We focus on mathematical modeling and machine learning, applied to networked systems in biology and medicine.Current projects include development of algorithms and software for both simulation and inference of discrete stochastic systems, uses of machine learning applied to medical data to improve the care of trauma patients, mathematical modeling of brain processes in migraine, unraveling neural communication in learning, inference of network structure of communities of neurons, and mathematical modeling of the process of cell polarization.
Announcements & News
Our proposal "Fluctuating sodium in the nervous system as the root cause of fluctuating brain function", in collaboration with Dr. Michael Harrington of Huntington Medical Research Institutes in... Read more
At the end of Fall '19, Brian successfully defended his PhD thesis in Computer Science. After graduation, Brian started his career at Madrona Venture Group in Seattle, WA. Congratulations, Brian!
On November 22, 2019, Professor Petzold was invited to UCLA's Institute for Quantitative and Computational Biosciences where she gave a seminar titled "Cell Polarization and Growth in Yeast Mating... Read more
At the beginning of Fall '19, we welcomed Dengxian (Dara) Yang to the CSE Research Group.
At the end of August, Tie Bo defended his PhD thesis in Mechanical Engineering. Congratulations, Tie!
Recent Publications
 mea_dl.pdf |
Zhao, Y., Guzman, E., Audouard, M., Cheng, Z., Hansma, P. K., Kosik, K. S., & Petzold, L. (2019). A Deep Learning Framework for Classification of in vitro Multi-Electrode Array Recordings. Proceedings of the 2019 International Conference on Data Mining | |
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hybrid_sdpd_and_ssa.pdf |
Drawert, B., Jacob, B., Li, Z., Yi, T-M, & Petzold, L. (2019). A Hybrid Smoothed Dissipative Particle Dynamics (SDPD) Spatial Stochastic Simulation Algorithm (sSSA) for Advection-Diffusion-Reaction Problems. J. Comp. Phys. 378, pp. 1-17. | |
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neco_a_01219.pdf |
Mitchell, B. A., Lauharatanahirun, N., Garcia, J. O., Wymbs, N., Grafton, S., Vettel, J. M., & Petzold, L. R. (2019). A Minimum Free Energy Model of Motor Learning. Neural Computation 32, 1945-1963 | |
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s12976-019-0099-z.pdf |
Ghaffari, H., Varner, J. D., & Petzold, L. R. (2019). Analysis of the Role of Thrombomodulin in All-trans Retinoic Acid Treatment of Coagulation Disorders in Cancer Patients. Theoretical Biology and Medical Modelling 16(1):3 | |
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journal.pbio_.3000453-2.pdf |
Jang, J., Han, D., Golkaram, M., Audouard, M., Liu, G., Bridges, D., Hellander, S., Chialastri, A., Dey, S. S., Petzold, L. R., & Kosik, K. S. (2019). Control over single-cell distribution of G1 lengths by WNT governs pluripotency. PLoS Biol 17(9): e3000453. |