August 4, 2020
Bradley J. Nelson, William H. Kruskal Instructor
Brad Nelson received a Ph.D. in Computational and Applied Mathematics from Stanford University, on a National Defense Science and Engineering Graduate Fellowship in 2020. His research area is in an emerging discipline of applied mathematics now widely called topological data analysis (TDA). In his PhD work, he developed several new methodologies in TDA, established new connections with current machine learning techniques, and created new software to realize his algorithmic ideas.
Zhongjian Wang, William H. Kruskal Instructor
Zhongjian Wang received a Ph.D. in Mathematics from the University of Hong Kong in 2020. His main area of expertise is the numerical simulation of stochastic differential equations. He developed numerical schemes that preserved important structures of the underlying model, allowing for long term integrations that do not suffer from usual exponential instabilities. His research interests also include the numerical simulation of partial differential equations by means of neural-network-type minimizations.
Ben Palacios, William H. Kruskal Instructor
Ben Palacios received a Ph.D. in Mathematics from University of Washington in 2018. He was most recently a post-doctoral scholar at the University of Chicago, Department of Statistics. He most recently worked on the derivation of Fermi pencil beam approximations to radiative transport and Fokker-Planck equations. This finds applications in the propagation of light in turbulent atmospheres or more general turbid media.
