Yibo Huang

Yibo Huang is a Research Fellow at the Department of Computer Science and Engineering (CSE), University of Michigan, working with Prof. Ang Chen. His research focuses on systems, networking, and security, emphasizing hardware-software co-design and ML-driven optimization. He holds a Ph.D. in Computer Science from Fudan University (2021), where he co-advised students under Prof. Jie Wu and Prof. Yang Xu. Notable contributions include the CoNEXT 2022 Best Paper Award and Usenix Security 2023 Distinguished Paper Award for innovations in low-latency interconnects and cloud security.

Education: Ph.D. in Computer Science (Fudan University, 2021), B.S. in Software Engineering (Central South University, 2016). Industrial experience includes roles at Bytedance (2020–2022) developing RDMA systems and internships at Intel (2015–2016). Academic service includes roles on program committees for EuroSys, FAST, OSDI, and USENIX Security.

Research interests span cloud management (e.g., Cloudless Computing), RDMA-based systems (e.g., Exposing RDMA NIC Resources), and AI-driven experimentation frameworks (e.g., EXP-Bench and Curie). His work bridges theoretical advancements with practical applications in high-performance computing and edge-cloud environments.

Key awards include the Distinguished RDMA Programming Instructor (2022), Intel PhD Fellowship (2020), and multiple APAC RDMA Programming Competition prizes. His lab collaborations include projects on disaggregated recommendation systems (FlexEMR) and persistent memory optimization (PFtree).

Labs/Teams: Active in the University of Michigan’s CSE division, collaborating with Prof. Ang Chen’s group, and previously part of Fudan University’s Starry Team (focusing on RDMA-enhanced distributed systems).