Vinith Suriyakumar

I am a fourth year PhD student at MIT EECS where I am advised by Dr. Ashia Wilson and Dr. Marzyeh Ghassemi. I also collaborate frequently with Dr. Dylan Hadfield-Menell. My research focuses on uncovering and addressing privacy, security, and safety risks in machine learning. Currently, my efforts are focused on foundation models (e.g. LLMs, diffusion models, and multimodal models). Examples of specific topics include: unlearning, backdoors, adversarial attacks, differential privacy, and copyright. Feel free to reach out if you are interested in chatting about or collaborating on any of these areas!

Previously in my PhD, I worked on algorithmic fairness, the role of race in medicine, health inequities in maternal health, and applications to organ procurement processes. I completed my Masters in May 2021 at the University of Toronto & Vector Institute advised by Dr. Marzyeh Ghassemi, Dr. Nicolas Papernot, Dr. Berk Ustun, and Dr. Anna Goldenberg. My thesis was focused on differential privacy and algorithmic fairness in machine learning for healthcare.

UROP & M.Eng Advising: My next availability for advising UROPs and M.Eng students is Fall 2025. I advise students interested in working on questions in my direct research areas as described above. I typically advise one student per academic year.