Lizhong Chen

Lizhong Chen is a Professor in the School of Electrical Engineering and Computer Science at Oregon State University and a core AI faculty member in the Collaborative Robotics and Intelligent Systems (CoRIS) Institute. He leads the STAR Lab which focuses on computing systems and AI applications with emphasis on computing efficiency across various computing platforms from embedded devices to supercomputers.

• Ph.D., Computer Engineering, University of Southern California, 2014
• M.S., Electrical Engineering, University of Southern California, 2011
• B.S., Electrical Engineering, Zhejiang University, 2009

Chen's research focuses on efficient computer systems (GPUs, accelerators, HPCs, IoT devices) and their applications in machine learning and natural language processing, especially large language models. His work spans machine learning accelerators, GPU architecture, AI-assisted design for computer architecture, and energy-efficient computing systems. He has made significant contributions to NoC (Network-on-Chip) power-gating research and developed the Agate simulator for simulating NoC power-gating.

His recent publications (2023-2025) show a strong focus on large language models, particularly for simultaneous translation tasks, Kolmogorov-Arnold networks, and efficient model architectures. His work bridges computer architecture design with AI applications, creating synergies between hardware efficiency and machine learning performance.

Scientific Awards:

• NSF CRII Award (2016)
• NSF CAREER Award (2018)
• Best Paper Nomination at IEEE NAS (2018)
• Best Paper Runner-up Award at HPCA (2020)
• Chu Kochen Award from Zhejiang University
• IEEE HPCA Hall of Fame (2020)

Chen has served as an Associate Editor of IEEE Transactions on Computers and as program committee member for top computer system and machine learning conferences. He is the founder and organizer of the Annual International Workshop on AIDArc (AI-assisted Design for Architecture). His research is supported by multiple grants from NSF, NIH, Department of Energy, and the Northwest-AI-Hub supported by the CHIPS and Science Act. He teaches courses in computer architecture, high-performance computing, and specialized topics in AI accelerators and GPU architecture.

As director of the STAR Lab, Chen leads research on computing efficiency across the spectrum from embedded and mobile devices to supercomputers and data centers. The lab's recent focuses include machine learning accelerators, GPU architecture, applications of AI in architecture designs, and improving the computing efficiency of machine learning and natural language processing models.