- 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 Professor and Larry Drummond Endowed Chair in the Department of Electrical and Computer Engineering at The University of Alabama. He 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 $17 million research grants including $16 million from federal agencies, NSF, DOE, and NOAA, as a Principal Investigator or Co-Principal Investigator. 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 Awards/Nominations 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
- 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.
- 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.
- J. Fu, Z. Liao, J. Liu, S. C. Smith, and J. Wang, “Memristor Based Variation Enabled Differentially Private Learning Systems for Edge Computing in IoT,” IEEE Internet of Things Journal, vol. 8, no. 12, pp. 9672-9682, June 2021.
- J. Fu, Z. Liao, and J. Wang, “Memristor-Based Neuromorphic Hardware Improvement for Privacy-Preserving ANN,” IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol. 27, no. 12, pp. 2745-2754, December 2019.
- X. Peng, W. Sansen, L. Hou, J. Wang, and W. Wu, “Impedance Adapting Compensation for Low-Power Multistage Amplifiers,” IEEE Journal of Solid-State Circuits, vol. 46, no. 2, pp. 445-451, February 2011.