcription of genes that control calcium cycling and cardiac rhythm, Nature Communications. 2017 Jul 24;8(1):106. doi: 10.1038/s41467-017-00127-0.
  95. Trayanova N, Pashakhanloo F, Wu KC, Halperin HR. Imaging-Based Simulations for Predicting Sudden Death and Guiding Ventricular Tachycardia Ablation. Circ Arrhythm Electrophysiol. 2017 Jul;10(7). pii: e004743. doi: 10.1161/CIRCEP.117.004743.
  96. Zile MA, Trayanova N. Myofilament protein dynamics modulate EAD formation in human hypertrophic cardiomyopathy, Prog Biophys Mol Biol. 2017 Nov;130(Pt B):418-428. doi: 10.1016/j.pbiomolbio.2017.06.015.
  97. Dhamala J, Arevalo HJ, Sapp J, Horacek M, Wu KC, Trayanova N, Wang L. Spatially Adaptive Multi-Scale Optimization for Local Parameter Estimation in Cardiac Electrophysiology. IEEE Trans Med Imaging. 2017 Sep;36(9):1966-1978. doi: 10.1109/TMI.2017.2697820.
  98. https://www.ncbi.nlm.nih.gov/pubmed/29790966
  99. https://www.ncbi.nlm .nih.gov/pubmed/28794021
  100. Antibiotic pressure on the acquisition and loss of antibiotic resistance genes in Klebsiella pneumoniaeSimner, PJ, Antar, AA, Hai, S, Gurtowski, J, Tamma, PD, Rock, C, Opene, BNA, Tekle, T, Carroll, KC, Schatz, MC, Timp, W (2018) Journal of Antimicrobial Chemotherapy https://doi.org/10.1093/jac/dky121
  101. Dingquan Wang and Jason Eisner (to appear 2018). Surface statistics of an unknown language indicate how to parse it.  Transactions of the Association for Computational Linguistics (TACL).
  102. Chu-Cheng Lin and Jason Eisner (2018). Neural particle smoothing for sampling from conditional sequence models. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT), pp. 929–941. [ bib ]
  103. Dingquan Wang and Jason Eisner (2017). Fine-grained prediction of syntactic typology: Discovering latent structure with supervised learning. Transactions of the Association for Computational Linguistics (TACL), 5:147–161. [ bib ]
  104. Hongyuan Mei and Jason Eisner (2017). The neural Hawkes process: A neurally self-modulating multivariate point process. In Advances in Neural Information Processing Systems (NIPS). [ bib ]
  105. Dingquan Wang and Jason Eisner (2016). The Galactic Dependencies treebanks: Getting more data by synthesizing new languages. Transactions of the Association for Computational Linguistics (TACL), 4:491–505. [ bib ]
  106. “Transcriptional and Epigenomic Landscapes of CNS and non-CNS Vascular Endothelial Cells” by Mark F. Sabbagh, Jacob Heng, Chongyuan Luo, Rosa Gomez Castanon, Joseph R. Nery, Amir Rattner, Loyal A. Goff, Joseph R. Ecker, and Jeremy Nathans
  107. Yang, G., L. Florea (2017) — “JULiP++: Fast and ultra-sensitive identification of differential splicing events from large RNA-seq data collections”, Cold Spring Harbor Laboratory Meeting – Genome Informatics, Cold Spring Harbor, NY (poster)
  108. Song, L., L. Florea (2017) — “CLASSX: Scalable simultaneous transcript assembly of multiple RNA-seq data sets”, Cold Spring Harbor Laboratory Meeting – Genome Informatics, Cold Spring Harbor, NY (poster).
  109. Xia, J. Lu, and G. Tryggvason. Fully Resolved Numerical Simulations of Fused Deposition Modeling. Part II—Solidification, Residual Stresses, and Modeling of the Nozzle. Rapid Prototyping Journal. To Appear, accepted 2/23/2018 (arXiv:1711.07094)
  110. de la Vega, S. A. Kassin, C. Pacifici, et al., “Galaxies by the pixel: Stellar Mass and SFR Maps of CANDELS Galaxies.” CANDELS Team Meeting, April 2018
  111. Can cut-generating functions be good and efficient? by Amitabh Basu and Sriram Sankaranarayanan. This is under submission in the SIAM Journal on Optimization, a top outlet for mathematical optimization research.
  112. “Learning with cutting planes” a manuscript in preparation by Amitabh Basu, Marco Molinaro, Tu Nguyen, Sriram Sankaranarayanan. We hope to also submit this to a top mathematical optimization journal soon.
  113. Mixed-Integer Programming (MIP) 2018 (poster presentation). The work got an honorable mention in a poster competition:https://or.clemson.edu/mip-2018/posters/
  114. International Symposium on Mathematical Programming (ISMP) 2018 (two oral presentations based on the above papers).
  115. Modeling and OPtimization: Theory and Applications (MOPTA) 2018 (oral presentation).
  116. Chan, C.-H. and Krolik, J.H., Astrop. J. 843, 58 (2017)
  117. Shiokawa, J., Cheng, R.M., Noble, S.C., and Krolik, J.H., Astrop. J.  861, 15 (2018)
  118. U. Bretheim, C. Meneveau, and D. F. Gayme, \The restricted nonlinear large eddy simulation approach to reduced-order wind farm modeling,” J. Renewable Sustainable Energy, vol. 10, no. 4, p. 043307, 2018.
  119. Hameduddin, C. Meneveau, T. A. Zaki, and D. F. Gayme, \Geometric decomposition of theconformation tensor in viscoelastic turbulence,” J. Fluid Mech., vol. 842, p. 395427, 2018.
  120. U. Bretheim, Numerical simulations of the restricted nonlinear system. Ph.d., Johns Hopkins University, Baltimore, MD, Feb. 2018.
  121. Hameduddin, Tackling viscoelastic turbulence. Ph.d., Johns Hopkins University, Baltimore, MD, May 2018.
  122. R. Shapiro, J. Meyers, C. Meneveau, and D. F. Gayme, \Wind farms providing secondaryfrequency regulation: Evaluating the performance of model-based receding horizon control,” Wind Energy Science, vol. 3, no. 1, pp. 11{24, 2018.
  123. R. Shapiro, D. F. Gayme, and C. Meneveau, \Modelling yawed wind turbine wakes: A lifting line approach,” J. Fluid Mech., vol. 841, p. R1, 2018.
  124. R. Shapiro, J. Meyers, C. Meneveau, and D. F. Gayme, \Coordinated pitch and torque control of wind farms for power tracking,” in Proc. of American Control Conf., (Milwaukee, WI), pp. 717{722, June 2018.
  125. Almansi, Mattia, Thomas W. N. Haine, Robert S. Pickart, Marcello G. Magaldi, Renske Gelderloos, and Dana Mastropole (2017). High-Frequency Variability in the Circulation and Hydrography of the Denmark Strait Overflow from a High-Resolution Numerical Model. Journal of Physical Oceanography 47(12), 2999–3013. eprint: https://doi.org/10.1175/JPO-D-17-0129.1.
  126. Almansi Mattia, Thomas W. N. Haine, and Renske Gelderloos (2018). The Evolution of Mesoscale Features in Denmark Strait Overflow. In: 16th ASOF-ISSG Meeting and Workshop. LOCEAN, Sorbonne Université, Paris, France.
  127. Almansi Mattia, Thomas W. N. Haine, and Renske Gelderloos (2018). The Evolution of Mesoscale Features in Denmark Strait Overflow. In: Ocean Sciences Meeting. Portland, Oregon, USA. https : / / agu.com/agu/os18/preliminaryview.cgi/Paper304691.html.
  128. Almansi Mattia, Thomas W. N. Haine, Robert S. Pickart, Marcello G. Magaldi, Renske Gelderloos, and Dana Mastropole (2017). Variability in the Circulation and Hydrography of Denmark Strait from a High-resolution Numerical Model. In: Irminger Sea Regional Science Workshop. National Oceanography Centre,
    Southampton, U.K. http://conference.noc.ac.uk/irminger-workshop2017.
  129. Gelderloos and T.W.N. Haine (2018). Potential for Arctic Sea Ice Cover Response to Changing Atlantic Inflow. Oral presentation at the Arctic-SubArctic Ocean Fluxes (ASOF) meeting (Paris, France, April 2018).
  130. Faisal Mahmood, Richard Chen, and Nicholas J. Durr. “Unsupervised Reverse Domain Adaptation for Synthetic Medical Images via Adversarial Training.” IEEE Transactions on Medical Imaging(2018).
  131. Faisal Mahmood and Nicholas J. Durr. “Deep learning and conditional random fields-based depth estimation and topographical reconstruction from conventional endoscopy.” Medical Image Analysis(2018).
  132. Faisal Mahmood, Richard Chen, Sandra Sudarsky, Daphne Yu, and Nicholas J. Durr. “Deep Learning with Cinematic Rendering: Fine-Tuning Deep Neural Networks Using Photorealistic Medical Images.” arXiv preprint arXiv:1805.08400(2018).
  133. Faisal Mahmood, and Nicholas J. Durr. “Topographical reconstructions from monocular optical colonoscopy images via deep learning.” IEEE 15th International Symposium onBiomedical Imaging (ISBI 2018), 216-219.
  134. Faisal Mahmood, and Nicholas J. Durr. “Deep learning-based depth estimation from a synthetic endoscopy image training set.” Medical Imaging 2018: Image Processing. Vol. 10574. International Society for Optics and Photonics, 2018.
  135. Faisal Mahmood, Richard Chen, Nicholas J Durr. “Adversarial Training for Adapting Networks Trained on Synthetically Generated Colonoscopy Data to Real Data” IEEE 15th International Symposium onBiomedical Imaging (ISBI 2018).
  136. Richard Chen, Mahmood F, Nicholas J Durr. “Improved Computer-Aided Polyp Localization using Reverse Domain-Adapted Endoscopy Images” IEEE 15th International Symposium onBiomedical Imaging (ISBI 2018).
  137. Faisal Mahmood, Norman Nishioka, Nicholas J Durr. “Quantitative polyp size measurements with photometric stereo endoscopy enhanced by deep learning” SPIE Photonics West 2018.
  138. Liang, X.-Z., C. Sun, X. Zheng, Y. Dai, M. Xu, H.I. Choi, T. Ling, F. Qiao, X. Kong, X. Bi, L. Song, and F. Wang, 2018: CWRF Performance at downscaling China climate characteristics. Climate Dynamics, DOI: 10.1007/s00382-018-4257-5.
  139. Sun, C. and X.-Z. Liang, 2018: Extreme precipitation simulation and its dependence on cumulus parameterization. Journal of Climate (to be submitted soon).
  140. Liang, X.-Z., Q. Li, H. Mei, and M. Zeng, 2018: Multi-grids nesting capability to represent convections across the gray zone, Journal of Advances in Modeling Earth Systems (In preparation).
  141. A Modeling Framework to Couple Food, Energy, and Water in the Teleconnected Corn and Cotton Belts (Poster & oral presentation), 2018 NSF Innovations at the Nexus of Food, Energy, and Water (INFEWS) Principal Investigators’ (PI) Meeting, National Science Foundation Alexandria, VA, May 16-18, 2018
  142. Liang, Xin-Zhong and Chao Sun, Understanding CWRF Ability to Simulate U.S. Extreme Precipitation Characteristics, AMS meeting (2018)
  143. Chao Sun and Xin-Zhong Liang, Using CWRF Multi-physics Ensemble to Improve Extreme Precipitation Prediction, AGU 2018 fall meeting, Washington DC, December 10-14, 2018
  144. Yufeng He, Chao Sun, Xin-Zhong Liang, Deepak Jaiswal, Stephen P. Long, A coupled modeling system for studying the impacts of growing biofuel crops in marginal lands on the food-energy-water nexus (Oral presentation), AGU 2018 fall meeting, Washington DC, December 10-14, 2018
  145. Rongsheng Jiang, Xin-Zhong Liang, Chao Sun, Evaluation of Planetary Boundary Layer Parameterizations for U.S. Climate Simulation (Oral presentation or Poster), AGU 2018 fall meeting, Washington DC, December 10-14, 2018
  146. Lei Sun, Xin-Zhong Liang, Min Xu, Tiejun Ling, Xuhui Lee, Evaluation of a multilevel turbulence closure model for shallow lakes against other models (Oral presentation or Poster), AGU 2018 fall meeting, Washington DC, December 10-14, 2018
  147. Kennedy, J., and X.Z. Liang. Applying Land Data Assimilation to Simulate Days Suitable for Fieldwork for Agricultural Decision-Making. Submitted to 2018 AGU Fall Meeting, Washington DC, 10-14 Dec. 2018
  148. Guros, N. ‡, A. Balijepalli, & J.B. Klauda. “Analyzing the Effects of Lipid Type on the a-Hemolysin Nanopore and 5HT3 Receptor Structure and Gating using Molecular Dynamics Simulations.” Biophysical Society (2017).
  149. Khakbaz, P. ‡ & J.B. Klauda. “Simulations Provide Insight into Improving the Tolerance of the E. coli membrane.” Biophysical Society (2017).
  150. Leonard, A. ‡ & J.B. Klauda. “Modeling Ethers with Molecular Dynamics.” Biophysical Society (2017).
  151. Wang, E.† & J.B. Klauda. “Examination of lipid bilayer mixtures containing sphingomyelin and cholesterol by molecular dynamics simulation.” American Chemical Society-Fall Meeting (2017).
  152. Bera, I.‖ & J.B. Klauda. “All-atom simulation studies on lipid bilayers, composed of sphingomyelin, glycerophospholipids and cholesterol.” American Chemical Society-Fall Meeting (2017).
  153. Bera, I.‖ & J.B. Klauda. “Structural events in a bacterial uniporter leading to translocation of glucose inside the cytosol.” Biophysics Society (2018).
  154. Guros, N. ‡, A. Balijepalli, & J.B. Klauda. “Analyzing the effects of membrane lipid type on transmembrane proteins (αHL and 5-HT3) using molecular dynamics simulations.” Biophysics Society (2018).
  155. Wang, E.† & J.B. Klauda. “Molecular dynamics simulations of stratum corneum model membranes.” Biophysics Society (2018).
  156. S. D’Souza, M.B. Nebel, N. Wymbs, S. Mostofsky, A. Venkataraman. A Generative Discriminative Basis Learning Framework to Predict Autism Spectrum Disorder Severity. In Proc. ISBI: International Symposium on Biomedical Imaging, 2018.
  157. Nandakumar, N.S. D’Souza, H. Sair, A. Venkataraman. A Modified K-Means Algorithm for Resting State fMRI Analysis of Brain Tumor Patients, As Validated by Language Localization. In Proc. ISBI: International Symposium on Biomedical Imaging, 2018.
  158. Craley, E. Johnson, A. Venkataraman. Robust Seizure Detection Using Coupled Hidden Markov Models. In Proc. ISBI: International Symposium on Biomedical Imaging, 2018.
  159. S. D’Souza, N. Wymbs, M.B. Nebel, S. Mostofsky and A. Venkataraman. “A Generative-Discriminative Basis Learning Framework to Predict Clinical Severity from Resting State Functional MRI Data”. To Appear in MICCAI: International Conference on Medical Image Computing and Computer Assisted Intervention, 2018.
  160. Craley, E. Johnson and A. Venkataraman. “A Novel Method for Epileptic Seizure Detection Using Coupled Hidden Markov Models”. To Appear in MICCAI: International Conference on Medical Image Computing and Computer Assisted Intervention, 2018.
  161. Nandakumar and N.S. D’Souza and J. Craley and K. Manzoor and J. Pillai and S. Gujar and H. Sair and A. Venkataraman. “Defining Patient Specific Functional Parcellations in Lesional Cohorts via Markov Random Fields”. To Appear in CNI: Connectomics in Neuroimaging, 2018
  162. Divya Mohan, Daniel L. Wansley, Brandon M. Sie, Muhammad S. Noon, Alan N. Baer, Uri Laserson & H. Benjamin Larman, “PhIP-Seq Characterization of Serum Antibodies Using Oligonucleotide Encoded Peptidomes” (accepted at Nature Protocols)
  163. Tory P. Johnson,* H. Benjamin Larman,* Myoung-Hwa-Lee, Stephen S. Whitehead, Jeffrey Kowalak, Camilo Toro, Juyun Kim1, Arline Faustin, Carlos Pardo, Sanjay Kottapalli, Jonathan Howard, Daniel Monaco, James Weisfeld-Adams, Craig Blackstone, Steven Galetta, Matija Snuderl, William A. Gahl, Ilya Kister & Avindra Nath, “Fatal Case of Chronic Dengue Encephalitis Presenting as Progressive Dementia” (under review)
  164. Daniel Monaco, Sanjay Kottapalli, Tiezheng Yuan, Florian Breitwieser, Danielle Anderson, Limin Wijaya, Kevin Tan, Wan Ni Chia, Kai Kammers, Mario Caturegli, Kathleen Waugh, Marian Rewers, Lin-Fa Wang, H. Benjamin Larman, “Deconvoluting Virome-Wide Antiviral Antibody Profiling Data” bioRxiv, 2018
  165. Tiezheng Yuan, Divya Mohan, Uri Laserson, Ingo Ruczinski, Alan Baer, H. Benjamin Larman, “Improved Analysis of Phage ImmunoPrecipitation Sequencing (PhIP-Seq) Data Using a Z-score Algorithm” bioRxiv, 2018
  166. Russ Taylor. “Pose Estimation of Periacetabular Osteotomy Fragments with Intraoperative X-Ray Navigation”. IEEE Transactions on Biomedical Engineering, 2018.
  167. Marro, E. A.; Press, E. M.; Siegler, M. A.; Klausen, R. S. “Directional Building Blocks Determine Linear and Cyclic Silicon Architectures” J. Am. Chem. Soc. 2018, 140, 5976-5986
  168. van de Wouw, H. L.; Awuyah, E. C.; Baris, J. I.; Klausen, R. S. “An Organoborane Vinyl Monomer with Styrene-like Radical Reactivity: Reactivity Ratios and Role of Aromaticity” Macromolecules 2018, In press
  169. A Critical Assessment of CMB Limits on Dark Matter-Baryon Scattering: New Treatment of the Relative Bulk Velocity Kimberly K. Boddy, Vera Gluscevic, Vivian Poulin, Ely D. Kovetz, Marc Kamionkowski, Rennan Barkana.  e-Print: arXiv:1808.00001
  170. Tighter Limits on Dark Matter Explanations of the Anomalous EDGES 21cm Signal  Ely D. Kovetz, Vivian Poulin, Vera Gluscevic, Kimberly K. Boddy, Rennan Barkana, Marc Kamionkowski.  e-Print: arXiv:1807.11482
  171. Studying the Milky Way Pulsar Population with Cosmic-Ray Leptons Ilias Cholis, Tanvi Karwal, Marc Kamionkowski (Johns Hopkins U.). e-Print: arXiv:1807.05230
  172. Cosmological implications of ultra-light axion-like fields  Vivian Poulin (Johns Hopkins U. (main)), Tristan L. Smith (Swarthmore Coll.), Daniel Grin (Haverford Coll.), Tanvi Karwal, Marc Kamionkowski (Johns Hopkins U.).  e-Print: arXiv:1806.10608
  173. Implications of an extended dark energy cosmology with massive neutrinos for cosmological tensions  Vivian Poulin, Kimberly K. Boddy, Simeon Bird, Marc Kamionkowski  Published in Phys.Rev. D97 (2018) no.12, 123504  e-Print: arXiv:1803.02474
  174. Features in the Spectrum of Cosmic-Ray Positrons from Pulsars  Ilias Cholis, Tanvi Karwal, Marc Kamionkowski (Johns Hopkins U.).  Published in Phys.Rev. D97 (2018) no.12, 123011  e-Print: arXiv:1712.00011.
  175. Xingfeng He, Yizhou Zhu, Alexander Epstein, Yifei Mo*, “Statistical Variances of Diffusional Properties from Ab Initio Molecular Dynamics Simulations”, NPJ Computational Materials, 4, 18 (2018)
  176. Qiang Bai, Xingfeng He, Yizhou Zhu, Yifei Mo*, “First Principles Study of Oxyhydride H- Ion Conductors: Toward Facile Anion Conduction in Oxide-Based Materials”, ACS Applied Energy Materials, 1(4), 1626-1634 (2018)
  177. Qiang Bai, Yizhou Zhu, Xingfeng He, Eric Wachsman, Yifei Mo*, “First Principles Hybrid Functional Study of Small Polarons in Doped SrCeO3 Perovskite: Towards Computation Design of Materials with Tailored Polaron”, Ionics 24(4), 1139-1151 (2018)
  178. Xingfeng He, Yizhou Zhu, Yifei Mo*, “Origin of Fast Ion Diffusion in Super-Ionic Conductors” Nature communications, 8, 15893 (2017)
  179. Yizhou Zhu, Xingfeng He, Yifei Mo*, “Strategies Based on Nitride Materials Chemistry to Stabilize Li Metal Anode”, Advanced Science, 1600517 (2017)
  180. Xingfeng He, Ph.D., “First Principles Computational Study of Fast Ionic Conductors”, 2018
  181. Yizhou Zhu, Ph.D., “Atomistic Modeling of Solid Interfaces in All-Solid-State Li-Ion Batteries”, 2018
  182. Mo, “First-Principles Computation Study and Design for Solid Electrolyte–Electrode Interfaces in All-Solid-State Li-Ion Batteries”, Materials Research Society (MRS) Spring Meeting, Phoenix AZ (04/2018) (Invited)
  183. Mo, “Computation Accelerated Design of Materials and Interfaces for All-Solid-State Li-ion Batteries”, Nature Conference on Materials Electrochemistry: Fundamentals & Applications, Shenzhen, China (01/2018) (Invited)
  184. Mo, “Design Strategies for Materials and Interfaces in All-Solid-State Li-ion Batteries”, American Chemical Society National meeting, Washington DC (08/2017) (Invited)
  185. Mo, “Computation Accelerated Design of Materials and Interfaces for Solid-State Batteries”, Carnegie Institute of Science, Washington DC (07/2017) (Invited)
  186. Mo, “Enabling All-Solid-State Li-ion Batteries Through Computation-Guided Design of Materials and Interfaces”, Beyond Lithium Ion Symposium-10 (BLI-X), IBM Research-Almaden, CA (06/2017) (Invited)
  187. Mo, “Computation-Guided Understanding and Design of Interfaces in All-Solid-State Li-ion Batteries”, 17thAnnual Advanced Automotive Battery Conference (AABC), San Francisco, CA (06/2017) (Invited)
  188. Mo, “Computation-Guided Understanding and Design of Interfaces in All-Solid-State Li-ion Batteries”, International Battery Seminar, Fort Lauderdale, FL (03/2017) (Invited)
  189. Mo, “Computation-Guided Understanding and Design of Solid-Solid Interfaces in All-Solid-State Li-ion Batteries”, Munich Battery Discussion, Technical University of Munich, Munich, Germany (03/2017) (Invited)
  190. Mo, “Accelerated Computation Design of Materials and Interfaces in All-Solid-State Li-ion Batteries”, 41st International Conference and Expo on Advanced Ceramics and Composites (ICACC), American Ceramic Society, Daytona Beach, FL (01/2017) (Invited)
  191. Mo, “Accelerated Computational Materials Design and Discovery for Fast Ion Conducting Materials”, Electronic Materials and Applications (EMA) 2017, American Ceramic Society national meeting, Orlando, FL (01/2017) (Invited)
  192. He, Y. Mo, “Universal Strategy to Design Super-Ionic Conductors through First Principles Computation”, Materials Research Society (MRS) Spring Meeting, Phoenix AZ (04/2018)
  193. Zhu, Y. Mo., “Atomistic Modeling of Interface Transport in All-Solid-State Li-ion Batteries”, Materials Research Society (MRS) Spring Meeting, Phoenix AZ (04/2018)
  194. Zhu, Y. Mo., “Novel Strategies for Lithium Metal Anode Protection from Computation-Guided Materials Discovery”, Materials Research Society (MRS) Spring Meeting, Phoenix AZ (04/2018)
  195. He, Y. Zhu, Y. Mo, “Universal Strategy to Design Super-Ionic Conductors through First Principles Computation”, Materials Research Society (MRS) Fall Meeting, Boston MA (11/2017)
  196. He, Y. Zhu, Y. Mo, “Universal Design Strategy for Li Super-Ionic Conductors in All-Solid-State Li-ion Batteries : A First-Principles Study”, 232nd Electrochemical Society (ECS) Meeting, National Harbor, Maryland (10/2017)
  197. Zhu, X. He, Y. Mo., “Novel Strategies for Lithium Metal Anode Protection Based on Nitride Materials Chemistry: Insight from First Principle Calculations”, 232nd Electrochemical Society (ECS) Meeting, National Harbor, Maryland (10/2017)
  198. Zhu, X. He, Y. Mo., “Electrochemical and Chemical Stability of Solid Electrolyte–Electrode Interfaces: A First Principles Computation Study”, 232nd Electrochemical Society (ECS) Meeting, National Harbor, Maryland (10/2017) (Poster)
  199. Bai, Y. Mo, “Understanding and Designing Novel H Ionic Conductors based on First Principles Calculations”, 232nd Electrochemical Society (ECS) Meeting, National Harbor, Maryland (10/2017)
  200. Bai, Y. Zhu, X. He, E. Wachsman, Y. Mo, “Accelerated Computational Design of Mixed Protonic and Electronic Conductors through Tailoring Polaron”, 232nd Electrochemical Society (ECS) Meeting, National Harbor, Maryland (10/2017)
  201. He, Y. Zhu, Y. Mo, “Facilitating fast ion diffusion in solids: Origin of super-ionic conductors”, American Chemical Society (ACS) national meeting, Washington DC (08/2017)
  202. Zhu, X. He, Y. Mo., “Novel Strategies for Lithium Metal Anode Protection Based on Nitride Materials Chemistry: A First Principles Study”, American Chemical Society (ACS) national meeting, Washington DC (08/2017)
  203. Bai, Y. Mo, “Tailoring Polaron in Materials through Computation Design: A First Principles Hybrid Functional Study on SrCeO3”, American Chemical Society (ACS) national meeting, Washington DC (08/2017)
  204. CMS Tracker Group (W. Adam et al.), “Trapping in proton irradiated p+-n-n+ silicon sensors at fluences anticipated at the HL-LHC outer tracker”, JINST 11, P04023, 2016.
  205. V. Gritsan, R. Rontsch, M. Schulze, M. Xiao, “Constraining anomalous Higgs boson couplings to the heavy flavor fermions using matrix element techniques”, Physical Review D94, 055023, 2016.
  206. CMS Collaboration, “Combined search for anomalous pseudoscalar HVV couplings in VH production and H -> VV decay”, Physics Letters B759, 672, 2016.
  207. CMS Collaboration, “Search for heavy resonances that decay into a vector boson and a Higgs boson in hadronic final states at sqrt(s)=13 TeV”, European Physics Journal C77, 636, 2017.
  208. CMS Collaboration, “Search for low mass vector resonances decaying to quark-antiquark pairs in proton-proton collisions at sqrt(s) = 13 TeV”, Physical Review Letters 119, 111802, 2017.
  209. –Gene Expression Profiles of Pediatric Tuberculosis Patients and Exposed Controls from India. RePORT International Conference; Rio de Janeiro, Brazil. September 2017
  210. Jeffrey A Tornheim, Differential Gene Expression as a Biomarker of Pediatric Tuberculosis. RePORT India Annual Meeting; New Delhi, India. February 2018
  211. Jeffrey A. Tornheim, Differential Gene Expression as a Biomarker of Pediatric Tuberculosis. Global Forum on TB Vaccines; New Delhi, India. February 2018
  212. Jeffrey A. Tornheim, Improving Diagnosis and Treatment Outcomes for Multidrug Resistant Tuberculosis in India. Johns Hopkins University School of Medicine Department of Medicine Research Retreat; Baltimore, MD. March 2018
  213. Jeffrey A. Tornheim, Drug Susceptibility of Rifampin-Resistant Tuberculosis Using Whole Genome Sequencing to Identify Genes of Interest in Pune, India, Union World Conference on Lung Health; Guadalajara, Mexico. October 2017
  214. Jeffrey A. Tornheim, Drug Susceptibility of Rifampin-Resistant Tuberculosis Using Whole Genome Sequencing to Identify Genes of Interest in Pune, India,  Johns Hopkins University School of Medicine Department of Medicine Research Retreat; Baltimore, MD. March 2018.
  215. Liu, A. Asthana, L. Cheng, and D. Mukherjee, “Unitary coupled-cluster based self-consistent polarization propagator theory: A third-order formulation and pilot applications”, J. Chem. Phys. 148, 244110 (2018).
  216. Liu and L. Cheng, “An atomic mean-field spin-orbit approach within exact two-component theory for a non-perturbative treatment of spin-orbit”, J. Chem. Phys. 148, 144108 (2018).
  217. H. Myhre, T. J. A. Wolf, L. Cheng, S. Nandi, S. Coriani, M. Guehr, and H. Koch, “A theoretical and experimental benchmark study of core-excited states in nitrogen”, J. Chem. Phys. 148, 064106 (2018).
  218. Gawrilow, H. Beckers, S. Riedel, and L. Cheng, “Matrix-Isolation and quantum-chemical analysis of the C3vconformer of XeF6, XeOF4, and their acetonitrile adducts”, J. Phys. Chem. A 122, 119-129 (2018).
  219. Liu, Y. Shen, A. Asthana, L. Cheng, “Two-component relativistic coupled-cluster methods using mean-field spin-orbit integrals”, J. Chem. Phys. 148, 034106 (2018).
  220. Zhang, Y. Yu, T. C. Steimle, and L. Cheng, “The electric dipole moments in the ground states of gold oxide, AuO, and gold sulfide, AuS”, J. Chem. Phys., 146, 064307 (2017).
  221. C. Steimle, D. L. Kokkin, C. Linton, and L. Cheng, “Characterization of the [18.28] 0 – a3D1 (0,0) Band of Tantalum Nitride, TaN”, J. Chem. Phys., 147, 154304 (2017).
  222. “Ab initio calculations of low-lying electronic states in metal-containing molecules”, 73th International Symposium on Molecular Spectroscopy, Champaign-Urbana, Illinois, (2018).
  223. “Accurate calculations of spin-orbit coupling in metal-containing molecules”, Spectroscopy and Kinetics on Multiple Potential Energy Surfaces, Telluride, CO, USA (2018)
  224. Yuchen Wang and David R. Yarkony, J. Chem. Phys. submitted (2018) Determining Whether Diabolical Singularities Limit the Accuracy of Molecular Property Based Diabatic Representations: The 1,21A States of Methylamine
  225. Addison et. Al. 2018 (ApJ 853, 119)   Bennett
  226. Huang et. al 2018 (arxiv 1804.05428) Bennett
  227. Invited talk at “Exploring Complex Free Energy Landscapes: Structure/Function Formation, Multiscales, and Long-timescales” workshop at Max Planck for Polymer Research in Mainz, Germany (forthcoming, June 2019)
  228. * Invited talk at “Three decades in Free Energy methods” conference at Santa Fe, New Mexico (forthcoming, June 2019)
  229. * Invited talk at CECAM/ECAM state-of-the-art workshop: Large scale activated event simulations, Vienna, Austria  (forthcoming, October 2018)
  230. * Invited talk at Gordon Research Conference on Water and Aqueous Solutions, New Hampshire (July 2018)
  231. * Invited talk at “Exploring and quantifying rough free energy landscapes” symposium at International School of Statistical Physics, Erice, Sicily, Italy (May 2018)
  232. * Invited talk at “Workshop on free energy methods, kinetics and markov state models in drug design” at Novartis Institutes for Biomedical Research, Boston (May 2018)
  233. * Seminar at Computer-Aided Drug Design Center, School of Pharmacy, University of Maryland, Baltimore (April 2018)
  234. * Seminar at Department of Chemistry and Biochemistry, Montana State University, Bozeman (March 2018)
  235. Leong, A.F.T., Robinson, A.K., Fezzaa, K., Sun, T., Sinclair, N., Casem, D.T., Lambert, P.K., Hustedt, C.J., Daphalapurkar, N.P., Ramesh, K.T., Hufnagel, T.C. Quantitative in situ studies of dynamic fracture in brittle solids using dynamic X-ray phase contrast imaging.Experimental Mechanics. In review.
  236. Zeng, Q., Daphalapurkar, N.P., Motamedi, M.H., Leong, A.F.T., Hufnagel, T.C., Ramesh, K.T. Comparison study of crack propagation in brittle materials under impact loading with EFEM and XFEM.International Journal of Fracture. In review.
  237. Cereceda, D., Daphalapurkar, N.P., Graham-Brady, L. One-dimensional models for dynamic fragmentation of brittle materials. Book Chapter inDynamic Damage and Fragmentation Edited by Oana Cazacu. Wiley publishing. In press.
  238. Lu, Y.-C., Daphalapurkar, N.P., Knutsen, A.K., Glaister, J., Ramesh, K.T., Pham, D., Butman, J.A., Prince, J.L., Bayly, P. A 3D computational head model and the importance of the falx and tentorium in mild TBI.Annals of Biomedical Engineering. In review
  239. Ganpule, S., Daphalapurkar, N.P., Ramesh, K.T. Effect of bulk modulus on computational predictions of mTBI.Shock Waves Journal 28(1), 127-139 (2018).
  240. Cereceda, D.S., Kats, D.,Daphalapurkar, N.P., Graham-Brady, L. A micro-mechanical modeling approach for dynamic fragmentation in multi-phase materials. International Journal of Solids and Structures 134, 116-129 (2018).
  241. Ganpule, S.,Daphalapurkar, N.P., Ramesh, K.T., Knutsen, A., Pham, D., Bayly, P., Prince, J. A 3D computational human head model that captures live human brain dynamics. Journal of Neurotrauma 34, 2154-2166 (2017).
  242. Cereceda, D.S., Graham-Brady, L.,Daphalapurkar, N.P. Modeling dynamic fragmentation of heterogeneous structural materials. International J of Impact Engineering 99, 85-101 (2017).
  243. Daphalapurkar, N.P., Ayyagari, R.S., Ramesh, K.T. “Modeling anisotropic damage evolution in flaw-sensitive brittle materials under compressive loading,” International Conference and Expo on Advanced Ceramics and Composites, Tampa FL (2017).
  244. Daphalapurkar, N.P., Ganpule, S.G., Ramesh, K.T. “Effect of bulk modulus on computational predictions of traumatic brain injury,” Mach Conference, Annapolis, MD (2017).
  245. Daphalapurkar, N.P. “Predictive simulations for damage evolution in high-strength brittle materials under impact loading,” Annual Conference on Composites, Materials and Structures, Cape Canaveral, FL (2017)
  246. 2018         With ‘era of denial’ over, Johns Hopkins, local inventor move forward with technology to thwart brain injury. Baltimore Business Journal.
  247. 2018         Once shunned by NFL, ‘disruptive’ helmet inventor believes his time has come. The Baltimore Sun.
  248. Yan, C. & Stanley, S., “Sensitivity of the Geomagnetic Octupole to a Stably Stratified Layer in the Earth’s Core”, American Geophysical Union Fall Meeting,
  249. Yan, C. & Stanley, S., “Sensitivity of the Geomagnetic Octupole to a Stably Stratified Layer in the Earth’s Core”, American Geophysical Union Fall Meeting,
  250. Yan, C. & Stanley, S., “Sensitivity of the Geomagnetic Octupole to a Stably Stratified Layer in the Earth’s Core”, Gordon Research Conference on the Interior of the Earth,
  251. Yan, C. & Stanley, S., “Sensitivity of the Geomagnetic Octupole to a Stably Stratified Layer in the Earth’s Core”, Study of the Earth’s Deep Interior Conference,
  252. Li, D,., Lu, Z., & Park, S. (2018). Neural substrate of visual navigation cue integration. Poster to be presented at the Annual Meeting of the Society for Neuroscience, San Diego CA.
  253. Baumann, A. E.; Aversa, G. E., Roy, A., Falk, M. L., Bedford, N. M., Thoi, V. S. “Promoting Sulfur Adsorption with Surface Cu Sites in Metal-Organic Frameworks for Lithium Sulfur Batteries” J. Mater. Chem. A, 2018, 6, 4811-4821 Baumann, A. E.; Burns, D. A., Diaz, J. C., Thoi, V. S. “Lithiated Defect Sites in Zr Metal-Organic Framework for Enhanced Sulfur Utilization in Li-S Batteries” Chem. Mater, 2018, in revision.
  254. Baumann, A. E., Aversa, G. E., Thoi, V. S.  “Incorporation of Lithium Thiophosphates within Metal-Organic Frameworks for Improved Lithium-Sulfur Batteries” Inorganic Chemistry – Gordon Research Seminar, Biddeford, ME, June 16-17th 2018
  255. Baumann, A. E., Aversa, G. E., Thoi, V. S. “Understanding Physical and Chemical Factors Determining Li-S Battery Performance using MOFs” American Chemical Society 254th National Meeting, Washington D.C., August 23rd, 2017
  256. Thoi, V.S., Baumann, A. E., Burns, D. A., Diaz, J. C. “Using Molecular Frameworks to Model Sulfur Redox Cycling,” Inorganic Chemistry Gordon Research Conference, University of New England, Biddeford, ME, June 21, 2018.
  257. Thoi, V. S., Baumann, A. E.; Burns, D. A. “Engineering Molecular Materials for Energy Storage,” ACS Spring National Meeting, San Francisco, CA, April 2, 2017.
  258. Taekjip Ha and Ana Damjanovic. “Understanding sequence dependent DNA flexibility using looping experiment and Molecular Dynamics simulations”. Poster at the Annual Biophysics Society Meeting in San Francisco on 2018. The tittle of the Poster
  259. Jia, Z. Zhao, L. Cao, J. Li, S. Ghoshal, V. Davies, E. Stavitski, K. Attenkofer, Z. Liu, M. Li, X. Duan, S. Mukerjee, T. Mueller, and Y. Huang “Roles of Mo Surface Dopants in Enhancing the ORR Performance of Octahedral PtNi Nanoparticles” Nano Letters18, 798-804 (2018). (Co-corresponding author)
  260. Raciti, L. Cao, C. Li, K. J. T. Livi, P. F. Rottman, K. J. Hemker, T. Mueller, and C. Wang “Mechanistic Insights for Low-Overpotential Electroreduction of COto CO on Copper Nanowires” ACS Catalysis7, 8578 (2017). (Co-corresponding author)
  261. Yuan and T. Mueller“Identifying descriptors of dielectric breakdown strength from high-throughput data via genetic programming” Scientific Reports 7, 17594 (2017).
  262. Park and T. A. Zaki (2018) Sensitivity of high-speed boundary-layer stability to base-flow distortion, Journal of Fluid Mechanics — submitted.
  263. Hameduddin, D. Gayme and T. A. Zaki (2018) Perturbative expansions of the conformation tensor in viscoelastic flows. Journal of Fluid Mechanics — submitted.
  264. Marxen and T. A. Zaki (2018) Turbulence in intermittent transitional boundary layer and in turbulence spots, Journal of Fluid Mechanics — submitted.
  265. Lee and T. A. Zaki (2018) Detection algorithm for large-scale structures in turbulent/non-turbulent intermittent flow. Computers & Fluids — submitted.
  266. Wu, J. Lee, C. Meneveau and T. A. Zaki (2018) Application of a self-organizing map to identify the turbulent-boundary-layer interface in a transitional flow. Phys. Rev. Fluids — submitted.
  267. You and T. A. Zaki (2018) Conditional statistics and flow structures in turbulent boundary layers buffeted by free-stream disturbances.  Journal of Fluid Mechanics — submitted.
  268. Workshop: Control of Turbulent Friction Drag, Beihang University, Beijing, China, 2018 “Dynamical and structural modifications of boundary layers by free-stream turbulence”
  269. Workshop: Elastic Turbulence, Princeton University, Princeton Center for Theoretical Physics, 2018 “Nonlocal vorticity amplification in viscoelastic Couette flow over wavy surfaces”
  270. Mini-symposium on Complex Flows: Dynamics of Viscoelastic and Inertioelastic flows, Okinawa Institute of Science and Technology (OIST), Okinawa, Japan 2018 “Natural transition and turbulence in viscoelastic channel flow”
  271. Lessen HJ,Fleming PJ, Fleming KG and AJ Sodt (2018) “Building Blocks of the Outer Membrane: Calculating a General Elastic Energy Model for β-Barrel Membrane Proteins” J Chem Theory Comput. 2018 Jul 19. doi: 10.1021/acs.jctc.8b00377 https://www.ncbi.nlm.nih.gov/pubmed/29979594
  272. Marx DC and KGFleming (2017) “Influence of Protein Scaffold on Side-Chain Transfer Free Energies” Aug 8;113(3):597-604. doi: 10.1016/j.bpj.2017.06.032. https://www.ncbi.nlm.nih.gov/pubmed/28793214
  273. “Effects of a non-adiabatic wall on shock/boundary-layer interactions”; Volpiani, Larsson and Bernardini; accepted in Physical Review Fluids.
  274. – “Anisotropic grid-adaptation in large eddy simulations of wall-bounded and free shear flows”; Toosi and Larsson; Computers and Fluids 2017.
  275. – “Grid-adaptation and convergence-verification in large eddy simulation: a robust and systematic approach”; Toosi and Larsson; AIAA 2018
  276. Srivastava, J.A. El-Awady, “Dislocation orientation effects on the on the anisotropy of Pyramidal Slip in Magnesium”, Submitted, Physical Review Letters, 2018
  277. Hamza, T.M. Hatem, J.A. El-Awady, “Atomistic simulations of hydrogen diffusion and segregation in -iron 3 (111) grain boundaries”, Submitted, MRS Communications, 2018.
  278. Srivastava, J.A. El-Awady, “The dominating role of Jogs in Controlling Plasticity in Magnesium”, Submitted, Acta Materialia, 2018.
  279. Fan, A. Ngan, K. Gan, J.A. El-Awady, “Origin of double-peak precipitation hardening in metallic alloys”, Submitted, Journal of the Mechanics and Physics of Solids, 2017.
  280. Zhang, Y. Zhang, J.A. El-Awady, Y. Tang, “The plausibility of <c + a> dislocation slip on {-12-11} planes in Mg”, Scripta Materialia, 156:19-22, 2018
  281. Gu, Yang Xiang, David J. Srolovitz, J.A. El-Awady, “Self-healing of low angle grain boundaries by vacancy diffusion and dislocation climb”, Scripta Materialia, 155:155-159, 2018.
  282. Hendy, T. Hatem, J.A. El-Awady, “Atomistic Simulations of Carbon and Hydrogen Diffusion and Segregation in Alfa-Iron Deviant CSL Grain Boundaries, MRS Advances, 1-6. doi:10.1557/adv.2018.452, (2018).
  283. Fan, Y. Zhu, J.A. El-Awady, D. Raabe, “Precipitation hardening effects on extension twinning deformation in magnesium”, International Journal of Plasticity, 106:186-202, 2018.
  284. Gu, J.A. El-Awady, “Quantifying the effect of hydrogen on dislocation dynamics: A three-dimensional discrete dislocation dynamics framework”, Journal of the Mechanics and Physics of Solids, 112:491-507, 2018.
  285. -D. Sim, G. Kim, S. Lavenstein, M.H. Hamza, H. Fan, J.A. El-Awady, “Anomalous Hardening in Magnesium Driven by a Size-Dependent Transition in Deformation Modes”, Acta Materialia, 144:11-20, 2018.
  286. Jiao, G.-D. Sim, H. Fan, J.A. El-Awady, “Micro-Mechanical Characterization of Micro-Architectured Tungsten Coating”, Materials Science and Engineering: A, 705:366-375, 2017.
  287. Aramoon, T.D. Breitzman, C. Woodward, J.A. El-Awady, “Correlating Free-Volume Hole Distribution to the Glass Transition Temperature of Epoxy Polymers”, The Journal of Physical Chemistry B 121(35):8399-8407, 2017.
  288. Srivastava, J.A. El-Awady, “Deformation in magnesium during c-axis compression at low temperatures”, Acta Materialia, 133:282-292, 2017.
  289. Fan, J. Tang, X. Tian, Y. Zhu, X. Tian, J.A. El-Awady, “Core Structures and Mobility of <c> Dislocations in Magnesium”, Scripta Materialia, 135:37-40, 2017.
  290. M. Hussein, S.I. Rao, M.D. Uchic, T.A. Parthasarathay, J.A. El-Awady, “The Strength and Dislocation Microstructure Evolution in Superalloy Microcrystals”, Journal of the Mechanics and Physics of Solids, 99:146–162, 2017.
  291. Fan, Q. Wang, X. Tian, J.A. El-Awady, Temperature effects on the mobility of pyramidal <c+a> dislocations in magnesium, Scripta Materialia, 127:68-71, 2017.
  292. Hindy, T.M. Hatem, J.A. El-Awady, “Atomistic Simulations of Carbon Diffusion and Segregation in α-Iron Grain Boundaries”, Proceedings of the 147th TMS Annual Meeting and Exhibition, 2018.
  293. A. El-Awady, 18th International Conference on the Strength of Materials (ICSMA 18), Columbus, OH, “The Evolution of Persistent Slip Bands and Point Defects in Metals: 3D Discrete Dislocation Dynamics Simulations, July 16th, 2018.
  294. A. El-Awady, University of California Riverside, Materials Science & Engineering Graduate Program Seminar Series, Riverside, CA, “Quantifying damage evolution and crack initiation in metals from high-frequency in situ experiments and dislocation dynamics simulations”, May 9th, 2018.
  295. A. El-Awady, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Department of Materials Science and Engineering, “High Frequency In Situ Experiments of Fatigue Damage Evolution and Crack Initiation in Ni and Ni-base Superalloys”, Feb. 23rd, 2018.
  296. A. El-Awady, Schöntal Symposium on Dislocation based Plasticity, Schöntal, Germany, “Damage evolution and crack initiation in metals during high-frequency cyclic loading, Feb. 28th, 2018.
  297. A. El-Awady, University of California Los Angeles, Department of Mechanical and Aerospace Engineering Seminar Series, Boston, MA, “Damage Evolution and Crack Initiation in Metals during High-Frequency Cyclic Loading”, Jan. 8th, 2018.
  298. A. El-Awady, Materials Research Society Fall Meeting & Exhibit, Boston, MA, “High Frequency In Situ Experiments of Fatigue Damage Evolution and Crack Initiation in Metals”, Nov. 29th, 2017.
  299. A. El-Awady, University of California Santa Barbara, Department of Mechanical Engineering Seminar Series, Santa Barbara, CA, “Anomalous Hardening in Magnesium Driven by a Size-Dependent Transition in Deformation Modes”, November 20th, 2017.
  300. A. El-Awady, University of California Irvine, Department of Mechanical and Aerospace Engineering Seminar Series, Irvine, CA, “The Effect of Temperature and Crystal Size on the Activation of Different Deformation Modes in Magnesium”, November 17th, 2017.
  301. A. El-Awady, University of California Santa Barbara, Materials Department Colloquium Series, Santa Barbara, CA, “The Evolution of Persistent Slip Bands in Metals: Coarse-Grained Simulations and In Situ Experiments”, October 20th, 2017
  302. A. El-Awady, Materials Science & Technology (MS&T), Pittsburgh, PA, “The Role of Pipe Diffusion in the Stability of Low Angle Grain Boundaries, October 11th, 2017.
  303. A. El-Awady, Gordon Research Conference, Physical Metallurgy, University of New England, Biddeford, ME, “Quantifying Fatigue Damage and Crack Initiation in Metals: Coarse-Grained Simulations and In Situ Experiments”, July 24th, 2017.
  304. A. El-Awady, Wright-Patterson Air Force Research Laboratory, Dayton, OH, “A Hierarchical Multiscale Simulations Approach for Modeling Failure in Polymer Matrix Composites”, July 19th, 2017.
  305. A. El-Awady, Beijing Jiaotong University, Institute of Engineering Mechanics, Beijing, China, “Evolution of Fatigue Microstructure and Crack Initiation in Ni and Ni-base Superalloy Microcrystals”, July 14th, 2017.
  306. A. El-Awady, Xi’an Jiaotong University, School of Aerospace Engineering, Xi’an, China, “Evolution of Fatigue Microstructure and Crack Initiation in Ni and Ni-base Superalloy Microcrystals”, July 12th, 2017.
  307. A. El-Awady, Sichuan University, Department of Mechanics, Chengdu, China, “High frequency in situ fatigue response of Ni-base superalloy Ren e-N5 microcrystals”, July 7th, 2017.
  308. Gu, J.A. El-Awady, “The Effect of Hydrogen on the Deformation of Face-Centered Cubic Microcrystals: Three-Dimensional Discrete Dislocation Dynamics Simulations”, 18th International Conference on the Strength of Materials (ICSMA 18), July 17th, 2018.
  309. Jiao, G.-D. Sim, J.A. El-Awady, “Micro-Mechanical Characterization of Micro-Architectured Tungsten Coating at Elevated Temperatures”, TMS Annual Meeting, San Diego, CA, February 28th, 2017.
  310. I. Rao, C. Woodward, B. Akdim, E. Antillon, T. Parthasarathy, J.A. El-Awady, D.M. Dimiduk, “Large Scale Dislocation Dynamics simulations of strain hardening of Ni microcrystals under tensile loading”, TMS Annual Meeting, Phoenix, AZ, March 11-15th, 2018.
  311. M. Hatem, M. Hindy, J.A. El-Awady, “Atomistic Simulations of Carbon Diffusion and Segregation in α-Iron Grain Boundaries”, TMS Annual Meeting, Phoenix, AZ, March 11-15th, 2018.
  312. Gu, J.A. El-Awady, “Incorporating Hydrogen-Diffusion and Dislocation-Hydrogen Interactions into Large Scale Discrete Dislocation Dynamics Simulations of Metals”, Materials Research Society Fall Meeting & Exhibit, Boston, MA, November 30, 2017.
  313. Gu, J.A. El-Awady, “The Effect of Hydrogen on Plastic Deformation as Predicted from Discrete Dislocation Dynamic Simulations”, Materials Science & Technology (MS&T), Pittsburgh, PA, October 11th, 2017.
  314. Annual Biophysics Society Meeting, San Francisco, 2018 “Slide-seq: Probing  Sequence-Dependence  of  Chromatin  Remodeling
    Activities in High Throughput”. Sangwoo Park, Jessica Winger, Gregory Bowman, Taekjip Ha. Johns Hopkins Univ, Baltimore, MD, USA.
  315. Goldberg D. et al “Observation of Radical Rebound in a Mononuclear Nonheme Iron Model Complex” (J. Am. Chem. Soc., 2018, 140, 4191–4194)
  316. Goldberg D. et al “A Reactive Manganese(IV)–Hydroxide Complex: A Missing Intermediate in Hydrogen Atom Transfer by High-Valent Metal-Oxo Porphyrinoid Compounds” (J. Am. Chem. Soc., 2018, 140, 4380–4390)
  317. C. O’Connor, N. J. Alvarez and M. O. Robbins, “Relating Chain Conformations to Extensional Stress in Entangled Polymer Melts,” Phys. Rev. Lett. 121, 047801 (2018). (doi:10.1103/PhysRevLett.121.047801)C. O’Connor, R. M. Elder, Y. R. Sliozberg, T. W. Sirk, J. W. Andzelm and M. O. Robbins, “Molecular Origins of Anisotropic Shock Propagation in Crystalline and Amorphous Polyethylene,’’ Phys. Rev. Materials 2, 035601 (2018). (doi:10.1103/PhysRevMaterials.2.035601)
  318. Dong, Z. Wang, T. C. O’Connor, A. Azoug, M. O. Robbins, and T. D. Nguyen, “Micromechanical models for the stiffness and strength of UHMWPE macrofibrils,” J. Mech. Phys. Solids 116, 70-98 (2018). (doi:10.1016.j.jmps.2018.03.015)
  319. A. Sharp, L. Pastewka, V. Lignères and M. O. Robbins, “Scale and load dependent friction in commensurate sphere-on-flat contacts,” Phys. Rev. B 96, 155436 (2017). (doi:10.1103/PhysRevB.96.155436)
  320. Jadhao and M. O. Robbins, “Reply to Bair: Crossover to Arrhenius behavior at high viscosities in squalane,” PNAS 114, E8807-E8808 (2017). doi:10.1073/pnas.1715298114.
  321. M. Elder, T. C. O’Connor, T. L. Chantawansri, Y. R. Sliozberg, T. W. Sirk, I.-C. Yeh, M. O. Robbins, and J. W. Andzelm, “Shock wave propagation and reflection in semi-crystalline polyethylene: An atomic-scale investigation,” Phys. Rev. Materials 1, 043606 (2017). (Editor’s Suggestion) (doi:10.1103/PhysRevMaterials.1.043606)
  322. H. Muser, W. B. Dapp, R. Bugnicourt, P. Sainsot, N. Lesaffre, T. A. Lubrecht, B. N. N. Persson, K. Harris, A. Bennett, K. Schulze, S. Rohde, P. Ifju, W. G. Sawyer, T. Angelini, H. A. Esfahani, M. Kadkhodaei, S. Akbarzadeh, J.-J. Wu, G. Vorlaufer, A. Vernes, S. Solhjoo, A. I. Vakis, R. L. Jackson, Y. Xu, J. Streator, A. Rostami, D. Dini, S. Medina, G. Carbone, F. Bottiglione, L. Afferrante, J. Monti, L. Pastewka, M. O. Robbins, J. A. Greenwood, “Meeting the contact-mechanics challenge,” Tribology Letters 65, 118 (2017). (doi:10.1007/s11249-017-0900-2)
  323. Jadhao and M. O. Robbins, “Probing large viscosities in glass-formers with nonequilibrium simulations,” PNAS 114, 7952-7957 (2017). Correction. PNAS 114, E8317 (2017) (doi:10.1073/pnas.1705978114,doi:10.1073/pnas.1715376114)
  324. Ge, C. Tzoumanekas, S. D. Anogiannakis, R. S. Hoy and M. O. Robbins, “Entanglements in Glassy Polymer Crazing: Cross-Links or Tubes?” Macromolecules 50, 459-471 (2017) (doi:10.1021/acs.macromol.6b02125
  325. “Scale Dependence of Friction: Contact of Nanometer to Millimeter Radius Tips,” American Chemical Society National Meeting, San Francisco, April 2-6, 2017.
  326. “Scale Dependence of Contact and Friction from Atomic to Macroscopic scales,” Joint ICTP-COST-MODPHYSFRICT Conference on ‘Trends in Nanotribology 2017’, Trieste, Italy, June 26-30, 2017
  327. “Competition Between Chain Scission and Slippage in Failure of Polymer Fibers and Glasses,” 254 American Chemical Society National Meeting, Washington, DC, Aug 20-24, 2017.
  328. “Scale Dependence of Friction and Contact from Nanometer to Millimeter Scales,” Keynote Talk, 6th World Tribology Congress, Beijing, China, Sept. 17-22, 2017
  329. “Activated Molecular Motion and Macroscopic Mechanical Response: From Failure of Polyethylene Fibers to Elastohydrodynamic Lubrication,” ExxonMobil Research and Engineering, Annandale, NJ. Jan 10, 2017.
  330. “Contact and Friction from Atomic to Macroscopic Scales,” Applied Mechanics Colloquium, Harvard University. March 29, 2017.
  331. “A Rough View of Friction and Adhesion,” Physics Colloquium, Florida State University. Nov. 2, 2017.“A Rough View of Friction and Adhesion,” Physics Colloquium, Calgary University. Dec. 1, 2017.
  332. “Contact of Rough Solids,” KITP Program: Physics of Dense Suspensions, Univ. of California, Santa Barbara Jan. 19, 2018.“Elastohydrodynamic Lubrication and the Glass Transition: Linking Experiment and Simulation at High Rates and Pressures,” NanoGoa: Nanoscale Effects in Macrotribology, Gao, India, Jan. 8-12, 2018.
  333. “Bridging from Atomic Forces to Macroscopic Friction,” Non-linear Mechanics and Rheology of Dense Suspensions: Nanoscale Structure to Macroscopic Behavior, KITP, Santa Barbara, CA. Jan. 22-26, 2018.
  334. “Scale Dependence of Friction: How Elasticity Destroys Superlubricity,” March Meeting of the American Physical Society, Los Angeles, CA, March 5-9, 2018.
  335. “Effect of Chain Alignment on Thermal Welding in Fused Filament Fabrication,” 255th ACS National Meeting, New Orleans, LA, March 18-22, 2018.
  336. “Alignment and Strength in Polymer Welds and Fibers,” 17th International Conference on Deformation, Yield and Fracture of Polymers, Rulduc, Netherlands, March 25-29, 2018.
  337. “Effect of Chain Alignment on Thermal Welding in Fused Filament Fabrication,” Additive Manufacturing Benchmarks 2018, National Institute of Standards and Technology, Gaithersburg, MD June 18-21, 2018.
  338. “Scale Dependence of Friction: How Elasticity Destroys Superlubricity, 9th International Conference on Multiscale Materials Modeling, Osaka, Japan, Oct. 28-Nov. 2, 2018.“Connecting Mechanical Properties of Amorphous Polymers to Chain Alignment and Entanglements,”Materials Research Society Fall Meeting, Boston, MA, November 25-30, 2018. 
  339. The Nonlinear Mechanics and Rheology of Oriented Polymers, Thomas C. O’Connor, Aug. 2018.
  340. Pouyan Khakbaz. COMPUTATIONAL STUDIES OF LIPID BILAYERS AND TRANSMEMBRANE PROTEINS. December, 2017. Ph.D. Dissertation at UMD.

2017

  1. Stevens, R. J.A.M., Martinez-Tossas, L. A., Meneveau, C. Comparison of wind farm large eddy simulations using actuator disk and actuator line models with wind tunnel experiments. Renewable Energy. Submitted
  2. Martinez-Tossas, L. A., Churchfield, M., Meneveau, C. Optimal smoothing length scale foractuator line models of wind turbine blades. To appear in Wind Energy. Accepted.
  3. Howland, M. F., Bossuyt, J., Martinez-Tossas, L. A., Meyers, J., Meneveau, C. (2016).Wake structure in actuator disk models of wind turbines in yaw underuniform inflow conditions. Journal of Renewable and Sustainable Energy, 8(4). Published.
  4. Martinez-Tossas, L. A., Churchfield, M., Meneveau, C., A Highly Resolved Large-Eddy Simulation of a Wind Turbine using an Actuator Line Model with Optimal Body Force. Projection. Munich: The Science of Making Torque from Wind (TORQUE 2016). Submitted.
  5. Shapiro, C., Meyers, J., Meneveau, C., Gayme, D., Wind farms providing secondary frequency regulation: Evaluating the performance of model-based receding horizon control. Munich: The Science of Making Torque from Wind (TORQUE 2016). Submitted.
  6. Martinez-Tossas, L. A., Stevens, R. J.A.M., Meneveau, C. (2016)., Wind Turbine Large-Eddy Simulations on Very Coarse Grid Resolutions using an Actuator Line Model (pp. AIAA 2016-1261). San Diego, CA: 34th Wind Energy Symposium (2016), AIAA SciTech. Published
  7. Thomas, V., Meneveau, C., Gayme, D., 69th Annual Meeting of the APS Division of Fluid Dynamics, A Predictive Model for Wind Farms Using Dynamic Mode Decomposition, Abstract: G35.00002 in Session G35: Turbulence: Wakes, The American Physical Society, Portland, OR. (November 21, 2016).
  8. Bretheim, J., Meneveau, C., Gayme, D., 69th Annual Meeting of the APS Division of Fluid Dynamics, Extending the restricted nonlinear model for wall-turbulence to high Reynolds numbers, Abstract: G33.00001 in Session G33: Turbulent Boundary Layers: Walls and Modeling, The American Physical Society, Portland, OR. (November 21, 2016).
  9. Shapiro, C., Meneveau, C., Gayme, D., 69th Annual Meeting of the APS Division of Fluid Dynamics, A simple dynamic wake model for time dependent wind turbine yaw, Abstract: D2.00001 in Session D2: Wind Turbines: Simulations, The American Physical Society, Portland, OR. (November 20, 2016)
  10. Martinez-Tossas, L. A., Churchfield, M. J., Meneveau, C., 69th Annual Meeting of the APS Division of Fluid Dynamics, “An actuator line model simulation with optimal body force projection length scales, Abstract: D2.00003 at Session D2: Wind Turbines: Simulations,” The American Physical Society, Portland, OR. (November 20, 2016).
  11. Shapiro, C. (Presenter & Author), Meneveau, C. (Author Only), Gayme, D. (Author Only), 1000 Island Energy Research Forum, “Wind Farm Control for Power Grid Frequency Regulation,” Alexandria Bay, NY. (October 29, 2016).
  12. Martinez-Tossas, L. A., Churchfield, M. J., Meneveau, C., The Science of Making Torque from Wind (TORQUE 2016), “Highly Resolved Large-Eddy Simulation of a Wind Turbine using an Actuator Line Model with Optimal Body Force Projection,” accepted for presentation, Munich, Germany. (October 5, 2016)
  13. Shapiro, C., Meyers, J., Meneveau, C., Gayme, D., The Science of Making Torque from Wind TORQUE 2016), “Wind farms providing secondary frequency regulation: Evaluating the performance of model-based receding horizon control,” accepted for presentation, Munich, Germany. (October 5, 2016)
  14. Bretheim, J., Meneveau, C., Gayme, D., 24th International Congress of Theoretical and Applied Mechanics ICTAM 2016, “A Restricted Nonlinear Large-Eddy Simulation Model For Wall-Bounded Turbulence,” Contributed talk, Montreal, Canada. (August 21, 2016).
  15. Meneveau, C., WindFarms in Complex Terrain, “Modeling boundary layer flow over fractal-like, multi-scale terrain in large eddy simulations,” Plenary Speaker, Euromech Colloquium, KTH, Stockholm, Sweden. (June 8, 2016).
  16. Bretheim, J., Meneveau, C., Gayme, D., WindFarms 2016 Meeting, “A Restricted Nonlinear Large Eddy Simulation Model for Turbulent Boundary Layers and Wind Farm Applications,” The University of Texas at Dallas, Richardson, TX. (May 24, 2016).
  17. Gayme, D., Meneveau, C., WindFarms 2016 Meeting, “Reduced order modeling for wind farm design and control,” The University of Texas at Dallas, Richardson, TX. (May 24, 2016).
  18. Thomas, V., Meneveau, C., Gayme, D., WindFarms 2016 Meeting, “Reduced order models of wind farms using Dynamic Mode Decomposition,” The University of Texas at Dallas, Richardson, TX. (May 24, 2016).
  19. Shapiro, C., Meneveau, C., Gayme, D. (2016). A simple dynamic wake model for time dependent wind turbine yaw (abstract only)., Bulletin of the American Physical Society, Div. of Fluid Dynamics (20th ed., vol. 61, pp. 97). Published.
  20. C. J. Harman, A. S. Ward, and A. Ball (2016), How does reach-scale stream-hyporheic transport vary with discharge? Insights from rSAS analysis of sequential tracer injections in a headwater mountain stream, Water Resources Research, 52, 7130–7150, doi:10.1002/2016WR018832.
  21. Kim, M., L. Pangle, C. Cardoso, M. Lora, T. Volkmann, Y. Wang, C. J. Harman, and P. Troch (2016), Transit time distributions and StorAge Selection functions in a sloping soil lysimeter with time-varying flow paths: Direct observation of internal and external transport variability, Water Resources Research, 52, 7105–7129, doi:10.1002/2016WR018620.
  22. Deng D; Arevalo HJ; Prakosa A; Callans DJ; Trayanova N, A feasibility study of arrhythmia risk prediction in patients with myocardial infarction and preserved ejection fraction, Europace
  23. Karathanos TV, Boyle PM, Trayanova N. Light-based approaches to cardiac arrhythmia research: From basic science to translational applications. Clin Med Insights Cardiol. 10(Suppl 1):47-60, 2016.
  24. Chang KC, Trayanova N. Mechanisms of arrhythmogenesis related to calcium-driven alternans in a model of human atrial fibrillation. Sci Rep Nov 4;6:36395. doi: 10.1038/srep36395, 2016
  25. Priest JR, Gawad C, Kahlig KM, Yu JK, O’Hara T, Boyle PM, Rajamani S, Clark MJ, Garcia ST, Ceresnak S, Harris J, Boyle S, Dewey FE, Malloy-Walton L, Dunn K, Grove M, Perez MV, Neff NF, Chen R, Maeda K, Dubin A, Belardinelli L, West J, Antolik C, Macaya D, Quertermous T, Trayanova N, Quake SR, Ashley EA. Early somatic mosaicism is a rare cause of long-QT syndrome, Proc Natl Acad Sci U S A. 113:11555-11560, 2016 (accompanied by a press release; story picked up bya number of national and international new outlets; featured video on PNAS webpage).
  26. Bruegmann T, Boyle PM, Vogt CC, Karathanos TV, Arevalo HJ, Fleischmann BK, Trayanova N, Sasse P. Optogenetic defibrillation terminates ventricular arrhythmia in mouse hearts and human simulations, J Clin Invest. 126:3894-3904, 2016 (accompanied by a press release and a video on YouTube and Facebook from JHU; story picked up by a number of national and international new outlets, including an interview by the Economist, and TV news by a number of TV channels around the country).
  27. HJ Arevalo, F Vadakkumpadan, E Guallar, A Jebb, P Malamas, KC Wu, N Trayanova. Arrhythmia risk stratification of patients after myocardial infarction using personalized heart models. Nature Communications. May 10;7:11437. doi: 10.1038/ncomms11437, 2016 (accompanied by a press release from JHU; story picked up by over 60 national and international new outlets, including an article in the Guardian and an interview on BBC. Chosen as Nature’s featured article, and accompanied by a review in Nature Reviews Cardiology)
  28. Zahid S, Whyte KN, Schwarz EL, Blake RC 3rd, Boyle PM, Chrispin J, Prakosa A, Ipek EG, Pashakhanloo F, Halperin HR, Calkins H, Berger RD, Nazarian S, Trayanova N. Feasibility of using patient-specific models and the “minimum cut” algorithm to predict optimal ablation targets for left atrial flutter. Heart Rhythm. 13:1687-1698, 2016
  29. Trayanova N, Chang KC. How computer simulations of the human heart can improve anti-arrhythmia therapy. J Physiol. 594:2483-2502, 2016.
  30. Zahid S, Cochet H, Boyle PM, Schwarz EL, Whyte KN, Vigmond EJ, Dubois R, Hocini M, Haïssaguerre M, Jaïs P,  Trayanova N. Patient-derived models link re-entrant driver localization in atrial fibrillation to fibrosis spatial pattern, Cardiovasc Res. 110(3):443-454, 2016
  31. Karathanos TV, PM Boyle, JD Bayer, D Wang, N Trayanova, Opsin Spectral Sensitivity Determines the Effectiveness of Optogenetic Termination of Ventricular Fibrillation in the Human Heart: A Simulation Study, J Physiol 2016 Mar 4. doi: 10.1113/JP271739. [Epub ahead of print]
  32. Ukwatta E, Arevalo H, Li K, Yuan J, Qiu W, Malamas P, Wu KC, Trayanova N, Vadakkumpadan F. Myocardial Infarct Segmentation from Magnetic Resonance Images for Personalized Modeling of Cardiac Electrophysiology, IEEE Trans
  33. Stevens, R. J. A. M., Gayme, D. F., Meneveau, C. (2016). Generalized Coupled Wake Boundary Layer Model: Applications and Comparisons with Field and LES Datafor Two Real Wind-Farms. Wind Energy, 19(11). Published
  34. Stevens, R. J. A. M., Gayme, D., Meneveau, C. (2016). Effects of turbine spacing on the power output of extended wind-farms. Wind Energy, 19(2), 359-370. Published.
  35. Shapiro, C., Meyers, J., Meneveau, C., Gayme, D., Model-Based Receding Horizon Control of Wind Farms for Secondary Frequency Regulation. Proc. of the American Control Conference.
  36. Gayme, D. (2016)., Wind farms providing secondary frequency regulation: Evaluating the performance of model-based receding horizon control (5th ed., vol. 753, pp. 052012).
    Journal of Physics: Conference Series. Published.
  37. Gayme, D. (Guest Speaker), Offshore Wind IGERT Seminar Series, “New directions in wind farm modeling and control,” University of Massachusetts Amherst. (December 1, 2016). Invited.
  38. Gayme, D., 10th Annual Trans-Atlantic Infraday Conference, “Finding new markets for wind energy: Exploiting wind farm flow physics to enable more cost effective secondary frequency regulation with wind,” Federal Energy Regulatory Commission, Washington, DC. (November 10, 2016). Invited.
  39. Gayme, D. (Guest Speaker), Mechanical and Aerospace Engineering Colloquium, “The restricted nonlinear model: a minimal model for self-sustaining turbulence in wall bounded shear flows,” Cornell University, New York. (September 27, 2016). Invited.
  40. Gayme, D. (Guest Speaker), Department of Aerospace and Mechanical Engineering Seminar Series, “The Restricted Nonlinear System: A Minimal Model for Self-Sustaining Turbulence in Wall Bounded Shear Flows,” University of Notre Dame. (September 13, 2016). Invited.
  41. Gayme, D. (Presenter & Author), Thomas, V. (Author Only), Mini- Symposium on Bypass Transition, “Restricted Nonlinear Roll/Streak Dynamics in Plane Couette Flow,” 24th International Congress of Theoretical and Applied Mechanics (ICTAM), Montreal, Quebec. (August 22, 2016). Invited.
  42. Gayme, D. (Presenter & Author), Shapiro, C. (Author Only), Meyers, J. (Author Only), (Author Only), Symposium on Experiments and Simulations in Fluid Dynamics Research, “Model-based wind farm control for power grid frequency regulation,” Queens University, Kingston, ON, Candada. (August 19, 2016). Invited.
  43. Gayme, D. (Presenter Only), FREEDM Systems Center Special Seminar, “Management of energy resources for flexible and efficient power systems,” Electrical and Computer Engineering, North Carolina State University. (February 19, 2016). Invited.
  44. Thomas, V., Meneveau, C., Gayme, D., 69th Annual Meeting of the APS Division of Fluid Dynamics, “A Predictive Model for Wind Farms Using Dynamic Mode Decomposition, Abstract: G35.00002 in Session G35: Turbulence: Wakes,” The American Physical Society, Portland, OR. (November 21, 2016).
  45. Bretheim, J., Meneveau, C., Gayme, D., 69th Annual Meeting of the APS Division of Fluid Dynamics, “Extending the restricted nonlinear model for wall-turbulence to high Reynolds numbers, Abstract: G33.00001 in Session G33: Turbulent Boundary Layers: Walls and Modeling,” The American Physical Society, Portland, OR. (November 21, 2016).
  46. Shapiro, C., Meneveau, C., Gayme, D., 69th Annual Meeting of the APS Division of Fluid Dynamics, “A simple dynamic wake model for time dependent wind turbine yaw, Abstract: D2.00001 in Session D2: Wind Turbines: Simulations,” The American Physical Society, Portland, OR. (November 20, 2016).
  47. Shapiro, C. (Presenter & Author), Meneveau, C. (Author Only), Gayme, D. (Author Only), 1000 Island Energy Research Forum, “Wind Farm Control for Power Grid Frequency Regulation,” Alexandria Bay, NY. (October 29, 2016).
  48. Shapiro, C., Meyers, J., Meneveau, C., Gayme, D., The Science of Making Torque from Wind (TORQUE 2016), “Wind farms providing secondary frequency regulation: Evaluating the performance of model-based receding horizon control,” accepted for presentation, Munich, Germany. (October 5, 2016).
  49. Bretheim, J., Meneveau, C., Gayme, D., 24th International Congress of Theoretical and Applied Mechanics ICTAM 2016, “A Restricted Nonlinear Large-Eddy Simulation Model For Wall-Bounded Turbulence,” Contributed talk, Montreal, Canada. (August 21, 2016).
  50. Stevens, R. J.A.M., Martinez-Tossas, L. A., Gayme, D., Meneveau, C., 24th International Congress of Theoretical and Applied Mechanics ICTAM 2016, “Simulation and modeling of extended wind farms,” Contributed talk,, Montreal, Canada. (August 21, 2016).
  51. Stevens, R. J. A. M. (Presenter & Author), Gayme, D. (Author Only), Meyers, J. (Author Only), Meneveau, C., EUROMECH Colloquium 576, Wind Farms in Complex Terrains, “LES Studies of Wind Farms Including Wide Turbine Spacings and Comparisons with the CWBL Engineering Model,” EUROMECH, KTH Royal Institute of Technology, Stockholm. (June 2016).
  52. Gayme, D. (Presenter & Author), Shapiro, C. (Author Only), Meyers, J. (Author Only), Meneveau, C. (Author Only), EUROMECH Colloquium 576, Wind Farms in Complex Terrains, “Using LES to Develop and Validate Model-Based Wind Farm Control,” EUROMECH, KTH Royal Institute of Technology, Stockholm. (June 2016).
  53. Bretheim, J., Meneveau, C., Gayme, D., WindFarms 2016 Meeting, “A Restricted Nonlinear Large Eddy Simulation Model for Turbulent Boundary Layers and Wind Farm Applications,” The University of Texas at Dallas, Richardson, TX. (May 24, 2016).
  54. Gayme, D., Meneveau, C., WindFarms 2016 Meeting, “Reduced order modeling for wind farm design and control,” The University of Texas at Dallas, Richardson, TX. (May 24, 2016).
  55. Thomas, V., Meneveau, C., Gayme, D., WindFarms 2016 Meeting, “Reduced order models of wind farms using Dynamic Mode Decomposition,” The University of Texas at Dallas, Richardson, TX. (May 24, 2016).
  56. Shapiro, C., Bauweraerts, P., Meyers, J., Meneveau, C., Gayme, D., WindFarms 2016 Meeting, “Model-based receding horizon control of wind farms for secondary frequency regulation,” The University of Texas at Dallas, Richardson, TX. (May 23, 2016).
  57. Mo A, Luo C, Davis FP, Mukamel EA, Henry GL, Nery JR, Urich MA, Picard S, Lister R, Eddy SR, Beer MA, Ecker JR, and Nathans J, Epigenomic landscapes of retinal rods and cones. eLife 5, e11613 (2016).
  58. Ghandi M, Mohammad-Noori M, Ghareghani N, Lee D, Garraway L, and Beer MA, gkmSVM, an R package for gapped-kmer SVM. Bioinformatics 10.1093/bioinformatics/btw203 (2016).
  59. Migeon BR, Beer MA, and Bjornsson HT, Embryonic loss of human females with partial trisomy 19 identifies region critical for the single active X. Plos ONE 12 (4), e0170403 (2017).
  60. Kreimer A, Zeng H, Edwards M, Guo Y, Tian K, Shin S, Welch R, Wainberg M, Mohan R, Sinnott-Armstrong N, Li Y, Amin T, Goke J, Mueller N, Kellis, M, Kundaje A, Beer MA, Keles S, Gifford D, and Yosef N, Predicting Gene Expression in Massively Parallel Reporter Assays: A Comparative Study. Human Mutation (2017).
  61. Cheng CS, Gate RE, Siba A, Tabaka M, Lituiev D, Subramaniam M, Hougen KL, Shamim M, Wortman I, Aiden AP, Machol I, Feng T, De Jager PL, Chang H, Lieberman Aiden E, Benoist C, Beer MA, Ye CJ, Regev A, Genetic determinants of chromatin accessibility and gene regulation in T cell activation across human individuals, Nature Genetics under review, bioRxiv, 090241 (2017).
  62. Beer MA, Predicting Enhancer Activity and Variant Impact using gkm-SVM. Human Mutation (2017).
  63. Xie F and Xu Y#, NDPP-Mix: Nested Dirichlet Process-Determinantal Point Process Mixture Model. Submitted
  64. Li Y, Dinalankara W, Marchionni L, Kochel C, Nirschl T, Drake C, and Xu Y#, BayRepulsive: A Bayesian Repulsive Deconvolution Model for Inferring Tumor Heterogeneity. Submitted
  65. Xie F and Xu Y#, Bayesian Repulsive Gaussian Mixture Model. Submitted
  66. Xie F, Zhou M, and Xu Y#, BayCount: A Bayesian Decomposition Method for Inferring Tumor Heterogeneity using RNA-Seq Counts. Submitted
  67. Xu Y, Xu Y, and Saria S, Bayesian Estimation of Individualized Treatment-Response Curves in Populations with Heterogeneous Treatment Effects. Journal ofMachine Learning Research. In Press.
  68. Xu Y, Xu Y, and Saria S, A Non-parametric Bayesian Approach for Estimating Treatment-Response Curves from Sparse Time Series. Proceedings of the 1st Machine Learning for Healthcare Conference. 2016, 282-300.
  69. DiPietro, Robert, et al. “Recognizing surgical activities with recurrent neural networks.” International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer International Publishing, 2016.
  70. DiPietro, Robert, Christian Rupprecht, Nassir Navab, and Gregory D. Hager. “Analyzing and Exploiting NARX Recurrent Neural Networks for Long-Term Dependencies.” arXiv preprint arXiv:1702.07805 (2017).
  71. Chi Li, Han Xiao, Keisuke Tateno, Federico Tombari, Nassir Navab, and Gregory D Hager. Incremental scene understanding on dense slam. In International Conference on Intelligent Robots and Systems (IROS), 2016
  72. Chi Li, Jonathan Boheren, Eric Carlson, and Gregory D Hager. Hierarchical semantic parsing for object pose estimation in densely cluttered scenes. In International Conference on Robotics Automation (ICRA), 2016
  73. Chi Li, Austin Reiter, and Gregory D Hager. Beyond spatial pooling: Fine-grained representation learning in multiple domains. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 4913–4922, 2015
  74. Chi Li, Jonathan Boheren, and Gregory D Hager. Bridging the robot perception gap with mid-level vision. In International Symposium on Robotics Research (ISRR), 2015
  75. Chi Li, Le Lu, Gregory D Hager, Jianyu Tang, and Hanzi Wang. Robust object tracking in crowd dynamic scenes using explicit stereo depth. In Asian Conference on Computer Vision (ACCV), pages 71–85. Springer, 2012
  76. Billings S.D. et al. (2016) Anatomically Constrained Video-CT Registration via the V-IMLOP Algorithm. In: Ourselin S., Joskowicz L., Sabuncu M., Unal G., Wells W. (eds) Medical Image Computing and Computer-Assisted Intervention — MICCAI 2016. MICCAI 2016. Lecture Notes in Computer Science, vol 9902. Springer, Cham 16GT: a fast and sensitive variant caller using a 16-genotype probabilistic model
  77. Luo, R, Schatz, MC, Salzberg, SL (2017) GigaScience doi: https://doi.org/10.1093/gigascience/gix045
  78. Cerizza, D., Sekiguchi, W., Tsukahara, T., Zaki, T., Hasegawa, Y. (2016). Reconstruction of scalar source intensity based on sensor signal in turbulent
    channel flow. Flow, Turbulence & Combustion!!!, 97(4), 1211–1233. Published.
  79. Lee, J., Zaki, T. Video: A computational laboratory for the study of transitional and turbulent boundary layers., 68th Annual Meeting of the APS Division of Fluid Dynamics – Gallery of Fluid Motion. American Physical Society (APS). Published
  80. Zaki, T., Big Data Joint Workshop, “A Big-Data Computational Laboratory for the Optimization of Olfactory Search Algorithms in Turbulent Environments, Japan Science and Technology Agency and National Science Foundation, Tokyo, Japan. (2016). Invited.
  81. Zaki, T., CSME International Congress, “High-fidelity simulations and predictive theory of boundary-layer transition, The Canadian Society for Mechanical Engineers (CSME), Kelowna, Canada. (June 2016). Invited.
  82. Zaki, T., “Boundary layer transition beneath free-stream turbulence: Linear precursors of nonlinear breakdown, Fluid Mechanics Unit, Okinawa Institute of Technology, Japan. (May 2016). Invited.
  83. Zaki, T., “Primary and secondary instabilities of transitional boundary layers beneath free-stream turbulence, Department of Electrical and Mechanical Engineering, Nagoya Institute of Technology, Japan. (May 2016). Invited.
  84. Zaki, T., “Linear analysis and nonlinear simulations of boundary-layer transition,” Department of Mechanical Engineering, University of Texas at Dallas. (March 2016). Invited.
  85. Wang, Q., Hasegawa, Y., Meneveau, C., Zaki, T., 69th Annual Meeting of the APS Division of Fluid Dynamics, Adjoint-optimization algorithm for spatial reconstruction of a scalar source, Abstract: L7.00008 in Session L7: Flow Control: Feedback, System and Model Identification,”” The American “Physical Society, Portland, OR. (November 21, 2016).”
  86. Lee, J., Zaki, T., 24th ICTAM Conference, “Turbulent/non-turbulent interface in transitional and turbulent boundary layers, The International Congress of Theoretical and Applied Mechanics, Montreal, Canada. (August 2016).
  87. Nicolaou, L., Materials for Extreme Dynamic Environments – Army Cooperative Research Agreement, Microme- chanical Model of the Rate-dependent and Temperature-dependent of Highly Oriented Polyethy- lene Fibers, 1/1/2014 – 12/1/2017, $283,504, PI: T. D. Nguyen.
  88. Cereceda, D., Graham-Brady, L. & Daphalapurkar, N. (2017). “Modeling dynamic fragmentation of heterogeneous structural materials,” International Journal of Impact Engineering, 99:85-101.
  89. Cereceda, D., Kats, D., Daphalapurkar, N. & Graham-Brady, L. (2017). “A
    micro-mechanical modeling approach for dynamic fragmentation in brittle
    multi-phase materials,” International Journal of Solids & Structures,
    under review.
  90. Bhaduri, A. & Graham-Brady, L. (2017). “A gradient based adaptive sparse grid collocation method for uncertainty propagation,” Probabilistic Engineering Mechanics, under review.
  91. Preheim SP, Olesen SW, Spencer SJ, Materna A, Varadharajan C, Blackburn M, Friedman J, Rodriguez J, Hemond H and Alm EJ. 2016. Surveys, simulation, and single-cell assays relate function and phylogeny in a natural ecosystem. Nature Microbiology 1:16130
  92. Nellore A, Jaffe AE, Fortin JP, Alquicira-Hernández J, Collado-Torres L, Wang S, Phillips RA, Karbhari N, Hansen KD, Langmead B, Leek JT. Human splicing diversity and the extent of unannotated splice junctions across human RNA-seq samples on the Sequence Read Archive . Genome Biology. 2016, 17:266.
  93. Nellore A, Collado-Torres L, Jaffe AE, Alquicira-Hernández J, Wilks C, Pritt J, Morton J, Leek JT, Langmead B. Rail-RNA: Scalable analysis of RNA-seq splicing and coverage. Bioinformatics. 2016 Sep 4. Advance access.
  94. Nellore A, Wilks C, Hansen KD, Leek JT, Langmead B. Rail-dbGaP: analyzing dbGaP-protected data in the cloud with Amazon Elastic MapReduce. Bioinformatics. 2016 Aug 15;32(16):2551-3.
  95. Langmead B. A tandem simulation framework for predicting mapping quality. bioRxiv doi: 10.1101/103952. (In press at Genome Biology)
  96. Wilks C, Gaddipati P, Nellore A, Langmead B. Snaptron: querying and visualizing splicing across tens of thousands of RNA-seq samples. bioRxiv doi: 10.1101/097881. (In revision at Bioinformatics)
  97. D. Raciti, L. Cao, K.  J. T. Livi, P. F. Rottmann, X. Tang, C. Li, Z. Hicks, Kit H. Bowen , K.  J. Hemker, T. Mueller, and C. Wang, “Low-Overpotential Electroreduction of Carbon Monoxide Using Copper Nanowires” ACS Catalysis 2017, 4467–4472 (2017)  http://dx.doi.org/10.1021/acscatal.7b01124
  98. L. Cao and T. Mueller, “Theoretical Insights into the Effects of Oxidation and Mo-Doping on the Structure and Stability of Pt–Ni Nanoparticles” Nano Letters 16, 7748–7754 (2016).
    http://dx.doi.org/10.1021/acs.nanolett.6b03867
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  102. Y. Wang, A. J. Sierakowski, and A. Prosperetti. Fully-resolved simulation of particulate flows with particles-fluid heat transfer. J. Comp. Phys. 350 (2017) 638-656. doi.org/10/1016/j.jcp.2017.07.44

2016

  1. Stevens, R. J.A.M., Martinez-Tossas, L. A., Meneveau, C. Comparison of wind farm large eddy simulations using actuator disk and actuator line models with wind tunnel experiments. Renewable Energy. Submitted
  2. Martinez-Tossas, L. A., Churchfield, M., Meneveau, C. Optimal smoothing length scale foractuator line models of wind turbine blades. To appear in Wind Energy. Accepted.
  3. Howland, M. F., Bossuyt, J., Martinez-Tossas, L. A., Meyers, J., Meneveau, C. (2016).Wake structure in actuator disk models of wind turbines in yaw underuniform inflow conditions. Journal of Renewable and Sustainable Energy, 8(4). Published.
  4. Martinez-Tossas, L. A., Churchfield, M., Meneveau, C., A Highly Resolved Large-Eddy Simulation of a Wind Turbine using an Actuator Line Model with Optimal Body Force. Projection. Munich: The Science of Making Torque from Wind (TORQUE 2016). Submitted.
  5. Shapiro, C., Meyers, J., Meneveau, C., Gayme, D., Wind farms providing secondary frequency regulation: Evaluating the performance of model-based receding horizon control. Munich: The Science of Making Torque from Wind (TORQUE 2016). Submitted.
  6. Martinez-Tossas, L. A., Stevens, R. J.A.M., Meneveau, C. (2016)., Wind Turbine Large-Eddy Simulations on Very Coarse Grid Resolutions using an Actuator Line Model (pp. AIAA 2016-1261). San Diego, CA: 34th Wind Energy Symposium (2016), AIAA SciTech. Published
  7. Thomas, V., Meneveau, C., Gayme, D., 69th Annual Meeting of the APS Division of Fluid Dynamics, A Predictive Model for Wind Farms Using Dynamic Mode Decomposition, Abstract: G35.00002 in Session G35: Turbulence: Wakes, The American Physical Society, Portland, OR. (November 21, 2016).
  8. Bretheim, J., Meneveau, C., Gayme, D., 69th Annual Meeting of the APS Division of Fluid Dynamics, Extending the restricted nonlinear model for wall-turbulence to high Reynolds numbers, Abstract: G33.00001 in Session G33: Turbulent Boundary Layers: Walls and Modeling, The American Physical Society, Portland, OR. (November 21, 2016).
  9. Shapiro, C., Meneveau, C., Gayme, D., 69th Annual Meeting of the APS Division of Fluid Dynamics, A simple dynamic wake model for time dependent wind turbine yaw, Abstract: D2.00001 in Session D2: Wind Turbines: Simulations, The American Physical Society, Portland, OR. (November 20, 2016)
  10. Martinez-Tossas, L. A., Churchfield, M. J., Meneveau, C., 69th Annual Meeting of the APS Division of Fluid Dynamics, “An actuator line model simulation with optimal body force projection length scales, Abstract: D2.00003 at Session D2: Wind Turbines: Simulations,” The American Physical Society, Portland, OR. (November 20, 2016).
  11. Shapiro, C. (Presenter & Author), Meneveau, C. (Author Only), Gayme, D. (Author Only), 1000 Island Energy Research Forum, “Wind Farm Control for Power Grid Frequency Regulation,” Alexandria Bay, NY. (October 29, 2016).
  12. Martinez-Tossas, L. A., Churchfield, M. J., Meneveau, C., The Science of Making Torque from Wind (TORQUE 2016), “Highly Resolved Large-Eddy Simulation of a Wind Turbine using an Actuator Line Model with Optimal Body Force Projection,” accepted for presentation, Munich, Germany. (October 5, 2016)
  13. Shapiro, C., Meyers, J., Meneveau, C., Gayme, D., The Science of Making Torque from Wind TORQUE 2016), “Wind farms providing secondary frequency regulation: Evaluating the performance of model-based receding horizon control,” accepted for presentation, Munich, Germany. (October 5, 2016)
  14. Bretheim, J., Meneveau, C., Gayme, D., 24th International Congress of Theoretical and Applied Mechanics ICTAM 2016, “A Restricted Nonlinear Large-Eddy Simulation Model For Wall-Bounded Turbulence,” Contributed talk, Montreal, Canada. (August 21, 2016).
  15. Meneveau, C., WindFarms in Complex Terrain, “Modeling boundary layer flow over fractal-like, multi-scale terrain in large eddy simulations,” Plenary Speaker, Euromech Colloquium, KTH, Stockholm, Sweden. (June 8, 2016).
  16. Bretheim, J., Meneveau, C., Gayme, D., WindFarms 2016 Meeting, “A Restricted Nonlinear Large Eddy Simulation Model for Turbulent Boundary Layers and Wind Farm Applications,” The University of Texas at Dallas, Richardson, TX. (May 24, 2016).
  17. Gayme, D., Meneveau, C., WindFarms 2016 Meeting, “Reduced order modeling for wind farm design and control,” The University of Texas at Dallas, Richardson, TX. (May 24, 2016).
  18. Thomas, V., Meneveau, C., Gayme, D., WindFarms 2016 Meeting, “Reduced order models of wind farms using Dynamic Mode Decomposition,” The University of Texas at Dallas, Richardson, TX. (May 24, 2016).
  19. Shapiro, C., Meneveau, C., Gayme, D. (2016). A simple dynamic wake model for time dependent wind turbine yaw (abstract only)., Bulletin of the American Physical Society, Div. of Fluid Dynamics (20th ed., vol. 61, pp. 97). Published.
  20. C. J. Harman, A. S. Ward, and A. Ball (2016), How does reach-scale stream-hyporheic transport vary with discharge? Insights from rSAS analysis of sequential tracer injections in a headwater mountain stream, Water Resources Research, 52, 7130–7150, doi:10.1002/2016WR018832.
  21. Kim, M., L. Pangle, C. Cardoso, M. Lora, T. Volkmann, Y. Wang, C. J. Harman, and P. Troch (2016), Transit time distributions and StorAge Selection functions in a sloping soil lysimeter with time-varying flow paths: Direct observation of internal and external transport variability, Water Resources Research, 52, 7105–7129, doi:10.1002/2016WR018620.
  22. Deng D; Arevalo HJ; Prakosa A; Callans DJ; Trayanova N, A feasibility study of arrhythmia risk prediction in patients with myocardial infarction and preserved ejection fraction, Europace 
  23. Karathanos TV, Boyle PM, Trayanova N. Light-based approaches to cardiac arrhythmia research: From basic science to translational applications. Clin Med Insights Cardiol. 10(Suppl 1):47-60, 2016. 
  24. Chang KC, Trayanova N. Mechanisms of arrhythmogenesis related to calcium-driven alternans in a model of human atrial fibrillation. Sci Rep Nov 4;6:36395. doi: 10.1038/srep36395, 2016
  25. Priest JR, Gawad C, Kahlig KM, Yu JK, O’Hara T, Boyle PM, Rajamani S, Clark MJ, Garcia ST, Ceresnak S, Harris J, Boyle S, Dewey FE, Malloy-Walton L, Dunn K, Grove M, Perez MV, Neff NF, Chen R, Maeda K, Dubin A, Belardinelli L, West J, Antolik C, Macaya D, Quertermous T, Trayanova N, Quake SR, Ashley EA. Early somatic mosaicism is a rare cause of long-QT syndrome, Proc Natl Acad Sci U S A. 113:11555-11560, 2016 (accompanied by a press release; story picked up bya number of national and international new outlets; featured video on PNAS webpage).
  26. Bruegmann T, Boyle PM, Vogt CC, Karathanos TV, Arevalo HJ, Fleischmann BK, Trayanova N, Sasse P. Optogenetic defibrillation terminates ventricular arrhythmia in mouse hearts and human simulations, J Clin Invest. 126:3894-3904, 2016 (accompanied by a press release and a video on YouTube and Facebook from JHU; story picked up by a number of national and international new outlets, including an interview by the Economist, and TV news by a number of TV channels around the country).
  27. HJ Arevalo, F Vadakkumpadan, E Guallar, A Jebb, P Malamas, KC Wu, N Trayanova. Arrhythmia risk stratification of patients after myocardial infarction using personalized heart models. Nature Communications. May 10;7:11437. doi: 10.1038/ncomms11437, 2016 (accompanied by a press release from JHU; story picked up by over 60 national and international new outlets, including an article in the Guardian and an interview on BBC. Chosen as Nature’s featured article, and accompanied by a review in Nature Reviews Cardiology)
  28. Zahid S, Whyte KN, Schwarz EL, Blake RC 3rd, Boyle PM, Chrispin J, Prakosa A, Ipek EG, Pashakhanloo F, Halperin HR, Calkins H, Berger RD, Nazarian S, Trayanova N. Feasibility of using patient-specific models and the “minimum cut” algorithm to predict optimal ablation targets for left atrial flutter. Heart Rhythm. 13:1687-1698, 2016
  29. Trayanova N, Chang KC. How computer simulations of the human heart can improve anti-arrhythmia therapy. J Physiol. 594:2483-2502, 2016.
  30. Zahid S, Cochet H, Boyle PM, Schwarz EL, Whyte KN, Vigmond EJ, Dubois R, Hocini M, Haïssaguerre M, Jaïs P,  Trayanova N. Patient-derived models link re-entrant driver localization in atrial fibrillation to fibrosis spatial pattern, Cardiovasc Res. 110(3):443-454, 2016
  31. Karathanos TV, PM Boyle, JD Bayer, D Wang, N Trayanova, Opsin Spectral Sensitivity Determines the Effectiveness of Optogenetic Termination of Ventricular Fibrillation in the Human Heart: A Simulation Study, J Physiol 2016 Mar 4. doi: 10.1113/JP271739. [Epub ahead of print]
  32. Ukwatta E, Arevalo H, Li K, Yuan J, Qiu W, Malamas P, Wu KC, Trayanova N, Vadakkumpadan F. Myocardial Infarct Segmentation from Magnetic Resonance Images for Personalized Modeling of Cardiac Electrophysiology, IEEE Trans 
  33. Stevens, R. J. A. M., Gayme, D. F., Meneveau, C. (2016). Generalized Coupled Wake Boundary Layer Model: Applications and Comparisons with Field and LES Datafor Two Real Wind-Farms. Wind Energy, 19(11). Published
  34. Stevens, R. J. A. M., Gayme, D., Meneveau, C. (2016). Effects of turbine spacing on the power output of extended wind-farms. Wind Energy, 19(2), 359-370. Published.
  35. Shapiro, C., Meyers, J., Meneveau, C., Gayme, D., Model-Based Receding Horizon Control of Wind Farms for Secondary Frequency Regulation. Proc. of the American Control Conference.
  36. Gayme, D. (2016)., Wind farms providing secondary frequency regulation: Evaluating the performance of model-based receding horizon control (5th ed., vol. 753, pp. 052012).
    Journal of Physics: Conference Series. Published.
  37. Gayme, D. (Guest Speaker), Offshore Wind IGERT Seminar Series, “New directions in wind farm modeling and control,” University of Massachusetts Amherst. (December 1, 2016). Invited.
  38. Gayme, D., 10th Annual Trans-Atlantic Infraday Conference, “Finding new markets for wind energy: Exploiting wind farm flow physics to enable more cost effective secondary frequency regulation with wind,” Federal Energy Regulatory Commission, Washington, DC. (November 10, 2016). Invited.
  39. Gayme, D. (Guest Speaker), Mechanical and Aerospace Engineering Colloquium, “The restricted nonlinear model: a minimal model for self-sustaining turbulence in wall bounded shear flows,” Cornell University, New York. (September 27, 2016). Invited.
  40. Gayme, D. (Guest Speaker), Department of Aerospace and Mechanical Engineering Seminar Series, “The Restricted Nonlinear System: A Minimal Model for Self-Sustaining Turbulence in Wall Bounded Shear Flows,” University of Notre Dame. (September 13, 2016). Invited.
  41. Gayme, D. (Presenter & Author), Thomas, V. (Author Only), Mini- Symposium on Bypass Transition, “Restricted Nonlinear Roll/Streak Dynamics in Plane Couette Flow,” 24th International Congress of Theoretical and Applied Mechanics (ICTAM), Montreal, Quebec. (August 22, 2016). Invited.
  42. Gayme, D. (Presenter & Author), Shapiro, C. (Author Only), Meyers, J. (Author Only), (Author Only), Symposium on Experiments and Simulations in Fluid Dynamics Research, “Model-based wind farm control for power grid frequency regulation,” Queens University, Kingston, ON, Candada. (August 19, 2016). Invited.
  43. Gayme, D. (Presenter Only), FREEDM Systems Center Special Seminar, “Management of energy resources for flexible and efficient power systems,” Electrical and Computer Engineering, North Carolina State University. (February 19, 2016). Invited.
  44. Thomas, V., Meneveau, C., Gayme, D., 69th Annual Meeting of the APS Division of Fluid Dynamics, “A Predictive Model for Wind Farms Using Dynamic Mode Decomposition, Abstract: G35.00002 in Session G35: Turbulence: Wakes,” The American Physical Society, Portland, OR. (November 21, 2016).
  45. Bretheim, J., Meneveau, C., Gayme, D., 69th Annual Meeting of the APS Division of Fluid Dynamics, “Extending the restricted nonlinear model for wall-turbulence to high Reynolds numbers, Abstract: G33.00001 in Session G33: Turbulent Boundary Layers: Walls and Modeling,” The American Physical Society, Portland, OR. (November 21, 2016).
  46. Shapiro, C., Meneveau, C., Gayme, D., 69th Annual Meeting of the APS Division of Fluid Dynamics, “A simple dynamic wake model for time dependent wind turbine yaw, Abstract: D2.00001 in Session D2: Wind Turbines: Simulations,” The American Physical Society, Portland, OR. (November 20, 2016).
  47. Shapiro, C. (Presenter & Author), Meneveau, C. (Author Only), Gayme, D. (Author Only), 1000 Island Energy Research Forum, “Wind Farm Control for Power Grid Frequency Regulation,” Alexandria Bay, NY. (October 29, 2016).
  48. Shapiro, C., Meyers, J., Meneveau, C., Gayme, D., The Science of Making Torque from Wind (TORQUE 2016), “Wind farms providing secondary frequency regulation: Evaluating the performance of model-based receding horizon control,” accepted for presentation, Munich, Germany. (October 5, 2016).
  49. Bretheim, J., Meneveau, C., Gayme, D., 24th International Congress of Theoretical and Applied Mechanics ICTAM 2016, “A Restricted Nonlinear Large-Eddy Simulation Model For Wall-Bounded Turbulence,” Contributed talk, Montreal, Canada. (August 21, 2016).
  50. Stevens, R. J.A.M., Martinez-Tossas, L. A., Gayme, D., Meneveau, C., 24th International Congress of Theoretical and Applied Mechanics ICTAM 2016, “Simulation and modeling of extended wind farms,” Contributed talk,, Montreal, Canada. (August 21, 2016).
  51. Stevens, R. J. A. M. (Presenter & Author), Gayme, D. (Author Only), Meyers, J. (Author Only), Meneveau, C., EUROMECH Colloquium 576, Wind Farms in Complex Terrains, “LES Studies of Wind Farms Including Wide Turbine Spacings and Comparisons with the CWBL Engineering Model,” EUROMECH, KTH Royal Institute of Technology, Stockholm. (June 2016).
  52. Gayme, D. (Presenter & Author), Shapiro, C. (Author Only), Meyers, J. (Author Only), Meneveau, C. (Author Only), EUROMECH Colloquium 576, Wind Farms in Complex Terrains, “Using LES to Develop and Validate Model-Based Wind Farm Control,” EUROMECH, KTH Royal Institute of Technology, Stockholm. (June 2016).
  53. Bretheim, J., Meneveau, C., Gayme, D., WindFarms 2016 Meeting, “A Restricted Nonlinear Large Eddy Simulation Model for Turbulent Boundary Layers and Wind Farm Applications,” The University of Texas at Dallas, Richardson, TX. (May 24, 2016).
  54. Gayme, D., Meneveau, C., WindFarms 2016 Meeting, “Reduced order modeling for wind farm design and control,” The University of Texas at Dallas, Richardson, TX. (May 24, 2016).
  55. Thomas, V., Meneveau, C., Gayme, D., WindFarms 2016 Meeting, “Reduced order models of wind farms using Dynamic Mode Decomposition,” The University of Texas at Dallas, Richardson, TX. (May 24, 2016).
  56. Shapiro, C., Bauweraerts, P., Meyers, J., Meneveau, C., Gayme, D., WindFarms 2016 Meeting, “Model-based receding horizon control of wind farms for secondary frequency regulation,” The University of Texas at Dallas, Richardson, TX. (May 23, 2016).
  57. Mo A, Luo C, Davis FP, Mukamel EA, Henry GL, Nery JR, Urich MA, Picard S, Lister R, Eddy SR, Beer MA, Ecker JR, and Nathans J, Epigenomic landscapes of retinal rods and cones. eLife 5, e11613 (2016).
  58. Ghandi M, Mohammad-Noori M, Ghareghani N, Lee D, Garraway L, and Beer MA, gkmSVM, an R package for gapped-kmer SVM. Bioinformatics 10.1093/bioinformatics/btw203 (2016).
  59. Migeon BR, Beer MA, and Bjornsson HT, Embryonic loss of human females with partial trisomy 19 identifies region critical for the single active X. Plos ONE 12 (4), e0170403 (2017).
  60. Kreimer A, Zeng H, Edwards M, Guo Y, Tian K, Shin S, Welch R, Wainberg M, Mohan R, Sinnott-Armstrong N, Li Y, Amin T, Goke J, Mueller N, Kellis, M, Kundaje A, Beer MA, Keles S, Gifford D, and Yosef N, Predicting Gene Expression in Massively Parallel Reporter Assays: A Comparative Study. Human Mutation (2017).
  61. Cheng CS, Gate RE, Siba A, Tabaka M, Lituiev D, Subramaniam M, Hougen KL, Shamim M, Wortman I, Aiden AP, Machol I, Feng T, De Jager PL, Chang H, Lieberman Aiden E, Benoist C, Beer MA, Ye CJ, Regev A, Genetic determinants of chromatin accessibility and gene regulation in T cell activation across human individuals, Nature Genetics under review, bioRxiv, 090241 (2017).
  62. Beer MA, Predicting Enhancer Activity and Variant Impact using gkm-SVM.  Human Mutation (2017).
  63. Xie F and Xu Y#, NDPP-Mix: Nested Dirichlet Process-Determinantal Point Process Mixture Model. Submitted
  64. Li Y, Dinalankara W, Marchionni L, Kochel C, Nirschl T, Drake C, and Xu Y#, BayRepulsive: A Bayesian Repulsive Deconvolution Model for Inferring Tumor Heterogeneity. Submitted 
  65. Xie F and Xu Y#, Bayesian Repulsive Gaussian Mixture Model. Submitted 
  66. Xie F, Zhou M, and Xu Y#, BayCount: A Bayesian Decomposition Method for Inferring Tumor Heterogeneity using RNA-Seq Counts. Submitted 
  67. Xu Y, Xu Y, and Saria S, Bayesian Estimation of Individualized Treatment-Response Curves in Populations with Heterogeneous Treatment Effects. Journal ofMachine Learning Research. In Press.
  68. Xu Y, Xu Y, and Saria S, A Non-parametric Bayesian Approach for Estimating Treatment-Response Curves from Sparse Time Series. Proceedings of the 1st Machine Learning for Healthcare Conference. 2016, 282-300. 
  69. DiPietro, Robert, et al. “Recognizing surgical activities with recurrent neural networks.” International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer International Publishing, 2016.
  70. DiPietro, Robert, Christian Rupprecht, Nassir Navab, and Gregory D. Hager. “Analyzing and Exploiting NARX Recurrent Neural Networks for Long-Term Dependencies.” arXiv preprint arXiv:1702.07805 (2017).
  71. Chi Li, Han Xiao, Keisuke Tateno, Federico Tombari, Nassir Navab, and Gregory D Hager. Incremental scene understanding on dense slam. In International Conference on Intelligent Robots and Systems (IROS), 2016
  72. Chi Li, Jonathan Boheren, Eric Carlson, and Gregory D Hager. Hierarchical semantic parsing for object pose estimation in densely cluttered scenes. In International Conference on Robotics Automation (ICRA), 2016
  73. Chi Li, Austin Reiter, and Gregory D Hager. Beyond spatial pooling: Fine-grained representation learning in multiple domains. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 4913–4922, 2015
  74. Chi Li, Jonathan Boheren, and Gregory D Hager. Bridging the robot perception gap with mid-level vision. In International Symposium on Robotics Research (ISRR), 2015
  75. Chi Li, Le Lu, Gregory D Hager, Jianyu Tang, and Hanzi Wang. Robust object tracking in crowd dynamic scenes using explicit stereo depth. In Asian Conference on Computer Vision (ACCV), pages 71–85. Springer, 2012
  76. Billings S.D. et al. (2016) Anatomically Constrained Video-CT Registration via the V-IMLOP Algorithm. In: Ourselin S., Joskowicz L., Sabuncu M., Unal G., Wells W. (eds) Medical Image Computing and Computer-Assisted Intervention — MICCAI 2016. MICCAI 2016. Lecture Notes in Computer Science, vol 9902. Springer, Cham 16GT: a fast and sensitive variant caller using a 16-genotype probabilistic model
  77. Luo, R, Schatz, MC, Salzberg, SL (2017) GigaScience doi: https://doi.org/10.1093/gigascience/gix045
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