I’m a PhD student in EECS at MIT, where I started in fall 2024 and am very fortunate to be advised by Prof Srini Devadas.
I am passionate about the security and privacy of machine learning. I aim to design principled algorithms to enable trustworthy machine learning with provable privacy and security guarantees.
Prior to MIT, I graduated with bachelor’s degrees in computer science and mathematics from National University of Singapore (NUS) in 2023, where I was advised by Prof Xiaokui Xiao and Prof Vincent Tan.
I have also gained industry experience via internships at NVIDIA (summer 2026), Apple (summer 2025), and TikTok (summer 2021).
Outside of research, I enjoy cooking, biking, music, films, and photography.
*My name can be pronounced probably approximately correctly as Shee-aw Chen Joo.
News
Sep 2026PACZero, on PAC-private fine-tuning of language models, was accepted to NeurIPS 2026.
Aug 2026Received the MIT Schwarzman College of Computing PhD Fellowship.
May 2026Started a summer internship at NVIDIA in the Security and Privacy Research group.
PPMLVecDBSpeakeasy: Billion-Scale Two-Server Private Semantic SearchVihan Lakshman*α, Xiaochen Zhu*α, Alexandra Henzinger, Henry Corrigan-Gibbs, Emma DautermanProceedings of the Privacy-Preserving Machine Learning Workshop (PPML@CRYPTO), 2026Proceedings of the Workshop on Vector Databases (VecDB@VLDB), 2026
