Weiwen Jiang

Assistant Professor
Electrical and Computer Engineering (ECE)
Volgenau School of Engineering (VSE)
College of Engineering and Computing (CEC)
Address: Room 3247, Nguyen Engineering Building, Virginia, 22030
Campus: Fairfax
Email: wjiang8@gmu.edu
Phone: (703)993-5083
[CV]     [Google Scholar]     [dblp]     [Research Gate]     [github]

Bio (long version)

Dr. Weiwen Jiang joined George Mason University in Fall 2021 as an Assistant Professor. He was a Post-Doctoral Researcher in the Sustainable Computing Laboratory (SCL) at the University of Notre Dame, which is directed by Prof. Yiyu Shi. He received his Ph.D. from Chongqing University in 2019. From 2017 to 2019, he complete his Ph.D. thesis in the Department of Electrical and Computer Engineering at the University of Pittsburgh under the supervision of Prof. Jingtong Hu.

Weiwen Jiang has published more than 60 research articles in refereed international conferences and premier journals, including 10+ IEEE/ACM Transactions papers. His current works on co-exploration of hardware and neural architecture are awarded for the 2021 IEEE Transactions on Computer-Aided Design Donald O. Pederson Best Paper Award, won the First Place of the 31st ACM SIGDA University Demonstration at DAC 2021, won the Top Winning Awards at IEEE Services Hackathon 2020, and nominated for the best paper in DAC’19, CODES+ISSS’19, and ASP-DAC’20. In addition, his work on this topic attracts great research interests from the industry; specifically, he got resarch funds from industry via NSF I/UCRC as PI and the Facebook Research Award as Co-PI. In addition, in his first postdoc year, he received research funds from NSF IIS as Co-PI. Furthermore, he built the first co-design framework, QuantumFlow, to demonstrate the quantum advantage in designing neural network onto a quantum computer, which is published in Nature Communications. His works on quantum computing won the NSEC Quantum Sensing 2022-QS-1 Award from Los Alamos National Laboratory.

Dr. Jiang serves as the Associate Editor at IEEE Transactions on Circuits and Systems - II: Express Briefs, the Guest Editor for the Special Issue “Quantum Machine Learning: Theory, Methods and Applications” at Electronics, and the Guest Editor for ISCAS Special Issue at IEEE TCAS-II. He also serves as Technical Program Committee (TPC) member in DAC, ICCAD, DATE, ASP-DAC, ASAP, GLSVLIS, SAC, ISVLSI, SRF@ASP-DAC, LBR@DAC, AEC@RTSS. Besides, he is the reviewer of many premier journals, including IEEE Transactions on Computers (TC), IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), IEEE Transactions on Very Large Scale Integration (TVLSI), IEEE Transactions on Emerging Topics in Computing (TETC), IEEE Transactions on Neural Networks and Learning Systems (TNNLS), ACM Transactions on Design Automation of Electronic Systems (TODAES), etc.

He was the recipient of the Best Paper Award in IEEE TCAD 2021, NVMSA’15 and ICCD’17 , the Best Paper Nomination in ASP-DAC’16, DAC’19, CODES+ISSS’19, and ASP-DAC’20, First Place of the 31st ACM SIGDA University Demonstration at DAC 2021, Top Winning Awards at IEEE Services Hackathon 2020 and the China National Scholarship (Ph.D.). He received grants from Technical University of Munich (TUM) to attend Research Opportunities Week (ROW) in 2020, grants from Chinese Government Scholarship to visit the University of Pittsburgh, grants from IEEE CEDA to attend ESWEEK’19, and grants from ACM/Sigda to attend HALO@ICCAD’19, FPGA’19, PhD Forum@DAC’18, SRC@ICCAD’17.

Selected Publications (Full List)

(Blod Authors: Members from JQub)

A Co-Design Framework of Neural Networks and Quantum Circuits Towards Quantum Advantage
Nature Communications, 12, 579, 2021
Weiwen Jiang, Jinjun Xiong, and Yiyu Shi

Hardware/Software Co-Exploration of Neural Architectures
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 39, Issue 12, Dec. 2020
Weiwen Jiang, Lei Yang, Edwin Hsing-Mean Sha, Qingfeng Zhuge, Shouzhen Gu, Sakyasingha Dasgupta, Yiyu Shi, and Jingtong Hu
(2021 IEEE Transactions on Computer-Aided Design Donald O. Pederson Best Paper Award (2 out of 1000+ submissions))

Accuracy vs. Efficiency: Achieving Both through FPGA-Implementation Aware Neural Architecture Search
Proc. of Design Automation Conference (DAC), Las Vegas, 2019.
Weiwen Jiang, Xinyi Zhang, Edwin H.-M. Sha, Lei Yang, Qingfeng Zhuge, Yiyu Shi, and Jingtong Hu
(Best Paper Nomination, acceptance rate 204/815=25%)

Achieving Super-Linear Speedup across Multi-FPGA for Real-Time DNN Inference
International Conference on Hardware/Software Co-design and System Synthesis CODE+ISSS) in ESWEEK’19
also appears at ACM Transactions on Embedded Computing Systems (TECS)
, NYC, New York, USA, Oct. 2019.
Weiwen Jiang, Edwin H.-M. Sha, Xinyi Zhang, Lei Yang, Qingfeng Zhuge, Yiyu Shi and Jingtong Hu
(Best Paper Nomination, acceptance rate 66/243=27.2%)

Co-Exploring Neural Architecture and Network-on-Chip Design for Real-Time Artificial Intelligence
Proc. Asia and South Pacific Design Automation Conference (ASP-DAC), Beijing, Jan. 2020.
Lei Yang, Weiwen Jiang, Weichen Liu, Edwin H.-M. Sha, Yiyu Shi and Jingtong Hu
(Best Paper Nomination, acceptance rate 86/263=32.6%)

Exploration of Quantum Neural Architecture by Mixing Quantum Neuron Designs
Proc. IEEE/ACM International Conference On Computer-Aided Design (ICCAD), Nov. 2021.
Zhepeng Wang, Zhiding Liang, Shanglin Zhou, Caiwen Ding, Yiyu Shi, and Weiwen Jiang

Can Noise on Qubits Be Learned in Quantum Neural Network? A Case Study on QuantumFlow
Proc. IEEE/ACM International Conference On Computer-Aided Design (ICCAD), Nov. 2021.
Zhiding Liang, Zhepeng Wang, Junhuan Yang, Lei Yang, Yiyu Shi, and Weiwen Jiang

Seleced Awards (Full List)

  • NSEC Quantum Sensing 2022-QS-1 Award
  • Best Demonstration (First Place), University Demo, IEEE/ACM Design Automation Conference, 2021 (1 out of 11 teams)
  • 2021 IEEE Transactions on Computer-Aided Design Donald O. Pederson Best Paper Award (2 out of 1000+ submissions)
  • Top Winning Awards at IEEE Services Hackathon (2 out of 10 teams)

Seleced Teaching (Full List)

  • ECE 618: Hardware Accelerators for Machine Learning, Instructor, Spring 2022
  • ECE 499/ECE 590: Machine Learning for Embedded Systems, Instructor, Fall 2021

Selected Services (Full List)


  • Associate Editor, IEEE Transactions on Circuits and Systems - II: Express Briefs
  • Guest Editor, Special Issue “Quantum Machine Learning: Theory, Methods and Applications” at Electronics
  • Guest Editor, ISCAS Special Issue at IEEE TCAS-II.
  • ACM/IEEE Design Automation Conference (DAC), Technical Program Committee
  • ACM/IEEE International Conference On Computer-Aided Design (ICCAD), Technical Program Committee
  • AAAI, Technical Program Committee