I am an interim Postdoctoral Scholar in the Computer Science Department at the University of California, Davis, working with Prof. Prasant Mohapatra. Prior to this, I received my PhD in Computer Science from UC Davis in September 2023, also advised by Prof. Mohapatra. My research primarily focuses on improving Machine Learning (ML) and Artificial Intelligence (AI) models to further facilitate their adoption into society by analyzing and improving model security, robustness, and fairness. I also work to translate these ideas to impact real-world models deployed in production systems, which by default are closed-source. Previously, I have also worked on developing ML approaches for improving networked systems.
1/16/2024: Our paper "What Data Benefits My Classifier? Enhancing Model Performance and Interpretability Through Influence-Based Data Selection" was accepted as an oral talk (top 1.2% of papers) at ICLR 2024 [pdf] [code]
12/1/2023: Invited to attend a research convening on LLMs and social media interventions at Google NYC organized by Google/Jigsaw and Prosocial Design Network [blog post]
10/15/2022: I was invited to give a seminar talk on Robust Clustering at Brandeis University, Boston by Prof. Hongfu Liu
9/17/2021: Our survey paper on fairness in clustering was accepted for publication in IEEE Access [pdf]
1/25/2019: Invited to talk about our research on adversarial attacks against clustering at Uber AI in SF by Ryan Turner