Xiaofan Yu

Xiaofan Yu is an Assistant Professor in the Department of Electrical Engineering at the University of California, Merced. He holds a Ph.D. (2025), M.S. (2020), and B.S. (2018) from the University of California, San Diego and Peking University, respectively. His research focuses on embedded systems, edge AI, and neuromorphic computing, with applications in IoT, federated learning, and hyperdimensional computing.

• ML&Systems Rising Star (2024)
• CPS Rising Star (2023)
• EECS Rising Star (2022)

His work addresses on-device AI for real-world IoT deployments, reliability-driven sensor networks, and next-generation edge intelligence. Recent publications highlight advancements in federated learning (TIOT 2025), multimodal sensor interaction (IMWUT 2025), and noise-resilient sensor systems (Sensors 2024). Key subfields include hyperdimensional computing, asynchronous distributed training, and resource-efficient edge models.

Dr. Yu actively mentors students across institutions and programs, including the Early Research Scholarship Program (UCSD) and ENLACE Summer Research Program. He has advised projects on smart elderly monitoring, LLM-based sensor reasoning, and hyperdimensional algorithm optimization. Collaborations span UCSD, TUM, and Stanford, with industry partnerships in IoT design automation (RelIoT simulator) and biomedical applications (bladder fullness restoration system).