Yanzhi Wang

Associate Professor,  Electrical and Computer Engineering

Contact

Office

  • 617.373.8805

Related Links

Research Focus

Real-time and energy-efficient deep learning and artificial intelligence systems, model compression of deep neural networks (DNNs), neuromorphic computing and non-von Neumann computing paradigms

Education

  • PhD, University of Southern California, 2014

Honors & Awards

  • 2022 College of Engineering Faculty Fellow
  • IEEE Technical Committee on Secure and Dependable Measurement Early Career Award
  • Army Research Office Young Investigator Award
  • Top Paper Award, IEEE Cloud Computing Conference (CLOUD)
  • System Design Contest Special Service Recognition Award at DAC
  • Massachusetts Acorn Innovation Award, Faculty Research Awards from Google, Mathworks, etc.
  • Best Paper Award, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
  • Best Paper Award, IEEE/ACM International Symposium on Low Power Electronic Design (ISLPED)

Research Overview

Real-time and energy-efficient deep learning and artificial intelligence systems, model compression of deep neural networks (DNNs), neuromorphic computing and non-von Neumann computing paradigms

Selected Research Projects

Research Centers and Institutes

Selected Publications

  • Yue, Jinshan, Liu, Yongpan, Liu, Ruoyang, Sun, Wenyu, Yuan, Zhe, Tu, Yung-Ning, Chen, Yi-Ju, Ren, Ao, Wang, Yanzhi, Chang, Meng-Fan, Li, Xueqing, Yang, Huazhong (2021). STICKER-T: An Energy-Efficient Neural Network Processor Using Block-Circulant Algorithm and Unified Frequency-Domain Acceleration. IEEE Journal of Solid-State Circuits, 56(6),1936-1948. 10.1109/JSSC.2020.3030264
  • Niu, X. Ma, S. Lin, S. Wang, X. Qian, X. Lin, Y. Wang, B. Ren, PatDNN: Achieving Real-Time Dnn Execution on Mobile Devices with Pattern-Based Weight Pruning, in ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2020
  • Ma, F-M. Guo, W. Niu, X. Lin, J. Tang, K. Ma, B. Ren, Wang, PCONV: The Missing but Desirable Sparsity in Dnn Weight Pruning for Real-Time Execution on Mobile Device, AAAI Conference on Artificial Intelligence (AAAI), 2020
  • R. Cai, A. Ren, O. Chen, N. Liu, C. Ding, X. Qian, J. Han, W. Luo, N. Yoshikawa, Y. Wang, A Stochastic-Computing Based Deep Learning Framework Using Adiabatic Quantum-Flux-Parametron Superconducting Technology, in Proceedings of International Symposium on Computer Architecture (ISCA), 2019
Yanzhi Wang

Faculty

Dec 02, 2022

Wang to Organize DACC Workshop at AAAI 2023

ECE Associate Professor Yanzhi Wang will organize the First Workshop on DL-Hardware Co-Design for AI Acceleration to be held in February 2023 at the 2023 AAAI Conference on Artificial Intelligence (AAAI 2023).

Yanzhi Wang

Faculty

Dec 02, 2022

Wang Receives APSIPA Distinguished Industrial Leader Award

ECE Associate Professor Yanzhi Wang received the Asia Pacific Signal and Information Processing Association (APSIPA) Distinguished Industrial Leader award at the APSIPA Annual Summit and Conference 2022 held in November 2022.

Faculty

Nov 02, 2022

2022 Stanford University Annual Assessment of Author Citations

The following COE professors are among the top scientists worldwide selected by Stanford University representing the top 2 percent of the most-cited scientists with single-year impact in various disciplines. The selection is based on the top 100,000 by c-score (with and without self-citations) or a percentile rank of 2% or above. The list below includes […]

Yanzhi Wang

Faculty

Oct 25, 2022

Wang organizes the HALO workshop at ICCAD 2022

Yanzhi Wang, associate professor at ECE, organized the Workshop on Hardware and Algorithms for Learning On-a-chip (HALO) being held in November 2022 at the 2022 International Conference on Computer-Aided Design (ICCAD 2022).

Yanzhi Wang

Faculty

Oct 25, 2022

Wang serves as Thrust Leader in NSF Expeditions in Computing

Yanzhi Wang, associate professor at ECE, serves as Thrust Leader for Thrust 5 in the NSF Expeditions in Computing “DISCoVER: Design and Integration of Superconducting Computation for Ventures beyond Exascale Realization“.

Yanzhi Wang

Faculty

Aug 02, 2022

Wang’s Research Paper Receives Honorary Mention at ICLR 2022 Workshop

ECE Associate Professor Yanzhi Wang was awarded an Honorary Mention for his paper “Coarsening the Granularity: Towards Structurally Sparse Lottery Tickets” at the International Conference on Machine Learning (ICML 2022) Workshop on Hardware-Aware Efficient Training (HAET) held on July 23, 2022.

Yanzhi Wang

Faculty

Jul 25, 2022

Wang organized the ROAD4NN workshop at DAC 2022

Yanzhi Wang, associate professor at ECE, organized the ROAD4NN workshop: International Workshop on Research Open Automatic Design for Neural Networks held on July 10, 2022, at the Design Automation Conference (DAC) 2022. Over 100 virtual attendees registered for the workshop. Wang also served in the Early Career Workshop at DAC 2022.

prof next to network rack

Faculty

Apr 22, 2022

ECE’s Wang and Collaborators Awarded $15M by NSF for Developing Superconducting Technology for Faster, More Efficient Computing

Yanzhi Wang, assistant professor, electrical and computer engineering (ECE), is part of a multi-university team that was awarded a $15 million, six-year grant from the National Science Foundation’s Expeditions in Computing program. With collaborators from the University of Southern California, Cornell University, Auburn University, and the University of Rochester, Wang is exploring the use of novel superconductor electronics as a viable next step in computing technology.

Faculty

Apr 15, 2022

Faculty and Staff Awards 2022

Congratulations to all the winners of the faculty and staff awards, and to everyone for their hard work and dedication during the 2021-2022 academic school year.

Faculty

Dec 23, 2021

COE Professors Selected in Stanford University List of Top 2% Scientists Worldwide

The following COE professors are among the top scientists worldwide selected by Stanford University representing the top 2 percent of the most-cited scientists with single-year impact in various disciplines. The selection is based on the top 100,000 by c-score (with and without self-citations) or a percentile rank of 2% or above. The list below includes […]

View All Related News