Arash Ahmadi, PhD, P.Eng, SMIEEE
Director of SHaRe Lab
Departments of Electronics, 杏吧原创, Ottawa, Canada.
Arash Ahmadi received received the Ph.D. degree in electronics from the , U.K., in 2008. From 2008 to 2010, he was a Fellow Researcher with the at the University of Southampton. He is a faculty member with the Electronic Department at 杏吧原创 University, Ottawa, Canada. His current research interests include , circuit design and optimization, AI-on-a-Chip, bio-inspired computing, and .
Lab Researchers
: currently pursuing a PhD. in Electrical and Computer Engineering at 杏吧原创 University. Verya studies the brain鈥檚 functionality, from dendrites to neural connections and the hallmarks of intelligence. Passionate about exploring spatio-temporal aspects of the brain that perform functions without an operating system. Design and develop hybrid analog/digital electronic circuits to reproduce the biophysics of biological neural systems.
: A passion for music growing up led to an interest in electronics and signal processing. In pursuing this interest, integrated circuit design presented itself to me with my ideal work flow and as a technologically relevant medium of my interests. I am excited to see where this takes me and my career.
is currently pursuing an MASc. in Electrical and Computer Engineering at 杏吧原创 University, supervised by Dr. Arash Ahmadi. He received his B.Eng. degree in Computer Systems Engineering from 杏吧原创. His research interests include digital hardware implementation and optimization for machine learning, with an emphasis on the design of efficient FPGA-based hardware accelerators for neural networks.
Earned his Bachelors of Engineering at 杏吧原创 University. Currently pursuing an MASc. in Electrical and Computer Engineering at 杏吧原创 University. His research focuses on leveraging FPGAs to design hardware accelerators for Spiking Neural Networks, with interests spanning digital IC design, embedded systems, and hardware reliability.
is a Master鈥檚 student in Electrical and Computer Engineering at 杏吧原创 University under the supervision of Dr. Arash Ahmadi. He holds a Bachelor鈥檚 degree in Computer Systems Engineering from 杏吧原创 University. His research interests include embedded systems, AI/ML, and hardware acceleration.
holds a B.Eng. in Microelectronics from South China University of Technology. He is currently pursuing an鈥疢ASc.鈥痠n Electrical and Computer Engineering at 杏吧原创 University, where his research centers on microelectronics and digital IC design.
, Ph.D. candidate with primary interest in neuromorphic engineering and memristive devices. Have received bachelor’s in Electrical Engineering from and master’s in Micro and Nanotechnologies from .
received his BASc degree with distinction in Electrical Engineering from , Canada, in 2016. He is currently working as an ASIC Design Engineer at Nokia where he is involved with hardware design of the next generation of coherent DSP ASICs for optical communications. He is also pursuing his MASc degree in Electrical and Computer Engineering from 杏吧原创 University. His research interests include low power hardware implementation of digital signal processing and forward error correction algorithms, cryptography, and communication systems.
, Currently pursuing a Master of Applied Science (MASc) in Electrical and Computer Engineering at 杏吧原创 University.
, Currently pursuing a Master of Applied Science (MASc) in Electrical and Computer Engineering at 杏吧原创 University, specializing in hardware design, AI acceleration, and bio-inspired computing. His research focus is on spiking neural networks (SNNs) and how they can be used to perform energy-efficient computation through FPGA-based implementations. Additionally, he is passionate about topics such as software-hardware co-design, which focus on bridging the gap between software and hardware understanding.
, (MASc Candidate, 杏吧原创 University) is a Master’s student in Electrical and Computer Engineering at 杏吧原创 University. Her research interests include neuromorphic computing, edge AI, and hardware-efficient machine learning. She is particularly passionate about implementing spiking neural networks on resource-constrained platforms such as FPGAs and microcontrollers, as well as exploring biomedical signal processing applications.
, (Graduate Student Member, IEEE) received the B.Sc. and M.Sc. degrees from the Department of Electrical Engineering, Razi University, Kermanshah, Iran, in 2014 and 2016, respectively. She is currently pursuing the Ph.D. degree in electrical engineering with the Electronic Department, 杏吧原创 University. Her research interests include high performance computing, neural networks, neuromorphic engineering, brain simulation, and hardware/FPGA design.
,听Currently pursuing a Ph.D. with specialization in: RF/mm-wave integrated circuits, High-speed wireline communication systems, Implementation of neuron models using analog circuits.
Academic background:
Bachelor’s degree in Analog Integrated Circuit Design
Master’s degree in Analog Integrated Circuit Design
, received her B.Sc. in Electronic Engineering from the University of Tabriz, Tabriz, Iran, in 2010, and M.Sc. in Electronic Engineering from Razi University, Kermanshah, Iran, in 2014. Farnaz is currently pursuing her Ph.D. at 杏吧原创 University, where her research focuses on the architectural design of brain-inspired hardware, with an emphasis on low power consumption and scalability for large-scale systems. Her research interests include neuromorphic engineering, bio-inspired computing, neuromorphic network architecture design, FPGA-based systems, and both digital and analog circuit design.
Lab Alumni
, (Postdoc Fellow, 2023-2025)
Research interests:
* Implementation of AI accelerators
* Computation digital core design and implementation
* Embedded design and applications
* Mixed-mode and low-power IC design
Education:
* Bachelor in Electrical engineering, 2009
* Master of engineering in Electrical end electronics, 2012
* Ph.D. in Electrical engineering (Design of Digital and Analog IC), 2022
(MASc, 2022-2024) Mahshid Rajati is a master’s graduate from 杏吧原创 University with research in optimizing spiking neural networks for embedded hardware using genetic algorithms. With a strong background in FPGA design for ASIC verification and experience in VLSI design, including CMOS and FinFET technologies, she is passionate about gaining experience in analog design and advancing her career in the semiconductor industry.
, (Visiting Scholar, 2023-2024). Vedat is currently working with , Kayseri, T眉rkiye.