me | papers | teaching | farming | grad apps
I am a fourth year PhD candidate at UC Davis with the advising of Prasant Mohapatra at the Networks lab. My research lies in the domain of private machine learning.
I interned at Intel for the 2023 calendar year as a Core-OS intern working on memory access tracking. In fall 2021, at Garrett Motion exploring EV charging protocols. In the summer of 2020, I interned with Sean Peisert at Berkeley Lab working on privacy preserving Machine learning. My grad journey has allowed me to identify flaws that affect my work ethic and ask the right questions before trying to cut off a thread with a scissor than an axe.
I researched edge computing paradigms during my undergrad with Sudeep Tanwar at Nirma, focusing on body area networks. During internships, I worked on a pregnancy chatbot, gait analyzing and stroke detection using facial recognition.
I was a core participant and a Graduate Research Fellow at IPAM, UCLA for the long program on Mathematical Challenges and Opportunities for Autonomous Vehicles, where I was a part of the working group focusing on Perception, Control and Safety of Machine Learning for AVs.
I am actively learning more about ML fairness and privacy at the moment!