2023 – 2024 Research Highlights
Overview
Amirali Amirsoleimani is an assistant professor in the Department of Electrical Engineering and Computer Science at the Lassonde School of Engineering. He received his PhD in electrical and computer engineering (ECE) from University of Windsor in December 2017 and completed his postdoctoral research fellowship at the Edward S. Rogers Sr. Electrical and Computer Engineering Department at the University of Toronto in July 2021. His current research interests include application specific processing units, in-memory computing, neuromorphic hardware design and RRAM-based accelerators for artificial intelligence. Amirali is a senior member of IEEE and a licensed professional engineer. He received IEEE Larry K. Wilson award for IEEE region 7 in 2016. He was the recipient of Odyssey Award 2023 from University of Windsor for the best mid-career alumni, also he was the recipient of a best poster honorable mention award at International Joint Conference on Neural Network (IJCNN) 2017 in Alaska, USA. He is a guest editor in Frontiers in Electronics and Frontiers in Nanotechnology journals and is also serving as a reviewer for several electrical and computer engineering journals including IEEE Transactions on Circuits and Systems I (TCASI), TCAS II, TNANO, TVLSI, TED, Frontiers in Neuro-Science, Microelectronics journal, Neural Computing and Applications.
Research Interests
- Hardware for Artificial Intelligence
- Neuromorphic Computing
- Emerging Memory Technologies
- Bio-Inspired Computing
- In-Memory Computing
- Memory Circuits and Systems
Selected Publications
- CODEX: Stochastic Encoding Method to Relax Resistive Crossbar Accelerator Design Requirements. A. Amirsoleimani. Authorea Preprints, 2024.
- Efficient Sparse Spiking Auto-Encoder for Reconstruction, Denoising, and Classification. B. Walters, H. R. Kalatehbali, Z. Cai, R. Genov, & A. Amirsoleimani. Neuromorphic Computing and Engineering, 4(3), 034005, 2024.
- Manhattan Rule for Robust In-Situ Training of Memristive Deep Neural Network Accelerators. E. Zhang, J. Cai, A. Amirsoleimani, M. R. Azghadi, R. Genov, & M. Ahmadi. 2024 IEEE 67th International Midwest Symposium on Circuits and Systems, 2024.
- Spike Timing Dependent Gradient for Direct Training of Fast and Efficient Binarized Spiking Neural Networks. Z. Cai, H. R. Kalatehbali, B. Walters, M. R. Azghadi, A. Amirsoleimani, & R. Genov. IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 3, 2023.
- WALLAX: A Memristor-Based Gaussian Random Number Generator. X. Dong, A. Amirsoleimani, M. R. Azghadi, & R. Genov. Neurocomputing, 566, 126933, 2024.