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Assist Prof Dr. Amirali Amirsoleimani | AI Hardware design | Best Scholar Award

Assist Prof Dr. Amirali Amirsoleimani, York University, Canada

Dr. Amirali Amirsoleimani is an Assistant Professor at York University, Canada, with a strong background in Electrical and Computer Engineering. His research is dedicated to advancing AI and neuromorphic computing by integrating CMOS technology with emerging memory solutions and bio-inspired algorithms. He has received numerous accolades for his contributions, including the IEEE Larry K. Wilson Award and the Alumni Odyssey Award from the University of Windsor. Dr. Amirsoleimani’s work is focused on developing cutting-edge technologies for efficient, high-performance computing systems in smart environments.

PROFILE

Orcid

Education

Ph.D. in Electrical and Computer Engineering (Sep 2014 – Dec 2017)

University of Windsor, Windsor, ON, Canada

Dissertation: In-Memory Computing by Using Nano-ionic Memristive Devices

Advisor: Dr. Majid Ahmadi

External Examiner: Dr. Manoj Sachdev

M.Sc. in Electrical and Computer Engineering (Sep 2011 – Sep 2013)

Razi University, Kermanshah, Iran

Dissertation: Process Variation Analysis of CMOS and CMOS-Memristor Logic Gates

Advisor: Dr. Arash Ahmadi

B.Sc. in Electrical and Computer Engineering (Sep 2006 – Sep 2010)

Razi University, Kermanshah, Iran

Dissertation: Intelligent Digital Thermal Measurement with USB Data Transfer Protocol

Advisor: Dr. Reza Keyhani

Research Interest 

Dr. Amirali Amirsoleimani’s research focuses on developing ultra-efficient artificial intelligence (AI) and neuromorphic computing solutions. His work involves the integration of CMOS circuits with emerging memory technologies such as RRAM and PCRAM, as well as bio-inspired spike-based computing algorithms. His goal is to design fully-integrated in-memory computing systems, employing a software-hardware co-design approach. Dr. Amirsoleimani leads an interdisciplinary team of experts to create innovative solutions at the device, circuit, and software levels, aimed at achieving low-power, high-performance AI for smart environments.

Professional Experience

Dr. Amirali Amirsoleimani is an Assistant Professor at York University, Canada. He has been recognized for his contributions to the field with the IEEE Larry K. Wilson Award in 2016, which is awarded to a single recipient annually in Canada. Dr. Amirsoleimani was also honored with a Best Poster Honorable Mention at the IEEE International Joint Conference on Neural Network in 2017. His involvement in IEEE has been notable, with various recognitions including Certificates of Recognition for his roles and contributions within the IEEE Windsor Section. Additionally, he received the Graduate Student Society (GSS) Scholarship in 2016, further highlighting his achievements in the academic and research communities.

TOP NOTABLE PUBLICATIONS

SITU: Stochastic input encoding and weight update thresholding for efficient memristive neural network in-situ training
BITLITE: Light Bit-wise Operative Vector Matrix Multiplication for Low-Resolution Platforms
WALLAX: A memristor-based Gaussian random number generator
MEDSA: A Memristive-passive Delta-Sigma ADC Circuit for Detecting Neural Signals
A subranging nonuniform sampling memristive neural network-based analog-to-digital converter
Assist Prof Dr. Amirali Amirsoleimani | AI Hardware design | Best Scholar Award