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 apply Automatic Differentiation tools and techniques for PDE-constrained Inverse Problems in order to calibrate large ice sheet models. I also study the applications of Deep Learning in order to reduce the cost of the computational complexity of the dynamics of sea ice models.
I use optimization and machine learning techniques for process control and energy system. The current focus of my research is production scheduling optimization for fluctuating electricity prices and energy supplies.
I work on the optimal experimental design of magnetic resonance imaging using techniques from optimal control and reinforcement learning.
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 an undergraduate Mathematics Senior with an interest in applied mathematics, data science and urban analytics.