Chen Zhang / 张宸

Chen Zhang / 张宸

Assistant Professor, 博导

张宸 - 上海交通大学

Biography

I joined the School of Electronic Information and Electrical Engineering at Shanghai Jiao Tong University in May 2023 as a Tenure-Track Assistant Professor and Ph.D. advisor. I am also a recipient of the Shanghai Overseas High-Level Talent Program. My research focuses on AI processor architectures and chip systems.

I received my Ph.D. from Peking University in 2017, under the supervision of Prof. Jason Cong and Prof. Guangyu Sun. From 2015 to 2016, I conducted academic research as a visiting scholar at the University of California, Los Angeles (UCLA). After graduation, I worked at Microsoft Research (as a Senior Researcher) and later at Alibaba T-Head Semiconductor (as a core member of the chief architect team), where I led the development of several high-impact AI processors and systems both in China and internationally.

I have published over 30 papers in top-tier conferences and journals, including ISCA, MICRO, FPGA, DAC, and IEEE TCAD, receiving 5 Best Paper Awards or nominations (FPGA’15, TCAD’19, MICRO’22, ISEDA’25, ISCA’25). My work has been cited over 5,200 times on Google Scholar, with a single paper cited more than 2,600 times. I have been honored as a member of the FPGA and Reconfigurable Computing Hall of Fame, named an AI 2000 Most Influential Scholar in the World, recognized as a Top 2% Most-Cited Researcher by Stanford and Elsevier, and received the ACM ChinaSys Rising Star Award, among other accolades.

News

  • [2025 June] “H^2-LLM: Hardware-Dataflow Co-Exploration for Heterogeneous Hybrid-Bonding-based Low-Batch LLM Inference” (ISCA-2025) wins Best Paper Award!
  • [2025 May.] “DATIS: DRAM Architecture and Technology Integrated Simulation” (ISEDA-2025) wins Best Paper Award!【Details】
  • [2025 Mar.] “Optimizing FPGA-based accelerator design for deep convolutional neural networks” is inducted into the Class of 2025 FPGA and Reconfigurable Computing Hall of Fame！【UCLA News，SIC News，SJTU News，SJTU News】
  • [2022 Oct.] I am honored with ChinaSys Rising Star Award. 【ChinaSys Web】
  • [2019 Jan.] “Caffeine: Toward uniformed representation and acceleration for deep convolutional neural networks” published on T-CAD 2018 has win Donald O. Pederson Best Paper! 【UCLA News，PKU News】

Selected Publications（Full List）

  • H^2-LLM: Hardware-Dataflow Co-Exploration for Heterogeneous Hybrid-Bonding-based Low-Batch LLM Inference, ISCA, 2025
  • SynGPU: Synergizing CUDA and Bit-Serial Tensor Cores for Vision Transformer Acceleration on GPU, DAC, 2025
  • Oltron: Software-Hardware Co-design for Outlier-Aware Quantization of LLMs with Inter-/Intra-Layer Adaptation, DAC, 2024
  • Dual-side sparse tensor core, ISCA, 2021
  • Caffeine: Toward uniformed representation and acceleration for deep convolutional neural networks, T-CAD, 2018
  • Optimizing FPGA-based accelerator design for deep convolutional neural networks, FPGA, 2015

Awards and Honors

  • [2025] ISCA Best Paper Award【First Winner from China】
  • [2025] ISEDA Best Paper Award
  • [2025] FPGA and Reconfigurable Computing Hall of Fame (名人堂)【SJTU News，UCLA News，TCFPGA Web】
  • [2024] Stanford and Elsevier Top-2% Most Cited Scholars (Computer Architecture and Hardware)【Web】
  • [2021~2024] AI-2000 World’s Most Influential Scholars (AI Chip)【AI-2000 Web】
  • [2022] MICRO Top Picks Honorable Mention （MICRO 年度最佳论文优胜奖）
  • [2022] ACM ChinaSys Rising Star【Web】
  • [2019] Microsoft Research SSA（微软研究院院长特别奖）
  • [2019] Donald O. Pederson Best Paper 【IEEE News，UCLA News，PKU News】
  • [2015] FPGA Best Paper Nomination 【Web】