Faculty

Dr. Jiaqi Gu is currently an Assistant Professor in the School of Electrical, Computer and Energy Engineering (ECEE), Arizona State University, Tempe, AZ, USA.
He is the director of the Co-design, Automation, and Optimization across System, Technology, and Intelligence Lab (ScopeX) at ASU.
[CV_JiaqiGu]

Research Interest

If you are here to seek "TL;DR"...
Multiple Research Assistant Positions Available

Academic Activities and Services

Dr. Gu received his Ph.D. degrees, under the supervision of Prof. David Z. Pan and Prof. Ray T. Chen, in Electrical and Computer Engineering from The University of Texas at Austin, Austin, TX, USA, in 2023. Dr. Gu has authored 60+ peer-reviewed international journal/conference papers in above area.

He has received Best Paper Award at ASP-DAC 2020, selected as one out of 6 Best Paper Finalists at DAC 2020, won First Place at the ACM/SIGDA Student Research Competition (SRC) held at ICCAD 2020, received the Best Poster Award at NSF Workshop on Machine Learning Hardware 2020, won First Place at the ACM Student Research Competition Grand Finals 2021, received the Best Paper Award at IEEE TCAD 2021, won the Robert S. Hilbert Memorial Optical Design Competition 2022, and won Margarida Jacome Dissertation Prize at UT Austin ECE (2023). He served as technical reviewers for over 18+ international journals/conferences, such as IEEE TCAD, TODAES, DAC, ICCAD, ISVLSI, GLVLSI, IEEE TNNLS, NeurIPS, CVPR, ICCV, ECCV, AAAI, IROS, Nature Communications, Science Advances, IEEE JSTQE, APL, IEEE PTL, etc. He also served as the Technical Program Committee member of ICCAD, ICCD, etc.

News

[Jan 2024]
  • Our recent work, M3ICRO: Machine Learning-Enabled Compact Photonic Tensor Core based on PRogrammable Multi-Operand Multimode Interference, is accepted by APL Machine Learning 2024. Cheers! [MO-MMI, APL ML 2024]
[Dec 2023]
  • Our recent work, Integrated Multi-Operand Optical Neurons for Scalable and Hardware-Efficient Deep Learning, is accepted by Nanophotonics 2023. Cheers! [MO-MZI, Nanophotonics 2023]
[Oct 2023]
  • Our recent work, Lightening-Transformer: A Dynamically-operated Optically-interconnected Photonic Transformer Accelerator, is accepted by HPCA 2024. Cheers! [DOTA, HPCA 2024]
[Sep 2023]
  • Our recent work, Pre-RMSNorm and Pre-CRMSNorm Transformers: Equivalent and Efficient Pre-LN Transformers, is accepted by NeurIPS 2023 and selected as Spotlight paper. Cheers! [PRE-RMSNorm, NeurIPS 2023]
  • Our recent work, Domain-Specific Optimization for Quantized Optical AI Computing Systems, is accepted by ICCV LBQNN workshop 2023. Cheers!
[Jun 2023]