Associate Professor of Electrical and Computer Engineering, Khoury College Courtesy Appointment
Boston
Associate Professor of Electrical and Computer Engineering, Khoury College Courtesy Appointment
Boston
Associate Professor of Electrical and Computer Engineering, Khoury College Courtesy Appointment
Boston
Associate Professor of Electrical and Computer Engineering, Khoury College Courtesy Appointment
Boston
Yanzhi Wang is an associate professor in the Department of Electrical and Computer Engineering, with a courtesy appointment in the Khoury College of Computer Sciences at Northeastern University. His group works on both algorithms and actual implementations (FPGAs, circuit tapeouts, mobile and embedded systems, GPUs, emerging devices, and UAVs). His research maintains the highest model compression rates on representative DNNs since 09/2018 (ECCV18, ASPLOS19, ICCV19) and achieves the highest performance/energy efficiency in DNN implementations on many platforms (FPGA19, ISLPED19, HPCA19). His work on AQFP superconducting-based DNN inference acceleration, which is validated through cryogenic testing, has by far the highest energy efficiency among all hardware devices (ISCA19). His work has been published broadly in top conference and journal venues (e.g., ASPLOS, ISCA, MICRO, HPCA, ISSCC, AAAI, ICML, CVPR, ICLR, IJCAI, ECCV, ACM MM, ICDM, DAC, ICCAD, FPGA, LCTES, CCS, VLDB, ICDCS, TComputer, TCAD, JSAC, Nature SP, etc.) and has been cited over 4,900 times according to Google Scholar. He has received four Best Paper Awards, has another seven Best Paper Nominations and three Popular Papers in IEEE TCAD. Several instances of his group’s work have been adopted by industry.
The first PhD student of Wang, Dr. Caiwen Ding, graduated in June 2019 and will become a tenure track assistant professor in the Department of CSE at the University of Connecticut. The second PhD student, Ning Liu, will start as a superstar employee at DiDi AI Research (DiDi Inc.).
Yanzhi Wang is an associate professor in the Department of Electrical and Computer Engineering, with a courtesy appointment in the Khoury College of Computer Sciences at Northeastern University. His group works on both algorithms and actual implementations (FPGAs, circuit tapeouts, mobile and embedded systems, GPUs, emerging devices, and UAVs). His research maintains the highest model compression rates on representative DNNs since 09/2018 (ECCV18, ASPLOS19, ICCV19) and achieves the highest performance/energy efficiency in DNN implementations on many platforms (FPGA19, ISLPED19, HPCA19). His work on AQFP superconducting-based DNN inference acceleration, which is validated through cryogenic testing, has by far the highest energy efficiency among all hardware devices (ISCA19). His work has been published broadly in top conference and journal venues (e.g., ASPLOS, ISCA, MICRO, HPCA, ISSCC, AAAI, ICML, CVPR, ICLR, IJCAI, ECCV, ACM MM, ICDM, DAC, ICCAD, FPGA, LCTES, CCS, VLDB, ICDCS, TComputer, TCAD, JSAC, Nature SP, etc.) and has been cited over 4,900 times according to Google Scholar. He has received four Best Paper Awards, has another seven Best Paper Nominations and three Popular Papers in IEEE TCAD. Several instances of his group’s work have been adopted by industry.
The first PhD student of Wang, Dr. Caiwen Ding, graduated in June 2019 and will become a tenure track assistant professor in the Department of CSE at the University of Connecticut. The second PhD student, Ning Liu, will start as a superstar employee at DiDi AI Research (DiDi Inc.).
