Trung (Average) Phan,
Assistant Professor at the Department of Natural Science, Pitzer & Scripps colleges
Personal Website: https://trungphan.squarespace.com
Biography
Dr. Phan earned his Ph.D. in Physics from Princeton University. Since then, he has explored many areas of science, working in biology at Yale University, in machine learning at Johns Hopkins University, and on cancer chemotherapeutic treatments with clinicians at the Johns Hopkins Medical Institute. Now at Claremont, he wants to focus more on teaching while pursuing research on bacteria and robotics (and more).
Alongside his academic career, Dr. Phan coaches the Vietnamese national teams for the Asian and International Physics Olympiads (APhO and IPhO). He remains committed to supporting the next generation of scientists in his home country, through outreach and collaborations.
Alongside his academic career, Dr. Phan coaches the Vietnamese national teams for the Asian and International Physics Olympiads (APhO and IPhO). He remains committed to supporting the next generation of scientists in his home country, through outreach and collaborations.
Academic History
- (2011-2015) B.S.; Massachussetts Institute of Technology
- (2015-2021) Ph.D.; Princeton University
- (2021-2023) Postdoc; Yale University
- (2023-2025) Postdoc; Johns Hopkins University
Interests
Biophysics, Robophysics, Machine Learning, Cancer Chemotherapy, Soft/Condensed Matter Physics, Stochastic Thermodynamics, Classical Physics, Partial Differential Equation, and more
Selected Research and Publications
Here is some of my notable work and their media coverage:
Phan, T. V., Morris, R., Black, M. E., Do, T. K., Lin, K. C., Nagy, K., Sturm, J. C., Bos, J., & Austin, R. H. (2020). “Bacterial Route Finding and Collective Escape in Mazes and Fractals.” Physical Review X, 10(3), 031017. Wired Magazine: “These Bacteria Ate Their Way Through a Really Tricky Maze” https://www.wired.com/story/these-bacteria-ate-their-way-through-a-really-tricky-maze/
Wang, G.*, Phan, T. V.*, Li, S., Wang, J., Peng, Y., Chen, G., Goldman, D. I., Levin, S. A., Pienta, K., Amend, S., Austin, R. H., & Liu, L. (2022). “Robots as Models of Evolving Systems.” Proceedings of the National Academy of Sciences, 119(12), e2120019119. [*co-first authors]. Physics Today: “Evolving robots could optimize chemotherapy” https://pubs.aip.org/physicstoday/Online/4906/Evolving-robots-could-optimize-chemotherapy PNAS Commentary: “Let the robotic game begin” https://www.pnas.org/doi/10.1073/pnas.2204152119
Guo, B.*, Ro, S.*, Shih, A., Phan, T. V., Austin, R. H., Martiniani, S., Levine, D., & Chaikin, P. M. (2022). “Model-free measurement of local entropy production and extractable work in active matter.” Phys. Rev. Lett. 129, 220601. [*co-first authors]. The cover picture of Physical Review Letter Volume 129 Issue 22: https://journals.aps.org/prl/issues/129/22/