top of page
Peng Zhang, Ph.D. @ AI-BioMedical Engineering
IMG_5837 (4).JPG

My focus areas within Computational Biomedical Engineering are High-Performance Computing (HPC), Multiscale Modeling (MSM), Machine Learning (ML), and Cloud technologies in BioMedical Engineering (BME) and Digital Health (DH).

My Academic-and-Industrial research and products included the technologies of:

  • Computational Biomedical Engineering

  • AI-Guided Multiscale Modeling

  • Wearable Medical Device

  • Software-as-a-Medical-Device (SaMD)

  • Machine Learning (ML) BoBiA

Education​

  • PostDoc at Biomedical Engineering, Stony Brook University, New York, USA

  • Ph.D. at Applied Mathematics, Stony Brook University, New York, USA

  • M.Sc. at Parallel Computing, Nankai University, Tianjin, China

  • B.Sc. at Computational Mathematics, Nankai University, Tianjin, China

Professional Experiences in
AI-Biomedical Engineering on Cloud

  • 2019-now, CTO & Co-Founder of ZBeats Inc. focusing on the development of AI-Cloud & IoT technologies for long-term remote telehealth software & wearables solutions. The product is funded by America's NSF Digital Health SBIR and NIH NHLBI STTR Clinical Study programs.

  • 2020-2022, Research Assistant Professor at Stony Brook University with a focus on AI-Guided Multiscale Modeling.

  • 2016-2019, Research Scientist, Senior Research Associate at Stony Brook University. Project: Multiscale Modeling of Blood Flow and Platelet Mediated Thrombosis (Award Number: NIH NHLBI U01HL131052, Total: $3.6M).

  • 2012-2015, Research Associate at Biomedical Engineering Department of Stony Brook University. Project: Multiscale Modeling of Blood Flow and Clotting in Cardiovascular Devices (Award Number: 1R21HL096930-01A2, Total: $190K).

  • 2010-2011, Consultant Engineer at Enterprise Grid Engineering at Bank of America Merrill Lynch, 222 Broadway, NY 10038. Project: Enterprise Grid Computing Solution, and High-Utilization Grid Scheduler.

  • 2008-2010, Research Assistant at Applied Mathematics Department of Stony Brook University. Research in Computational Applied Mathematics with a focus on high-performance computing (HPC) algorithms and applications.

Teaching Experiences in Applied Mathematics and Statistics

  • AMS 361 Applied Calculus IV: Differential Equations - Spring 22', Winter 22', Fall 21', Summer 21', Winter 21', Summer 20', Fall 08'.

  • AMS 326 Numerical Analysis - Fall 22', Summer 21'.

  • AMS 261 Applied Calculus III - Fall 09'.

  • AMS 503 Applications of Complex Analysis - Fall 13'.

  • AMS 530 Principles in Parallel Computing - Fall 21'.

Awards and Honors

  • 2020, National Science Foundation (NSF) Panelist.

  • 2020, Travel Award and Finalist for Oral Presentation Competition for 13th Multiscale Modeling (MSM) Consortium Meeting held by NIH IMAG, March 2020.

  • 2017-now, Top Peer Reviews, Publons.

  • 2015, U.S. Permanent Resident: First Preference EB-1A, Foreign National with an Extraordinary Ability in the Sciences.

  • 2010, SuperComputing 2010 Travel Scholarship of Asian Technology Information Program.

  • 2003, Admission to Postgraduate Programs with Exemption of Exams, Nankai University.

  • 2002, National Scholarship of Nankai Univesity.

Academic & Industrial Funding

  • 2022~2023, Principal Investigator for NIH NHLBI STTR Phase I: Feasibility testing of a novel AI-enabled, cloud-based ECG diagnostic solution to enable fast and affordable diagnosis in long-term continuous ambulatory ECG monitoring. Grant number: 1R41HL160317. Award amount: $259,613.

  • 2020~2021, Principal Investigator for NSF SBIR Phase I: A Cloud-based, AI-enabled ECG Analysis Platform for More Efficient Arrhythmia Detection (Digital Health). Awarded amount: $276,000.

  • 2020~2021, Principal Investigator for "Multiscale Modeling of Binding SARS-CoV-2 to Various Substrates" funded by Office of the Vice President for Research & the Institute for Engineering-Drive Medicine COVID-19 Seed Grant, Stony Brook University. Awarded Amount: $25,000. (17 winners from 63 submissions)

  • 2020~now, Principal Investigator for "Scalable Multiscale Simulator for Platelet Mediated Thrombosis" funded by Rensselaer Polytechnic Institute CCI (Project ID: LCLB). Awarded resources at the Artificial Intelligence Multiprocessing Optimized System (AiMOS) to explore new AI applications. Research is highlighted at SUNY AiMOS Projects Spotlight.

  • 2020, Principal Investigator for "The Analysis of Binding SARS-CoV-2 to Various Substrates" funded by the COVID-19 HPC Consortium project BIO200016. Awarded Resources: 88K GPU hours on SDSC Comet HPC.

  • 2016~2020, Senior Personnel (Research Scientist) for "Multiscale Modeling of Blood Flow and Platelet Mediated Thrombosis" funded by NIH NHLBI, Project Number: 5U01HL131052-03. The 5-year total awarded amount is $3,597,060.

  • 2017~2018, Principal Investigator for XSEDE Research Project Award, Project Number: DMS150011 renewal. 657,703 core hours on SDSC Comet. Awarded Resource is $21,895.20 of NSF investment in advanced computing infrastructure.

  • 2015~2017, Principal Investigator for XSEDE Research Project Award, Project Number: DMS150011. 1.8 million core hours on SDSC Comet HPC. Awarded Resource: $59,521.47 of NSF investment in advanced computing infrastructure.

  • 2014~2015, Principal Investigator for XSEDE Start-up Research Project Award DMS140019. Awarded Resource: 120K core hours on TACC Stampede HPC.

Journal & Conference Papers

TOPIC 1: Integration of Artificial Intelligence and Multiscale Modeling (AI-MSM) for Biomedical Applications.

  1. Zhou, Y., Zhang, P., Song, M., Zheng, A., Lu, Y., Liu, Z., Chen, Y. and Xi, Z., "Zodiac: A Cardiologist-Level LLM Framework for Multi-Agent Diagnostics". arXiv preprint arXiv:2410.02026 (2024).

  2. Zhang, Z, Kementzidis, Zhang, P., Zhang, L., Kozloski, J., Hansen, A., Rafailovich, M., Simon, M., Deng, Y., "Learning Coarse-Grained Force Fields for Fibrogenesis Modeling". Computer Physics Communications, volume 295, 2024, 108964, DOI: 10.1016/j.cpc.2023.108964.

  3. Wang, P., Sheriff, J., Zhang, P., Deng, Y., Bluestein, D. "A Multiscale Model for Shear-Mediated Platelet Adhesion Dynamics: Correlating In Silico with In Vitro Results". Annals of Biomedical Engineering, 5 April 2023. DOI: 10.1007/s10439-023-03193-2

  4. Zhu, Y., Han, C., Zhang, P., Cong, G., Kozloski, J., Yang, C-C, Zhang, L., Deng, Y.. "AI-Aided Multiscale Modeling of Physiologically-Significant Blood Clots". Computer Physics Communications, 7 March 2023. 108718. DOI: 10.1016/j.cpc.2023.108718

  5. Niu, Z., Kementzidis, G., Zhang, Z., et al., "Modelling of SARS-CoV-2 spike protein structures at varying pH values". Molecular Simulation, 16 Oct 2024. DOI: 10.1080/08927022.2024.2415524

  6. Niu, Z., Hasegawa, K., Deng, Y., Zhang, Z., Rafailovich, M., Simon, M., Zhang, P (2022) "Modeling of the thermal properties of SARS-CoV-2 S-protein". Frontier in Molecular Biosciences, Section Biological Modeling and Simulation, 9:953064. DOI: 10.3389/fmolb.2022.953064

  7. Han, C., Zhang, P., Zhu, Y., Cong, G., Kozloski, J.R., Yang, C-C., Zhang, L., Deng, Y., "Scalable Multiscale Modeling of Platelets with 100 Million Particles", Journal of Supercomputing, 2022. DOI: 10.1007/s11227-022-04648-4.

  8. Zhang, Z., Zhang, P., Han, C., Cong, G., Yang, C-C., Deng, Y., "Online Machine Learning for Accelerating Molecular Dynamics Modeling of Cells", Frontiers in Molecular Biosciences, section Biological Modeling and Simulation, 27 January 2021. DOI: 10.3389/fmolb.2021.812248.

  9. Niu, Z., Zhang, P., Rafailovich, M., Simon, M., Song, M., Deng, Y., "Molecular Dynamics Modeling of the SARS-CoV-2 Spike Protein at pH2 Through pH11. 5", Journal of Molecular Modeling, 2021. DOI: 10.21203/rs.3.rs-665823/v1

  10. Zhu Y., Zhang P., Han C., Cong G., Deng Y. "Enabling AI-Accelerated Multiscale Modeling of Thrombogenesis at Millisecond and Molecular Resolutions on Supercomputers", International Conference on High Performance Computing, ISC 2021. Lecture Notes in Computer Science, vol 12728. pp 237-254. DOI: 10.1007/978-3-030-78713-4_13

  11. Sheriff, J., Wang, P., Zhang, P., Zhang, J., Deng, Y., Bluestein, D., "In Vitro Measurements of Shear-Mediated Platelet Adhesion Kinematics as Analyzed through Machine Learning", Annals of Biomedical Engineering, vol 49, 3452-3464, 2021. DOI: 10.1007/s10439-021-02790-3

  12. Gupta, P., Zhang, P., Sheriff, J., Bluestein, D., Deng, Y., "A Multiscale Model for Multiple Platelet Aggregation in Shear Flow", Biomechanics and Modeling in Mechanobiology, vol 20, 1013-1030, 2021. DOI: 10.1007/s10237-021-01428-6

  13. Zhang, J., Zhang, P., Wang, P., Sheriff, J., Bluestein, D., Deng, Y. "Rapid Analysis of Streaming Platelet Images by Semi-unsupervised Learning", Computerized Medical Imaging and Graphics, vol 89, pp. 101895, April 2021, DOI: 10.1016/j.compmedimag.2021.101895

  14. Han, C., Zhang, P., Bluestein, D., Cong, G., Deng, Y., "Artificial Intelligence for Accelerating Time Integrations in Multiscale Modeling", Journal of Computational Physics, vol. 427, pp. 110053, February 2021. DOI: 10.1016/j.jcp.2020.110053

  15. Zhang, P., Sheriff, J., Einav, S., Slepian, MJ., Deng, Y., Bluestein, D., "A Predictive Multiscale Model for Simulating Flow-Induced Platelet Activation: Correlating In Silico Results with In Vitro Results", Journal of Biomechanics, vol. 115, pp. 110275, March 2021. DOI: 10.1016/j.jbiomech.2021.1102750

  16. Gupta, P., Zhang, P., Sheriff J., Bluestein D., Deng Y. "A Multiscale Model for Recruitment Aggregation of Platelets by Correlating with In vitro Results", Cellular and Molecular Bioengineering, vol 12, pp. 327-343, August 2019. DOI: 10.1007/s12195-019-00583-2

  17. Yazdani A., Zhang P., Sheriff J., Slepian M.J., Deng Y., Bluestein D. (2018) “Multiscale Modeling of Blood Flow-Mediated Platelet Thrombosis.” In: Andreoni W., Yip S. (eds) Handbook of Materials Modeling. Springer, Cham DOI: 10.1007/978-3-319-50257-1_69-1

  18. Gao, C., Zhang, P., Marom, G., Deng, Y., Bluestein, D., "Reducing the Effects of Compressibility in DPD-based Blood Flow Simulations through Severe Stenotic Microchannel", Journal of Computational Physics, vol. 335, pp. 812-827, 15 April 2017. DOI: 10.1016/j.jcp.2017.01.062

  19. Zhang, P., Zhang, L., Slepian, M.J., Deng, Y., Bluestein, D., "A Multiscale Biomechanical Model of Platelets: Correlating with In-Vitro Results", Journal of Biomechanics, vol. 50, pp. 26-33, 4 January 2017. DOI: 10.1016/j.jbiomech.2016.11.019

  20. Zhang, P., Zhang, N., Gao, C., Zhang, L., Gao, Y., Deng, Y., Bluestein, D., "Scalability Test of Multiscale Fluid-Platelet Model for Three Top Supercomputers", Computer Physics Communications, vol. 204, pp. 132-140, July 2016. DOI: 10.1016/j.cpc.2016.03.019

  21. Zhang, P., Zhang, N., Deng, Y., Bluestein, D., "A Multiple Time Stepping Algorithm for Efficient Multiscale Modeling of Platelets Flowing in Blood Plasma", Journal of Computational Physics, vol. 284, pp. 668-686, 1 March 2015. DOI: 10.1016/j.jcp.2015.01.004

  22. Pothapragada, S., Zhang, P., Sheriff, J., Livelli, M., Slepian, M.J., Deng, Y., Bluestein, D., "A Phenomenological Particle-Based Platelet Model for Simulating Filopodia Formation during Early Activation", International Journal for Numerical Methods in Biomedical Engineering, vol. 31, no. 3, pp. 1-16, March 2015. DOI: 10.1002/cnm.2702

  23. Zhang, N., Zhang, P., Zhang, L., Zhu, X., Huang, L., Deng, Y., "Performance Examinations of Multiple Time-Stepping Algorithms on Stampede Supercomputer", in Proceedings of the 2015 XSEDE Conference: Scientific Advancements Enabled by Enhanced Cyberinfrastructure, St. Louis, Missouri, 2015. DOI: 10.1145/2792745.2792753

  24. Zhang, P., Gao, C., Zhang, N., Slepian, M.J., Deng, Y., Bluestein, D., "Multiscale Particle-Based Modeling of Flowing Platelets in Blood Plasma Using Dissipative Particle Dynamics and Coarse Grained Molecular Dynamics", Cellular and Molecular Bioengineering, vol. 7, no. 4, pp. 552-574, December 2014. DOI: 10.1007/s12195-014-0356-5

  25. Bluestein, D., Soares, J. S., Zhang, P., Gao, C., Pothapragada, S., Zhang, N., Slepian, M.J., Deng, Y., "Multiscale Modeling of Flow Induced Thrombogenicity With Dissipative Particle Dynamics and Molecular Dynamics", Journal of Medical Devices, vol. 7, issue 4, pp. 024502-024503, April 2014. DOI: 10.1115/1.4027347

  26. Zhang, N., Zhang, P., Kang, W., Bluestein, D., Deng, Y., "Parameterizing the Morse potential for coarse-grained modeling of blood plasma", Journal of Computational Physics, vol. 257, Part A, pp. 726-736, 15 January 2014. DOI: 10.1016/j.jcp.2013.09.040

  27. Zhang, P., Sheriff, J., Soares, J.S., Gao, C., Pothapragada, S., Zhang, N., Deng, Y., Bluestein, D. "Multiscale Modeling of Flow Induced Thrombogenicity Using Dissipative Particle Dynamics and Coarse Grained Molecular Dynamics," in Proceedings of the ASME 2013 Summer Bioengineering Conference, Sunriver, Oregon, June 26-29, 2013. DOI: 10.1115/SBC2013-14187

  28. Bluestein, D., Soares, J.S., Zhang, P., Gao, C., Pothapragada, S., Zhang, N., Slepian, M.J., Deng, Y. "Multiscale Modeling of Flow Induced Thrombogenicity with Dissipative Particle Dynamics (DPD) and Molecular Dynamics (MD)," in Proceedings of the ASME/FDA 2013 1st Annual Frontiers in Medical Devices: Applications of Computer Modeling and Simulation FMD 2013, Washington, D.C., September 11-13, 2013. DOI: 10.1115/FMD2013-16176

  29. Bluestein, D., Soares, J.S., Zhang, P., Gao, C., Pothapragada, S., Zhang, N., Slepian, M.J., Deng, Y. “Multiscale Modeling of Flow Induced Thrombogenicity Using Dissipative Particle Dynamics and Molecular Dynamics," in Proceedings of the ASME 2013 2nd Global Congress on NanoEngineering for Medicine and Biology, Boston, Massachusetts, USA, February 4–6, 2013. DOI: 10.1115/NEMB2013-93094

TOPIC 2: Research at High Performance Computing, Machine Learning, Big Data and Cloud.

  1. Liang, D.; Zhang, Z.; Rafailovich, M.; Simon, M.; Deng, Y.; Zhang, P. "Coarse-Grained Modeling of the SARS-CoV-2 Spike Glycoprotein by Physics-Informed Machine Learning". Computation 2023, vol. 11, no. 2, pp. 24. DOI: 10.3390/computation11020024

  2. Liang, D., Song, M., Niu, Z., Zhang, P., Rafailovich, M., Deng, Y., "Supervised Machine Learning Approach to Molecular Dynamics Forecast of SARS-CoV-2 Spike Glycoproteins at Varying Temperatures", Materials Research Society Advances. 2021. DOI: 10.1557/s43580-021-00021-4

  3. Zhang, P., Liu, Y., Qiu, M., "SNC: A Cloud Service Platform for Symbolic-Numeric Computation using Just-In-Time Compilation", Cloud Computing, IEEE Transactions on, vol. 7, no. 2, pp. 580-592, 2019. DOI: 10.1109/TCC.2017.2656088

  4. Zhang, P., Shi, X., Khan, S.U., "QuantCloud: Enabling Big Data Complex Event Processing for Quantitative Finance through a Data-Driven Execution", Big Data, IEEE Transactions on, vol. 5, no. 4, pp. 564-575, 1 Dec. 2019. DOI: 10.1109/TBDATA.2018.2847629

  5. Zhang, P., Yu, K., Yu, J., Khan, S.U., "QuantCloud: Big Data Infrastructure for Quantitative Finance on the Cloud", Big Data, IEEE Transactions on, vol. 4, no. 3, pp. 368-380, 1 Sept. 2018. DOI: 10.1109/TBDATA.2017.2649544

  6. Zhang, P., Gao, Y., Shi, X., "QuantCloud: A Software with Automated Parallel Python for Quantitative Finance Applications", in Proceedings of 2018 IEEE International Conference on Software Quality, Reliability and Security (QRS), 16-20 July 2018. pp 388-396. DOI: 10.1109/QRS.2018.00052

  7. X. Shi, P. Zhang and S.U. Khan, "Quantitative Data Analysis in Finance," in Handbook of Big Data Technologies, A. Y. Zomaya and S. Sakr, Eds., Springer International Publishing, 2017, pp. 719-753. DOI: 10.1007/978-3-319-49340-4_21

  8. Zhang, P., Shi, X., Khan, S.U., "Can Quantitative Finance Benefit from IoT?", In Proceedings of Second ACM/IEEE Symposium on Edge Computing: Workshop on Smart IoT (SmartIoT 17), San Jose / Silicon Valley, CA, USA, October 14, 2017. DOI: 10.1145/3132479.3132491

  9. B. Fang and P. Zhang, "Big Data in Finance," in Big Data Concepts, Theories, and Applications, S. Yu and S. Guo, Eds., ed Cham: Springer International Publishing, 2016, pp. 391-412. DOI: 10.1007/978-3-319-27763-9_11

  10. Liu, H., Zhang, P., Wang, K., Yang, Bo., Chen, Z., "Performance and Scalability Analysis for Parallel Reservoir Simulations on Three Supercomputer Architectures", in Proceedings of the 2016 XSEDE Conference: Diversity, Big Data, & Science at Scale, Miami, FL, USA, 2016. DOI: 10.1145/2949550.2949577

  11. Chen, Y., Liu, H., Wang, K., Chen, Z., Zhang, P., "Large-scale Reservoir Simulations on Parallel Computers", in Proceedings of the 2nd IEEE International Conference on High Performance and Smart Computing (HPSC 2016), New York, NY, April 9-10, 2016. DOI: 10.1109/BigDataSecurity-HPSC-IDS.2016.20

  12. Wang, K., Lui, H., Luo, J. Yu, S., Chen, Z., Zhang, P., "Parallel Simulation of Full-Field Polymer Flooding", in Proceedings of the 2nd IEEE International Conference on High Performance and Smart Computing (HPSC 2016), New York, NY, April 9-10, 2016. DOI: 10.1109/BigDataSecurity-HPSC-IDS.2016.35

  13. Zhang, P., Gao, Y., "Matrix Multiplication on High-Density Multi-GPU Architectures: Theoretical and Experimental Investigations", in Lecture Notes in Computer Science, vol. 9137, pp 17-30, 20 June 2015. DOI: 10.1007/978-3-319-20119-1_2

  14. Zhang, P., Ling, L., Deng, Y., "A Data-driven Paradigm for Mapping Problems", Parallel Computing, vol. 48, pp. 108-124, 2015. DOI: 10.1016/j.parco.2015.05.002

  15. Zhang, P., Gao, Y., Qiu, M., "A Data-oriented Method for Scheduling Dependent Tasks on High-density Multi-GPU Systems", in High Performance Computing and Communications (HPCC), 2015 IEEE 17th International Conference on, New York, NY, August 24-26, 2015, pp. 694-699. DOI: 10.1109/HPCC-CSS-ICESS.2015.314

  16. Liu, Y., Zhang, P., Qiu, M., "Fast Numerical Evaluation for Symbolic Expressions in Java", in High Performance Computing and Communications (HPCC), 2015 IEEE 17th International Conference on, New York, NY, August 24-26, 2015, pp. 599-604. DOI: 10.1109/HPCC-CSS-ICESS.2015.19

  17. Gao, Y., Iqbal, S., Zhang, P., Qiu, M., "Performance and Power Analysis of High-Density Multi-GPGPU Architectures: A Preliminary Case Study", in High Performance Computing and Communications (HPCC), 2015 IEEE 17th International Conference on, New York, NY, August 24-26, 2015, pp. 66-71. DOI: 10.1109/HPCC-CSS-ICESS.2015.68

  18. Yu, K., Gao, Y., Zhang, P., Qiu, M., "Design and Architecture of Dell Acceleration Appliances for Database (DAAD): A Practical Approach with High Availability Guaranteed", in High Performance Computing and Communications (HPCC), 2015 IEEE 17th International Conference on, New York, NY, August 24-26, 2015, pp. 430-435. DOI: 10.1109/HPCC-CSS-ICESS.2015.67

  19. P. Zhang, Y. Deng, R. Feng, X. Luo and J. Wu, "Evaluation of Various Networks Configurated by Adding Bypass or Torus Links," in IEEE Transactions on Parallel and Distributed Systems, vol. 26, no. 4, pp. 984-996, 1 April 2015, DOI: 10.1109/TPDS.2014.2315201

  20. Sedighi, A., Deng, Y., Zhang, P., "Fairness of Task Scheduling in High Performance Computing Environments", Scalable Computing: Practice and Experience, vol. 15, no. 3, pp. 273-285, 2014. DOI: 10.12694/scpe.v15i3.1020

  21. Zhang, P., Gao, Y., Fierson, J., Deng, Y., "Eigenanalysis-Based Task Mapping on Parallel Computers with Cellular Networks," Mathematics of Computation, vol. 83, no. 288 (2014), pp. 1727 - 1756. DOI: 10.1090/S0025-5718-2013-02770-6

  22. Deng, Y., Zhang, P., Marques, C., Powell, R., Zhang, L., "Analysis of Linpack and Power Efficiencies of the World's TOP500 Supercomputers," Parallel Computing, vol. 39, pp. 271-279, 2013. DOI: 10.1016/j.parco.2013.04.007

  23. Zhang, P., Deng, Y., "An Analysis of the Topological Properties of the Interlaced Bypass Torus (iBT) Networks," Applied Mathematics Letters, vol. 25, pp. 2147-2155, Dec. 2012. DOI: 10.1016/j.aml.2012.05.013

  24. Feng, R., Zhang, P., Deng, Y., "Deadlock-free Routing Algorithms for 6D Mesh/iBT Interconnection Networks", in Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), 2013 14th ACIS International Conference on, 2013, pp. 275-282. DOI: 10.1109/SNPD.2013.43

  25. Zhang, P., Deng, Y., "Design and Analysis of Pipelined Broadcast Algorithms for the All-Port Interlaced Bypass Torus Networks", Parallel and Distributed Systems, IEEE Transactions on, vol. 23, no. 12, pp. 2245 - 2253, Dec. 2012, DOI:10.1109/TPDS.2012.93

  26. Feng, R., Zhang, P., Deng, Y., "Network Design Considerations for Exascale Supercomputers", Parallel and Distributed Computing and Systems (PDCS), 2012 24th IASTED International Conference on. November 12 - 14, 2012. Las Vegas, USA. DOI: 10.2316/P.2012.789-001

  27. Feng, R., Zhang, P., Deng, Y., "Simulated Performance Evaluation of a 6D Mesh/iBT Interconnect", in Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), 2012 13th ACIS International Conference on, 2012, pp. 253-259. DOI:10.1109/SNPD.2012.19

  28. Zhang, P., "A Methodology for Design and Applications of Parallel Computers", Ph.D. Dissertation, Department of Applied Mathematics and Statistics, State University of New York at Stony Brook, May 2012. [ProQuest/UMI | SUNY Digital Repository]

  29. Zhang, P., Powell, R., Deng, Y., "Interlacing Bypass Rings to Torus Networks for More Efficient Networks," Parallel and Distributed Systems, IEEE Transactions on, vol. 22, no. 2, pp. 287-295, Feb. 2011, DOI:10.1109/TPDS.2010.89

  30. Deng, Y., Korobka, A., Lou, Z., Zhang, P. "Perspective on Petascale Processing," KISTI Supercomputer, vol 31, pp. 36-59, 2008.

Publication

Refereed Abstracts and Presentations at International Conferences

  1. Wang, P., Zhu, Y., Sheriff, J., Zhang, P., Han, C., Deng, Y., Bluestein, D., "AI-Accelerated Multiscale Modeling for Platelet Adhesion Dynamics and Multi-Platelet Aggregation at Millisecond and Molecular Resolutions", 2022 Summer Biomechanics, Bioengineering, and Biotransport Conference (SB3C2022), June 20-23, Eastern Shore, MD, USA.

  2. Han, C., Zhu, Y., Zhang, P., Sheriff, J., Slepian, M.J., Bluestein, D., Deng, Y., "AI-Guided Multiscale Modeling for Platelets Aggregation and Adhesion under Shear Flow", BMES 2021 Annual Meeting, Orlando, Florida, October 6-9, 2021.

  3. Wang, P., Zhang, P., Sheriff, J., Han, C., Deng, Y., Bluestein, D., "A Multiscale Model of Platelet Adhesion Dynamics in Shear Flow", BMES 2021 Annual Meeting, Orlando, Florida, October 6-9, 2021.

  4. Zhang, Z., Zhao, Q., Wang, H., Adikes, R., Zhang, P., Martin, B., Matus, D., Deng, Y., "An Active Learning Workflow for 3D Morphological Analysis of Bioimages", Intelligent Systems for Molecular Biology and European Conference on Computational Biology, ISMB/ECCB 2021, July 25-30, 2021. (abstract #476)

  5. Sheriff, J., Wang, P., Zhang, P., Zhang, Z., Bahou, W., Deng, Y., Bluestein, D., “Machine Learning-Guided Analysis of Adult and Cord Platelet Adhesion Dynamics“, Intelligent XXIX Congress of the International Society on Thrombosis and Haemostasis (ISTH 2021), virtue poster presentation, July 17, 2021. (abstract #PB0967)

  6. Zhang, Z., Zhang, P., Rafailovich, M., Simon, M., Deng, Y., "AI-Guided Multiscale Biomechanical Model of Fibrinogen: correlating with in vitro results", IFRS - 26th International Fibrinogen Research Society Workshop, Session 3: Biomechanics, Structure and Polymerisation, June 15-16, 2021.

  7. Li, K., Essuman, B., Zhang, P., Rafailovich, M., Simon, M., Deng, Y., Galanakis, D., "Minimizing Surface-Initiated Thrombogenesis in H1N1 Patients Using the Fibronectin-Derived Peptide, P12", IFRS - 26th International Fibrinogen Research Society Workshop, Session 5: Fibrinolysis and Fibrin(ogen)-Cell Interactions June 15-16, 2021.

  8. Essuman, B., Zhang, P., Rafailovich, M., Simon, M., Deng, Y., "Modeling αC Domain and P12 Interactions to Study the Blocking of Fibrinogen Fiber", IFRS - 26th International Fibrinogen Research Society Workshop, Session 1: Fibrin Clot Properties, June 15-16, 2021.

  9. Zhang, P., Zhu, Y., Han, C., Sheriff, J., Deng, Y., Bluestein, D., "AI-Accelerated Multiscale Modeling for Multi-Platelet Aggregation at Millisecond and Molecular Resolutions", 2021 Virtual Summer Biomechanics, Bioengineering, and Biotransport Conference (SB3C2021), June 14-18, 2021.

  10. Sheriff, J., Wang, P., Zhang, P., Zhang, Z., Bahou, W., Deng, Y., Bluestein, D., "Platelet Adhesion Dynamics: Machine Learning-Assisted Analysis of Adult and Cord Platelets and Development of A Multiscale Model", 2021 Virtual Summer Biomechanics, Bioengineering, and Biotransport Conference (SB3C2021), June 14-18, 2021.

  11. Zhang, Z., Zhang. D., Narayanan, A., Ramabadran, A., Simon, M., Rafailovich, M., Deng, Y., Zhang, P., "AI-Guided Coarse-Graining for More Efficient Modeling of SARS-CoV-2 Spike Glycoprotein", 2020 MRS Spring/Fall Meeting & Exhibit, November 28 - December 4, 2020. (abstract #3480255)

  12. Song, M., Yang, F., Rafailovich, M., Simon, M., Deng, Y., Zhang, P., "Thermal Analysis of the SARS-CoV-2 Spike Glycoprotein by in silico and in vitro Experiments", 2020 MRS Spring/Fall Meeting & Exhibit, November 28 - December 4, 2020. (abstract #3481942)

  13. Swayze, K., Myers, J., Yang, F., Elder, R., Rafailovich, M., Simon, M., Deng, Y., Zhang, P., "Investigation of the COVID-19 Spike Glycoprotein at Varied Salt Concentrations: Correlating In Silico Simulations with In Vitro Droplet Drying Experiments", 2020 MRS Spring/Fall Meeting & Exhibit, November 28 - December 4, 2020. (abstract #3480907)

  14. Hasegawa, K., Essuman, B., Yang, F., Rafailovich, M., Simon, M., Deng, Y., Zhang, P., "Binding Dynamics of SARS-CoV-2 Spike Glycoprotein to Polylactic Acid", 2020 MRS Spring/Fall Meeting & Exhibit, November 28 - December 4, 2020. (abstract #3481262)

  15. Niu, Z., Rafailovich, M., Simon, M., Deng, Y., Zhang, P., "The pH-varying Conformational States of SARS-CoV-2 Spike Glycoprotein", 2020 MRS Spring/Fall Meeting & Exhibit, November 28 - December 4, 2020. (abstract #3481950)

  16. Zhang, Z., Zhang, P., Han, C., Cong, G., Yang, C-C., Deng, Y., "AI Meets HPC: Learning the Cell Motion in Biofluids", Supercomputing Conference 2020 (SC20), Research Posters Track, November 16–19, 2020. SC20 Best Research Poster Nominees. (poster).

  17. Han, C; Zhang, P. (advisor), Deng, Y. (advisor), "AI-Guided Adaptive Multiscale Modeling of Platelet Dynamics", Supercomputing Conference 2020 (SC20), ACM Graduate Student Posters Track, November 16–19, 2020. (poster)

  18. Song, M., Zhang, P., Han, C., Zhang, Z., Deng, Y., "Long-Time Simulation of Temperature-Varying Conformations of COVID-19 Spike Glycoprotein on IBM Supercomputers", Supercomputing Conference 2020 (SC20), Research Posters Track, November 16–19, 2020. (poster)

  19. Zhang, P., Sheriff, J., Gupta, P., Han, C., Wang, P., Zhang, Z., Slepian, M.J., Deng, Y., Bluestein, D., "An Integrated Machine Learning and Multiscale Modeling (ML-MSM) Framework for Platelet Adhesion and Aggregation under Shear Flow", BMES 2020 Virtual Annual Meeting, October 14-17, 2020. (abstract #1215)

  20. Wang, P., Sheriff, J., Zhang, P., Zhang, Z., Bahou, W., Deng, Y., Bluestein, D., "Machine Learning-Assisted Analysis of Adult and Cord Platelet Adhesion Dynamics", BMES 2020 Virtual Annual Meeting, October 14-17, 2020. (abstract #1408)

  21. Zhang, P., Sheriff, J., Zhang, Z., Wang, P., Gupta, P., Han, C., Slepian, M.J., Deng, Y., Bluestein, D., "A Multiscale Flow-Mediated Platelet Adhesion Model and Its Experimental Validation using Machine Learning", presented to International Conference on the Virtual Physiological Human (VPH2020), Paris, France, August 26-28, 2020.

  22. Sheriff, J., Zhang, P., Zhang, Z., Wang, P., Deng, Y., Bluestein, D., "Characterization of Flow-Mediated Platelet Activation and Adhesion Dynamics via Semi-Unsupervised Learning", presented at the 2020 Virtual Summer Biomechanics, Bioengineering, and Biotransport Conference (SB3C2020), June 17-20, 2020. (abstract #291)

  23. Zhang, P., Sheriff, J., Gupta, P., Han, C., Wang, P., Zhang, Z., Slepian, M.J., Deng, Y., Bluestein, D., "Machine Learning in Multiscale Modeling and Validation of In Vitro Experiments of Blood Flow and Platelet Mediated Thrombosis Initiation" presented to Integrating Machine Learning with Multiscale Modeling for Biomedical, Biological, and Behavioral Systems (2019 ML-MSM), Bethesda, Maryland (NIH Campus), October 24-25, 2019. (abstract | poster)

  24. Zhang P, Sheriff J, Gupta P, Han C, Wang P, Zhang Z, Slepian MJ, Deng Y, Bluestein D. "Machine Learning in Multiscale Modeling of Blood Flow and Platelet Mediated Thrombosis". presented to BMES 2019 Annual Fall Conference, Philadelphia, Pennsylvania, October 16-19, 2019. (abstract)

  25. Bluestein, D., Zhang, P., Sheriff, J., Gupta, P., Deng, Y., "Multiscale Modeling of Blood Flow and Platelet Mediated Thrombosis", presented at 16th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering (CMBBE 2019), in New York City, NY, USA, August 14-16, 2019.

  26. Zhang, P., Sheriff, J., Gupta, P., Han, C., Wang, P., Slepian, M.J., Deng, Y., Bluestein, D., "Machine Learning in Multiscale Modeling of Blood Flow and Platelet Mediated Thrombosis", presented at 2019 Multiscale Modeling Consortium Meeting Special Session on Machine Learning on the NIH main campus in Bethesda, MD, March 6, 2019.

  27. Zhang, P., Sheriff, J., Gupta, P., Han, C., Wang, P., Slepian, M.J., Deng, Y., Bluestein, D., "Multiscale Modeling of Blood Flow and Platelet Mediated Thrombosis", presented at 2019 Multiscale Modeling Consortium Meeting on the NIH main campus in Bethesda, MD, March 6-7, 2019.

  28. Zhang, P., Sheriff, J., Wang, P., Slepian, M.J., Deng, Y., Bluestein, D., "A Multiscale Flow-Mediated Platelet Adhesion Model and Its Experimental Validation", podium presentation at Summer Biomechanics, Bioengineering and Biotransport Conference (SB3C), Seven Springs, PA, USA, June 25-28, 2019.

  29. Zhang, P., Gupta, P., Sheriff, J., Han, C., Slepian, M.J., Deng, Y., Bluestein, D., "A Multiscale Model for Simulating Platelet Aggregation: Correlating with in vitro Results", podium presentation at Summer Biomechanics, Bioengineering and Biotransport Conference (SB3C), Seven Springs, PA, USA, June 25-28, 2019.

  30. Han, C., Gupta, P., Zhang, P., Bluestein, D., Deng, Y., "Machine Learning for Adaptive Discretization in Massive Multiscale Biomedical Modeling", presentation at the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC18), Dallas, TX, USA, November 11-16, 2018. (poster)

  31. Zhang, P., Sheriff, J., Gupta, P., Han, C., Slepian, M.J., Deng, Y., Bluestein, D. "Multiscale Modeling of Blood Flow and Platelet Mediated Thrombosis", BMES 2018 Annual Meeting, Atlanta, Georgia, October 17-20, 2018.

  32. Zhang, P., Sheriff, J., Gupta, P., Slepian, M.J., Deng, Y., Bluestein, D. "A Predictive Multiscale Model for Simulating Flow-Induced Platelet Activation and Aggregation: Correlating with In-Vitro Results", 8th World Congress of Biomechanics (WCB), Dublin, Ireland, July 8-12, 2018.

  33. Zhang, P., Sheriff, J., Gupta, P., Slepian, M.J., Deng, Y., Bluestein, D. "A Predictive Multiscale Model for Simulating Flow-Induced Platelet Activation and Aggregation: Correlating with In-Vitro Results", Summer Biomechanics, Bioengineering and Biotransport Conference (SB3C), Tucson, AZ, June 21-24, 2017. DOI: 10.13140/RG.2.2.17460.65926

  34. Zhang, P., Sheriff, J., Marom, G., Gao, C., Slepian, M.J., Yang, X., Sotiropoulos, F., Deng, Y., Bluestein, D. "A Predictive Multiscale Framework for Simulating Flow-Induced Platelet Activation: DNS-DPD-CGMD-MD," 5th International Conference on Computational and Mathematical Biomedical Engineering (CMBE2017), Pittsburgh, PA, United States, April 10-12, 2017.

  35. Zhang, P., Gao, C., Sheriff, J., Slepian, M.J., Deng, Y., Bluestein, D. "A Predictive Multiscale Model of Simulating Shear-Induced Platelet Activation," BMES Annual Fall Meeting, Minneapolis, Minnesota, October 5-8, 2016. DOI: 10.13140/RG.2.1.4904.8561 

  36. Zhang, P., Gao, C., Sheriff, J., Slepian, M.J., Deng, Y., Bluestein, D. "A Predictive Multiscale Model for Simulating Flow-Induced Platelet Activation: Correlating with In-Vitro Results," Summer Biomechanics, Bioengineering and Biotransport Conference (SB3C), National Harbor, MD, June 29-July 2, 2016. DOI: 10.13140/RG.2.1.1852.3288 [detail]

  37. Zhang, P., Gao, C., Zhang, N., Slepian, M.J., Deng, Y., Bluestein, D. "A Predictive Multiscale Model for Simulating Flow-Induced Platelet Activation: Correlating with In-Vitro Results," The 8th International Bio-Fluid Symposium, CalTech Pasadena, California, February 12-14, 2016. DOI: 10.13140/RG.2.1.2854.1205

  38. Zhang, P., Gao, C., Zhang, N., Slepian, M.J., Deng, Y., Bluestein, D. "A Predictive Multiscale Model for Simulating Platelets Activation in Shear Flows," BMES Annual Fall Meeting, Tampa, Florida, United States, October 7-10, 2015. DOI: 10.13140/RG.2.1.4723.4962

  39. Zhang, P., Gao, C., Zhang, N., Slepian, M.J., Deng, Y., Bluestein, D. "A Predictive Multiscale Model for Simulating Platelets Activation in Shear Flows," at the 2015 IMAG Multiscale Modeling (MSM) Consortium Meeting, Lister Hill Auditorium, NIH Campus, United States, September 8-9, 2015. DOI: 10.13140/RG.2.1.3412.7767

  40. Zhang, P., Gao, C., Zhang, N., Zhang, L., Pothapragada, S., Deng., Y., Bluestein, D., "Cloud Supercomputing: Multiscale Simulation Techniques and Optimization for Biomedical Research," at New York Scientific Data Summit (NYSDS), New York, NY, United States, August 2-5, 2015. DOI: 10.13140/RG.2.1.3000.3047

  41. Zhang, P., Gao, C., Zhang, N., Pothapragada, S., Slepian, M.J., Deng, Y., Bluestein, D. "Multiscale Simulation of Shear-Induced Platelet Activation: Correlating Numerical with Experimental Results," Summer Biomechanics, Bioengineering and Biotransport Conference (SB3C), Snowbird, Utah, United States, June 17-20, 2015. DOI: 10.13140/RG.2.1.4130.4168

  42. Zhang, N., Zhang, P., Zhang, L., Bluestein, D., Deng, Y. "A Multiple Time Stepping Algorithm for Efficient Multiscale Modeling of Platelets Flowing in Blood Plasma," presentation at Supercomputing Conference 2014 (SC14), New Orleans, LA, Nov. 2014.

  43. Zhang, P., Sheriff, J., Gao, C., Livelli, M., Pothapragada, S., Zhang, N., Zhang, L., Slepian, M.J., Deng, Y., Bluestein, D. "A Multiscale Particle Based Model of Platelets in Shear Flows: Correlating Numerical Simulations with In Vitro Results," BMES Annual Fall Meeting, San Antonio, Texas, October 22-25, 2014. DOI: 10.13140/2.1.1222.9128

  44. Gao, C., Zhang, P., Livelli, M., Sheriff, J., Soares, J., Pothapragada, S., Zhang, N., Deng, Y., Bluestein, D. "Multiscale Modeling of Fine-Grained Platelet Suspension in Coarse-Grained Shear Flow Using Molecular Dynamics and Dissipative Particle Dynamics," BMES Annual Fall Meeting, Seattle, WA, September 25-28, 2013. DOI: 10.13140/2.1.2009.3445

  45. Pothapragada, S., Zhang, P., Livelli, M., Sheriff, J., Deng, Y., Bluestein, D. "Multiscale Model of Shear Induced Platelet Activation and Pseudopod Formation," BMES Annual Fall Meeting, Seattle, WA, September 25-28, 2013. DOI: 10.13140/2.1.2533.6323

  46. Soares, J.S., Gao, C., Sheriff, J., Alemu, Y., Zhang, P., Pothapragada, S., Yu, G., Deng, Y., Bluestein, D. "Multiscale Modeling of Shear Induced Platelet Activation Using Dissipative Particle Dynamics and Molecular Dynamics," BMES Annual Fall Meeting, Atlanta, GA, October 24-27, 2012. DOI: 10.13140/RG.2.1.1009.2645

  47. Zhang, P., "Networking Architectures for Exascale Computing," poster presentation at Supercomputing Conference 2010 (SC'10), New Orleans, LA, Nov 15, 2010. DOI: 10.13140/RG.2.1.2057.8401

Abstracts

Awarded Patents

Patent

  1. System and Methods for Cloud-Based Interactive Graphic Editing on ECG Data. International Application Number: PCT/US21/19243; Inventors: Zhang, P. and Fang, B.

  2. Class of Interlaced Bypass Torus Networks. US Patent Application Number: US 13/773,959 (Filing Date: Feb 22, 2013); Inventors: Zhang, P. and Deng, Y.

  3. Mixed torus and hypercube multi-rank tensor expansion method, USPTO Number: US8510535 B2 (Grant Date: Aug 13, 2013), China Patent Number: ZL 200710042397.0 (Grant Date: Aug 8, 2012), Inventors: Deng, Y. and Zhang, P.

  4. Ultra-scalable supercomputer based on MPU architecture, USPTO Number: US8159973 B2 (Grant Date: Apr. 17, 2012), China Patent Number: ZL 200710044230.8 (Grant Date: Oct 13, 2010), Inventors: Deng, Y., Korobka, A. and Zhang, P.

  5. A Master Processing Unit with Self-consistent Expandable Internal and External Networks. China Patent Number: ZL 200610029753.0 (Grant Date: May 12, 2010); Inventors: Deng, Y. and Zhang, P.

  6. A Self-Consistent Multi-rank Tensor Expansion Scheme and Multi-MPU Parallel Computing Systems. China Patent Number: ZL 200610030472.7 (Grant Date: Apr 7, 2010); Inventors: Deng, Y. and Zhang, P.

  7. Routing Strategies for Cellular Networks in MPU Architectures. China Patent Number: ZL 200610117704.2 (Grant Date: Oct 28, 2009); Inventors: Zhang, P. and Deng, Y.

© 2010-2021 by Peng Zhang, Ph.D.

bottom of page