• 6
    Citations - based on content available in repository [source: Scopus]
20182023

Content available in repository

Personal profile

Research profile

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.

Academic background

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.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 7 - Affordable and Clean Energy

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