Hi! I'm Suyu (Michael) Ye, a Sophomore at Johns Hopkins University, advised by Professor Tianmin Shu. I'm double majoring in Computer Science and Applied Maths and Statistics, supported by a National Merit Scholarship.

My research interests are Human-Computer Interaction (HCI), multi-modal learning, and multi-agent systems. I'm particularly interested in studying human behaviors to build AI systems that interact naturally, understand complex social and multi-modal contexts, and collaborate effectively with people. My goal is to develop safe and reliable AI systems that enhance daily life.

News

• [Aug 2025] - RealWebAssist preprint available on arXiv
• [Jan 2025] – MuMA-ToM accepted to AAAI 2025 as an Oral Presentation
• [Sept 2024] – Assessing the limitations of relief based algorithms in detecting higher order interactions published on BioData Mining
• [Oct 2024] – MuMA-ToM accepted to NeurIPS 2024 Video Language Workshop.
• [Oct 2024] – MuMA-ToM accepted to NeurIPS 2024 Behavioral ML workshop.

Publications

MuMA-ToM: Multi-modal Multi-Agent Theory of Mind

Haojun Shi*, Suyu Ye*, Xinyu Fang, Chuanyang Jin, Leyla Isik, Yen-Ling Kuo, Tianmin Shu (*equal contribution)
AAAI 2025 (Oral)
Paper | Website | Code

Assessing the limitations of relief-based algorithms in detecting higher-order interactions

Philip J. Freda, Suyu Ye, Robert Zhang, Jason H. Moore, Ryan J. Urbanowicz
BioData Mining
Paper

RealWebAssist: A Benchmark for Long-Horizon Web Assistance with Real-World Users

Suyu Ye*, Haojun Shi*, Darren Shih, Hyokun Yun, Tanya Roosta, Tianmin Shu (*equal contribution)
arXiv preprint
Paper | Website | Code