Ihsan Erdin

Ihsan Erdin is a practicing engineer with over 20 years of experience in the design of high-speed data communication circuits. He has been working as an SI SME at Celestica in the design of server and networking switch systems since 2007. He is also an adjunct faculty member at Carleton U. Ottawa with research interests in electromagnetics theory and microwave engineering methods in PCB applications. He holds a Ph.D. degree in electromagnetics engineering. He is a member of the Professional Engineers Ontario and a senior member of IEEE. From 2018 to 2020, he served as a Distinguished Lecturer of the IEEE EMC Society.


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Data-Efficient Supervised Machine Learning Technique for Practical PCB Noise Decoupling

DesignCon 2023 Best Paper Award Winner

Design of PCB-based PDNs has become a challenge due to rising power consumption, lowering supply voltages, increasing integration density and design complexity. In this paper, we propose an algorithmic procedure using supervised machine learning techniques to provide expert guidance on the PDN design and optimize power supply decoupling capacitors. The proposed method replaces the computationally expensive numerical simulations with faster ANNs.

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