Assistant Professor @ NJIT
I completed my doctoral studies in Electrical Engineering at the School of Electrical, Computer and Energy Engineering, Arizona State University (ASU), Tempe, AZ.
My group research interests include the cross-layer (device/circuit/architecture/algorithm/application) co-design of energy-efficient and high-performance systems with the following directions:
Accelerator Design for Big Data Applications: Deep Learning, Bioinformatics, Graph Processing, etc.
In-Memory Computing with Volatile & Non-Volatile Memories
Adaptive Learning for Collaborative In-Edge AI Computing IoT Systems
Low Power and Area-Efficient In-Sensor Computing for IoT
Hardware Security Solution for Emerging Non-Volatile Memories
Low power VLSI circuits
Research Assistant Positions Available
I am currently looking for highly motivated and self-driven Master & Ph.D. students for 2022!
[Oct 2021]: I am invited to serve as a TPC member for DAC 2022.
[Oct 2021]: I am invited to serve as a TPC member for ISQED 2022.
[Aug 2021]: Our paper “MeF-RAM: A New Non-Volatile Cache Memory Based on Magneto-Electric FET” is accepted ACM Transactions on Design Automation of Electronic Systems (TODAES).
[Aug 2021]: "Neuromorphic Computing: From Material to Algorithm (NeuMA)" workshop program at IEEE IGSC 2021 is now finalized.
[July 2021]: Our paper “RNSiM: Efficient Deep Neural Network Accelerator Using Residue Number Systems” is accepted to the 40th International Conference On Computer Aided Design (ICCAD), 2021.
[April 2021]: Our paper “Processing-in-Memory Acceleration of MAC-based Applications Using Residue Number System: A Comparative Study” in collaboration with UNL is accepted to the 31st edition of GLSVLSI.
[Feb 2021]: Two papers are accepted to 58th DAC.
Selected Awards and Distinctions:
2019 Outstanding Adjunct Instructor performance for EEL 4362 Post-CMOS Devices and Circuits from UCF
2019 David T. & Jane M. Donaldson Memorial Scholarship Award from UCF
2019 Best Paper Award of 2019 ACM Great Lakes Symposium on VLSI (GLSVLSI), Washington, D.C., USA
2018 Best Ph.D. Research Award (1st-place) of 2018 Ph.D. Forum at Design Automation Conference (DAC), San Francisco, CA, USA
2018 Best Paper Award of 2018 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), Hong Kong, China
2018 IEEE/ACM Design Automation Conference (DAC) - Ph.D. Forum Travel Grant, San Francisco, CA, USA
2018 Featured Paper of October-December 2018 issue of IEEE Transactions on Emerging Topics in Computing
2017 Best Paper Award of 2017 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), Bochum, Germany
2017 Two Most Cited Articles in Elsevier’s Microelectronics Journal
2017 Most Cited Article in Elsevier’s Microprocessors and Microsystems
2017 Outstanding Reviewer Award of Microelectronics Journal and Microprocessors and Microsystems
2016 Doctoral Fellowship Award from UCF- Office of Research and Commercialization (ORC)
Academic Activities and Service:
Dr. Angizi has authored and co-authored more than 70 research articles in top-ranked international journals and top-tier electronic design automation conferences such as IEEE TNANO, IEEE TCAD, IEEE TC, IEEE TCASI, IEEE TETC, DAC, DATE, ICCAD, ASP-DAC, etc. He received the “Best Ph.D. research award” at the Design Automation Conference’s Ph.D. forum in 2018, two “Best Paper” awards at the IEEE Computer Society Annual Symposium on Very Large-Scale Integration (VLSI) in 2017 and 2018, and a “Best Paper” award at the ACM Great Lakes Symposium on VLSI in 2019.
He has served as a technical reviewer for over 30 international journals/conferences, such as IEEE TC, TVLSI, TCAD, TNANO, TCAS, ESL, ACM JETC, MICRO, DAC, ASP-DAC, DATE, ICCAD, ICCD, GLSVLSI, ISVLSI, etc.