About me

I am currently working as Research Impacts Data Analyst at Institute for Interdisciplinary Data Sciences, University of Idaho. In this role, my primary objective is to empower the university administration to make well-informed decisions by effectively analyzing and leveraging diverse research data generated across the institution. Key responsibilities encompass developing robust systems and tools to manage and analyze research-related information, including grants, awards, and publications. I actively collaborate with various departments to enhance their data quality and improve data interoperability, ensuring the availability of comprehensive and up-to-date research insights. Utilizing my expertise in data analytics, I create visually appealing and intuitive data visualization dashboards that provide actionable insights for university stakeholders. I develop AI and large language model(LLM) powered tools to streamline workflow of different processes across the university.

Before joining my current job at the University of Idaho I completed my PhD in Mathematics at Texas A&M University with my primary research area lying in Geometric Complexity Theory, under the supervision of Prof Joseph M Landsberg.

As a PhD in Mathematics with a focus in Theoretical Computer Science and Complexity Theory, I have worked on the problems surrounding the exponent of matrix multiplication. My research explores the area of minimal border rank tensors, which play a crucial role in achieving the state-of-the-art bound for the exponent of matrix multiplication using Coppersmith-Winograd tensor. My research focuses on studying the geometric properties of these tensors and their applications in fields such as Phylogenetics and Algebraic Statistics. I have also worked on problems related to Algebraic Statistics and Convolution Neural Networks, and have a deep understanding of Algebraic Geometry, Representation Theory, Lie Algebras, Deep Learning, and Statistics.