Zhiru Zhang

Dr. Zhiru Zhang is a Professor in the School of Electrical and Computer Engineering at Cornell University and a member of the Computer Systems Laboratory. His research focuses on new algorithms, methodologies, and design automation tools for heterogeneous computing systems, with recent publications centering on high-level synthesis (HLS), hardware specialization for machine learning, and programming models for software-defined FPGAs.

Dr. Zhang earned his Ph.D. in Computer Science from UCLA, where he co-founded AutoESL based on his dissertation research on HLS. AutoESL was acquired by Xilinx (now AMD), and its HLS tool evolved into Vivado HLS (now Vitis HLS), which is widely used for designing FPGA-based hardware accelerators. He also holds a B.S. in Computer Science from Peking University and an M.S. in Computer Science from UCLA.

Dr. Zhang's research interests span hardware design, high-level synthesis, FPGA acceleration, machine learning acceleration, heterogeneous computing systems, and computer architecture. His work bridges the gap between software algorithms and hardware implementation, focusing on creating efficient design automation tools that enable specialized hardware for emerging applications, particularly in AI and machine learning. His recent publications demonstrate strong trends in differentiable programming for hardware design, sparse computation optimization, and efficient implementation of large language models on FPGAs.

Dr. Zhang has received numerous prestigious awards including being named an IEEE Fellow, the Intel Outstanding Researcher Award, AWS AI Amazon Research Award, Facebook Research Award, Google Faculty Research Award, DAC Under-40 Innovators Award, Rising Professional Achievement Award from UCLA, DARPA Young Faculty Award, IEEE CEDA Ernest S. Kuh Early Career Award, and NSF CAREER Award. His papers have won multiple Best Paper Awards from top conferences including ASPLOS (2025), ISPD (2025), FPGA (2024, 2022, 2021, 2019), AutoML (2024), FCCM (2018), ACM TODAES (2012), and Top Picks in Hardware and Embedded Security (2020). His papers on HLS scheduling and application-specific instruction-set processor (ASIP) compilation have been inducted into the ACM/SIGDA TCFPGA Hall of Fame for the classes of 2022 and 2023, respectively.

On the teaching side, Dr. Zhang has received the Ruth and Joel Spira Award for Excellence in Teaching (2018) and twice the Michael Tien'72 Excellence in Teaching Award (2016, 2022), the highest recognition for teaching in the College of Engineering. He teaches courses including ECE 5775/6775: High-Level Digital Design Automation, ENGRD/ECE 2300: Digital Logic and Computer Organization, ECE 6980: Special Topics on Hardware Acceleration of Deep Learning, ENGRG 1050: Freshman Engineering Seminar, and ECE 5950: Special Topics on High-Level Digital Design Automation.

Dr. Zhang leads an active research group with numerous PhD students and postdocs. His current students include Jordan Dotzel, Jie Liu, Zichao Yue, Yixiao Du, Yaohui Cai, Andrew Butt, Hongzheng Chen, Jiajie Li, Niansong Zhang, Matthew Hofmann, Zhanqiu Hu, Vesal Bakhtazad, and Grace Dinh. His alumni have gone on to successful careers at companies like NVIDIA, Google, AWS AI, Meta, Microsoft, and academic positions at universities including University of Illinois Chicago and Zhejiang University. The group has received multiple research grants from industry partners including AWS, Intel, and Google.