About Me

I am a fifth-year PhD student at UCSD, advised by Kamalika Chaudhuri. My primary focus is differential privacy, where I am intrigued by questions like how to define privacy for graphs and how to improve the performance of private graph algorithms. I am also interested in the connections between information theory and privacy, such as strong composition and privacy-utility bounds.

I am becoming more interested in theoretical aspests of trustworthy machine learning/statistics, such as how to take a well-known problem like clustering and design algorithm which are private, robust, resistant to data poisoning, etc.

Outside of work, I enjoy playing sports, cooking, surfing, reading, and spending time outdoors.