Vinith Suriyakumar

I am a fifth year PhD student at MIT EECS where I am advised by Dr. Ashia Wilson and Dr. Marzyeh Ghassemi. I’m supported through a fellowship from Bridgewater AIA Labs advised by Dr. Daniel Kang where I research LLM pretraining and post-training. Additionally, I’ll be joining the Red Team at UK AISI in the Fall as a Research Resident.

Broadly, I’m interested in the privacy, security, and safety of machine learning. I’ve worked on many topics in these areas including differential privacy, auditing, algorithmic fairness, and unlearning.

My research focuses on securing internet platforms against malicious behavior enabled by generative AI systems. I am particularly interested in the safety, security, and governance of open-weight foundation models, with recent work focusing on image-based abuse such as CSAM and NCII generation. Additionally, I focus on addressing safety issues related to cyber misuse, investigating new pretraining algorithms to address dual-use risks. I also investigate security challenges in closed-source systems, including jailbreaking and secure fine-tuning interfaces.

My research advancing the privacy, security and safety of machine learning has received awards at NeurIPS, ICLR, ICML, and FAccT:

• ICML 2022 Spotlight
• ICML 2023 Oral
• ICLR 2024 Oral
• FAccT 2024 Best Paper Award
• NeurIPS 2025 Spotlight
• ICML 2026 AI4Good Spotlight