Zishen Wan

Zishen Wan is an Assistant Professor of Computer Science at Columbia University, where he leads the Wan Lab. His research spans computer architecture, systems, and VLSI design, with a focus on efficient and reliable computing for emerging AI applications.

His group pursues two complementary directions: computing for AI and AI for computing. He co-designs software systems, hardware architectures, and silicon for physical and embodied AI, neuro-symbolic reasoning, and autonomous agents. He also develops agentic AI methods for the design, optimization, and verification of computing systems, from software and computer architectures to accelerators and chips. Across both directions, his work uses cross-layer co-design to improve efficiency, scalability, reliability, and adaptability.

Before joining Columbia, Wan was a postdoctoral fellow at Harvard University. He received his Ph.D. from the Georgia Institute of Technology in 2025.

His research has been recognized with the Best Paper Awards from DAC, IEEE Computer Architecture Letters, and SRC JUMP 2.0, as well as IEEE Micro Top Picks and ACM SIGDA Research Highlights. His Ph.D. dissertation received ACM SIGDA Outstanding Ph.D. Dissertation Award, ACM FCCM Outstanding Ph.D. Dissertation Award, and Georgia Tech's Colonel Oscar P. Cleaver Award. He was also awarded first place at DAC Ph.D. Forum and ACM Student Research Competition, and selected as ML and Systems Rising Star.