Soheil Salehi
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Assistant Professor of Electrical and Computer Engineering
Soheil Salehi's Full CV (PDF)
Soheil Salehi is a tenure-track assistant professor in the Electrical and Computer Engineering (ECE) Department at the University of Arizona. Before joining the University of Arizona, he was an NSF-Sponsored Computing Innovation Fellow (CIFellow) and Postdoctoral Research Fellow in the Accelerated, Secure, and Energy-Efficient Computing (ASEEC) Laboratory and the Center for Hardware and Embedded Systems Security and Trust (CHEST) at the University of California, Davis (UCD) from 2020 until 2022. Dr. Salehi's postdoctoral fellowship was supported by the Computing Research Association (CRA) and the Computing Community Consortium (CCC) under the NSF-Sponsored CIFellows Program.
Salehi received his Ph.D. and M.S. degrees in ECE from the University of Central Florida (UCF) in 2016 and 2020, respectively. He also received a B.S. degree from the Isfahan University of Technology (IUT), Isfahan, Iran, in 2014. Salehi was the sole recipient of the UCF Excellence by a Graduate Teaching Assistant at the university level in 2016. He was nominated for the 30-under-30 Award at UCF in 2020 and the Postdoctoral Research Excellence Award at UCD in 2022.
Salehi's technical research interests are hardware and AI-enabled security in IoT, energy-efficient and intelligent signal conversion and processing in IoT, neuromorphic and biologically-inspired AI hardware, emerging spin-based devices, reconfigurable and adaptive computer architectures, and low-power and reliability-aware VLSI circuits.
Degrees
- PhD: Electrical and Computer Engineering, University of Central Florida, 2020
- MS: Electrical and Computer Engineering, University of Central Florida, 2016
- BS: Electrical and Computer Engineering, Isfahan University of Technology, 2014
Teaching Interests
Hardware security, digital VLSI design, applications of AI in CAD and security, embedded system design, computer organization and architecture
Research Interests
Hardware and AI-enabled security in IoT, energy-efficient and intelligent signal conversion and processing in IoT, neuromorphic and biologically-inspired AI hardware, emerging spin-based devices, reconfigurable and adaptive computer architectures, and low-power and reliability-aware VLSI circuits.