Research

My Research Overview

I have two primary research areas. The first is focused on physics-guided computational modeling, which encompasses topics such as fluid-structure interaction, graph neural networks, physics-informed machine learning, and equation-free data-driven methods. The second area involves the development of mathematical models for cancer immunology, with a specific emphasis on CART cell therapy. You can access most of my latest works in my Github. 

I am the Spelman PI of  MOLUcQ(Uncertainty Quantification for Multifidelity Operator Learning) and Co-PI of SEA-CROGS projects funded by Department of Energy.

Research Projects

Recent Workshops and Panels

(CDS&E-MSS) Review Panel,  2022

Undergraduate Research
Below is a compilation of undergraduate students I have previously advised, as well as those I am currently mentoring.

Recent Talks