معرفی
Dr. Mohamed Elamien is an Assistant Professor in the Department of Electrical and Computer Engineering at McMaster University. His research focuses on automating high-performance integrated circuit (IC) design, addressing Power-Performance-Area (PPA) challenges in semiconductors, and developing self-powered platforms for emerging technologies like biomedical and IoT applications. He holds a BSc (Highest Honors) and MSc from the University of Sharjah (2015–2017), and a PhD in Electrical and Computer Engineering from the University of Calgary (2021). Prior to academia, he worked as a senior analog/mixed-signal circuit design engineer at Synopsys (2022).
- Education:
- BSc (Highest Honors) in Electrical & Electronics Engineering – University of Sharjah (2015)
- MSc in Electrical & Electronics Engineering – University of Sharjah (2017)
- PhD in Electrical & Computer Engineering – University of Calgary (2021)
His research interests span analog and mixed-signal circuit design, CMOS integrated circuits, biomedical technologies, and energy-efficient systems. He has developed innovative designs for oscillators, filters, and low-power circuits with applications in IoT and healthcare. His work emphasizes automation and symbolic math tools to streamline circuit synthesis.
Dr. Elamien has published extensively in top-tier journals like IEEE Transactions on VLSI Systems and IEEE Transactions on Microwave Theory and Techniques, focusing on topics such as all-pass filters, low-power oscillators, and AI-driven circuit design. His articles often address challenges in high-frequency communication systems and noise reduction.
- Awards:
- Alberta Innovates Graduate Student Award (2020 – Technology Category)
- Alberta Graduate Excellence Scholarship (2019–2020)
- 2022 Schulich School of Engineering Graduate Student Research Excellence Award
He currently teaches ELECENG 2CJ4: Circuits and Systems and ELECENG 3TP3: Signals and Systems, emphasizing advanced circuit analysis and systems theory. His lab explores next-generation circuit architectures for energy-efficient and biomedical applications.
