About Me

I’m a Doctoral Candidate at Purdue University, advised by Dr. Snehasis Mukhopadhyay, Computer Science @Purdue University and Dr. Shiaofen Fang, Computer Science @Indiana University.

My work lies at the intersection of multimodal AI, natural language processing, generative AI and uncertainty analysis using human in the loop techniques. I am broadly interested in developing algorithms in AI for social good applications, especially in AI for education and building robust AI systems.

The focus of my research is to derive human behavioral patterns from videos using multimodal inputs. The goal is to improve STEM retention in academia by providing instructor feedback through AI using uncertainty analysis and RLHF methods in generative AI. The pedagogical tool is modeled on the online version of peer-led team learning. I investigate key metrics in group dynamics using AI.

I’m fortunate to work on building LLM applications at Pacific Northwest National Laboratory for the Department of Energy. Last summer, I interned at IBM T.J. Watson Research Center, Yorktown Heights, NY where I worked on NLP and large language models (LLMs) for text classification applications. I also worked on a performance engineering project involving machine learning with Intel calibrations at Dell Technologies, Austin TX.

I participated as a panelist at the AI4Ed vision 2034 discussion at AAAI2024 held in Vancouver, Canada. I was a Microsoft TEALS teaching assistant during the 2022-23 academic year. It was an enriching experience to teach principles of computer science using an innovative curriculum from code.org. I was also fortunate to be selected as a Google Computer Science Research Mentee Scholar in 2022. I serve as the GradSWE affinity group lead. In my role, I initiate DEI programming to support women in STEM fields.

Contact me to know more!