My current research interests are: 1) Sequential Recommender Systems: Creating efficient foundation models, 2)Improving Computing education to prepare a workforce for the future 3) Time Series Forecasting for financial data.
My work experience includes working at EY as a Senior Data Scientist with my project focused on credit and risk analytics. My dissertation research finds direct application in online retail and
subscription entertainment platforms like Amazon and Netflix. My dissertation work is at the intersection of four fields: (1) online recommender systems (2) consumer choice models, (3) supply chain models, and (4) assortment planning. My thesis includes an in-depth, iterative and methodical exploration of some of the very Big-Datasets available for consumer preference ratings.
I conceptualized and built a peer-to-peer tutoring platform (from scratch) for facilitating better usage of resources on campus and improving learning experience for students. This platform (Instantutor: http://www.instantutorrpi.com/) uses a two-step algorithm to create a content-based filtering recommender system and an NLP (Natural Language processing) approach to better match tutors with student requests.