معرفی
Geng Yuan is an Assistant Professor at the University of Georgia's School of Computing, specializing in AI systems, energy-efficient deep learning, and hardware-software co-design. His work bridges machine learning algorithms with emerging hardware technologies like superconducting circuits and ReRAM. He holds a Ph.D. in Computer Engineering from Northeastern University (2023) and a Master's in Electrical & Computer Engineering from Syracuse University (2016).
- Doctor of Philosophy (Ph.D.) in Computer Engineering, Northeastern University (2023)
- Master of Science (M.S.) in Electrical & Computer Engineering, Syracuse University (2016)
- Bachelor of Science (B.S.) in Electrical Engineering, Beijing University of Technology (2014)
His research focuses on optimizing deep learning systems for edge computing and mobile platforms through techniques like model compression, sparse training, and hardware-aware neural architecture search. Recent projects include adapting large language models via hybrid-grained pruning and developing ultra-low-power AQFP circuits for binary networks.
Geng Yuan's publications span top venues like NeurIPS, CVPR, ICML, ICLR, ISCA, and DAC, with notable awards including a Best Paper Award at ICLR Workshop 2021, Spotlight Papers at ICLR 2023 and NeurIPS 2021, and a Design Contest 1st Place at ISLPED 2020.
- Best Paper Award (ICLR Workshop'21)
- Spotlight Paper Award (ICLR'23, NeurIPS'21)
- Design Contest 1st Place (ISLPED'20)
- Best Paper Nomination (DATE'21, ISQED'18)
He actively recruits Ph.D., Master's students, and interns to his research group, focusing on advancing AI systems through interdisciplinary approaches combining machine learning, computer architecture, and electronic design automation.
