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

Professor Petzold was elected to the National Academy of Sciences. This year she was one of 120 members elected and one of the 59 women elected, the most elected in a single year. Membership in the... Read more
Professor Petzold has been elected as Fellow of the American Institute for Medical and Biological Engineers (AIMBE). Later this month, Professor Petzold will be inducted as an AIMBE Fellow in a... Read more
On March 5, 2020, Yun successfully passed his preliminary exam!
At the end of Winter '20, Hamed successfully defended his PhD thesis in Mechanical Engineering. Hamed will be joining Gilead Sciences in Foster City, California. Congratulations, Hamed!
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

Recent Publications

bertsurv-bert_based_survival_models_for_predicting_outcomes_for_trauma_patients.pdf Zhao, Y., Hong, Q., Zhang, X., Deng, Y., Wang, Y., & Petzold, L. (2021). BERTSurv: BERT based Survival Models for Predicting Outcomes for Trauma Patients. To Appear, ICDM 2021.
2020.05.21.108076v1.full_.pdf Banavar, S. P., Trogdon, M., Drawert, B., Yi, T-M, Petzold, L. R., & Campas, O. (2021). Coordinating Cell Polarization and Morphogenesis Through Mechanical Feedback. To appear PLOS Computational Biology
ml_mof.pdf Wang, Y.*, Zhao, Y.*, Callcut, R., & Petzold, L. (2021). Empirical Analysis of Machine Learning Configurations for Prediction of Multiple Organ Failure in Trauma Patients. To Appear, ICDM 2021.
btab061.pdf Jiang, R., Jacob, B., Geiger, M., Matthew, S., Rumsey, B., Singh, P., Wrede, F., Yi, T-M, Drawert, B., Hellander, A., & Petzold, L. (2021). Epidemiological modeling in StochSS Live!. Bioinformatics, 2021, 1-2.
journal.pone_.0233640.pdf Wu, T. B., Orfeo, T. Moore, H. B., Sumislawski, J. J., Cohen, M. J., & Petzold, L. R. (2020). Computational Model of Tranexamic Acid on Urokinase Mediated Fibrinolysis. PLoS ONE 15(5):e0233640