- 1018 North Engineering Research Center
- Phone (205) 348-2823
- Faculty Website
Dr. Jinhui Wang
Professor and Larry Drummond Endowed Chair
Contact
- 1018 North Engineering Research Center
- phone (205) 348-2823
- Faculty Website
Education
- Postdoctoral Fellow, University of Rochester
- Ph.D., Electrical Engineering, Beijing University of Technology
Dr. Jinhui Wang is a Director of the Intelligent Multi-Level Power-Aware Circuits and sysTems (IMPACT) Lab. Throughout his academic career, Dr. Wang has secured a total of $16 million in federal grants including NSF, DOE, and NOAA, as a Principal Investigator (PI) or Co-Principal Investigator (Co-PI). He has published over 200 refereed journal/conference papers and book chapters as well as 31 patents in emerging semiconductor technologies. His previous work has received the Best Paper Award/Nomination at DATE 2021, ISVLSI 2019, ISLPED 2016, ISQED 2016, and EIT 2016. His research interests include: (1) VLSI System, Digital and Mixed-Signal Integrated Circuit (IC) Design, 3D and 2.5D IC Design, and Emerging Memory; (2) AI Hardware Design, Post/Beyond CMOS Device, such as Memristors, Based Neuromorphic Computing System; and (3) Post/Beyond CMOS Devices Enabled Cybersecurity and Internet of Things (IoT) Systems.
Affiliated Areas
Electrical and Computer Engineering
Selected Publications
- H. Uppaluru, Z. Templin, M. R. Khan, M. O. Faruque, F. Zhao, and J. Wang, “256-level Honey Memristor Based In-Memory Neuromorphic System,” IET’s Electronics Letters, vol. 60, no. 17, pp. e70029, September 2024.
- S. A. Khan, M. Oli-Uz-Zaman, and J. Wang, “PAWN: Programmed Analog Weights for Non-linearity Optimization in Memristor-based Neuromorphic Computing System,” IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol. 13, no. 1, pp. 436–444, March 2023.
- M. Oli-Uz-Zaman, S. A. Khan, W. Oswald, Z. Liao, and J. Wang, “Stuck-At-Fault Immunity Enhancement of Memristor-Based Edge AI Systems,” IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol. 12, no. 4, pp. 922–933, December 2022.
- J. Fu, Z. Liao, and J. Wang, “Level Scaling and Pulse Regulating to Mitigate the Impact of the Cycle-to-Cycle Variation in Memristor-Based Edge AI System,” IEEE Transactions on Electron Devices, vol. 69, no. 4, pp. 1752-1762, April 2022.
- Z. Liao, J. Fu, and J. Wang, “Ameliorate Performance of Memristor Based ANNs in Edge Computing,” IEEE Transactions on Computers, vol. 70, no. 8, pp. 1299-1310, August 2021.