Our research is focused on modeling, analysis, simulation and software, applied to multiscale, networked systems in biology, materials and social networks. My group has been developing advanced algorithms for discrete stochastic simulation of systems where the fate of a few key molecules can make a big difference to important outcomes. We engage with experimentalists through the analysis of data and the development of mathematical models that yield insight and offer new directions for research. Current collaborations range from biology (circadian rhythm [jet lag] and cell polarization), to medicine (coagulopathy and post-traumatic stress disorder), to ecology (chytrid disease in frogs), to social networks (sentiment analysis and opinion dynamics), to materials. We are collaborating with Prof. Chandra Krintz on the development of an integrated, cloud-based environment called Stochastic Simulation Service (StochSS) for modeling and simulation of biological processes.

Announcements & News

St. Elmo Wilken was awarded the Dow Discovery Fellowship by the Chemical Engineering Department at UCSB. The Fellows are selected by the Chemical Engineering faculty as a whole; only two outstanding... Read more
StochSS: Stochastic Simulation Service is an integrated development environment for modeling and simulation of discrete stochastic biochemical systems. An easy-to-use GUI enables researchers to... Read more
StochSS: Stochastic Simulation Service, is an integrated development environment for modeling and simulation of discrete stochastic biochemical systems.  An easy to use GUI enables researchers to... Read more
Kasturi and Yuanyang successfully defended their Ph.D. theses this summer, and immediately started working in industry. Kasturi is employed at Target Corp., Sunnyvale, California as a data analyst ... Read more
StochSS: Stochastic Simulation Service, is an integrated development environment for modeling and simulation of discrete stochastic biochemical systems.  An easy to use GUI enables researchers to... Read more

Recent Publications

1.5017840.pdf Bales, B., Petzold, L., Goodlet, B. R., Lenthe, W. C., & Pollock, T. M. (2018). Bayesian Inference of Elastic Properties with Resonant Ultrasound Spectroscopy. J. Acoust. Soc. Am., 143, pp. 71-83
10.10072fs10439-018-2031-9.pdf Wu, T. B., Wu, S., Buoni, M., Orfeo, T., Brummel-Ziedins, K., Cohen, M., & Petzold, L. (2018). Computational Model for Hyperfibrinolytic Onset of Acute Traumatic Coagulopathy. Ann. Biomed. Eng. pp. 1-10
mitchell_et_al-2018-scientific_reports.pdf Mitchell, B. A. & Petzold, L. R. (2018). Control of Neural Systems at Multiple Scales Using Model-free, Deep Reinforcement Learning. Scientific Reports 8:10721
10.1007-s11661-018-4575-6.pdf Goodlet, B. R., Mills, L., Bales, B., Charpagne, M-A, Murray, S. P., Lenthe, W. C., Petzold, L., & Pollock, T.M. (2018). Elastic Properties of Novel Co- and CoNi-Based Superalloys Determined through Bayesian Inference and Resonant Ultrasound Spectroscopy. Metall. and Mat. Trans. A
stancon_alzheimers.pdf Pourzanjani, A. A., Bales, B. B., Harrington, M., & Petzold, L. R. (2018). Flexible Modeling of Alzheimer's Disease Progression with I-Splines. StanCon 2018 Proceedings.