UT Austin’s student chapter of SIAM was founded in 2008 to foster interactions between members of the applied mathematics community at UT Austin, across departments, institutes, and professional marks. We aim to provide a forum for discussing applied and computational mathematics and to help members prepare for future STEM careers in academia and industry. We also promote publications, conferences, prizes, and other opportunities offered by SIAM.
I use numerical simulations to study diverse fluid flow problems in planetary sciences such as impact crater lake dynamics on Mars, melting of ice on glaciers and formation of planetary cores.
I work broadly on machine learning methods for community detection in networks using known information. I’m interested in supervised and reinforcement learning methods and the application area of finding protein complexes in human protein interaction networks - which will help us better understand cellular function and mechanisms of disease.
I am interested in mathematics applied to various engineering fields and machine learning.
I work on the optimal experimental design of magnetic resonance imaging using techniques from optimal control and reinforcement learning.
I work on understanding the impacts of numerical discretization on the Large Eddy Simulation of turbulent flows and the development of turbulence models capable of representing the correct statistical characteristics of the flow in the presence of such numerical issues. This research has been applied to a range of turbulence applications from channel flow to flow through a wind turbine.