I am an incoming post-doctoral fellow at Stanford University. I completed my Ph.D. in the Electrical and Computer Engineering (ECE) Department from University of California, Santa Barbara (UCSB). My research interest is at the intersection of computer vision, pattern recognition, graph theory, and computational geometry. My PhD research takes a principled approach to mathematically model the white matter pathways in the human brain and analyze crucial topological information. A central focus in my research is to build on and apply theoretical tools from computational geometry along with machine learning to mitigate the complexity of brain imaging data. My Ph.D. research has earned me the Lancaster Dissertation award 2024, UCSB’s highest honor for PhD dissertations completed within a 2-year period covering all areas of engineering, physical sciences, and mathematics. I have been honored as an NSF iRedefine fellow 2023 for my leadership and research potential from the ECE Department Heads Association. Throughout my Ph.D., I have enjoyed teaching and mentorship as much as research. I have been awarded the Fiona and Michael Goodchild best graduate student mentor award for my impactful undergraduate mentorship.

In 2018, I graduated with a bachelors degree from the Indian Institute of Technoloy (IIT) Kharagpur, India. My Bachelor of Technology degree is from the Electrical Engineering department.