Sherif Eissa is a PhD Candidate under the supervision of prof. Henk Corporaal and prof. Sander Stuijk in the Electronic Systems group of the Department of Electrical Engineering at Eindhoven University of Technology (TU/e). His PhD work is part of a national research project "efficientdeeplearning.nl".
In his project, Sherif looks to unvail the power of neuromorphic computing for efficient real-time AI through hardware design.
Sherif earned his Bachelor cum laude in Information Engineering with a major in Electronics in 2016 from German University in Cairo, earning his bachelor thesis at the Institute for Microelectronics Stuttgart (IMS) and University of Stuttgart. He continued to earn his Masters degree cum laude in Information technology and Embedded Systems in 2019 from University of Stuttgart where his Master's thesis at Bosch Research Campus, Renningen discussed CNN accelerators and sparsity utilization. In both bachelor and masters, Sherif was recognized and awarded as the best achieving student in his class in overall grades.
Sherif's research interests intersect Machine learning, hardware design and data encoding. He is intreseted in innovating parallel data processing structures with innovated memory structures and sparsity as a key component to low power edge AI.
Hardware Approximation of Exponential Decay for Spiking Neural Networks3rd IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2021 (2021)
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