Projects per year
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):
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Collaborations and top research areas from the last five years
Projects
- 1 Finished
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TTW P16-25 (project 7): Efficient Deep Learning Platforms (eDLP)
Stuijk, S. (Project Manager), Eissa, S. (Project member), van der Hagen, D. (Project communication officer) & de Mol-Regels, M. (Project communication officer)
1/09/18 → 31/12/23
Project: Research direct
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NEXUS: A 28nm 3.3pJ/SOP 16-Core Spiking Neural Network with a Diamond Topology for Real-Time Data Processing
Sadeghi, M., Rezaeiyan, Y., Khatiboun, D. F., Eissa, S., Corradi, F., Augustine, C. & Moradi, F., 30 Aug 2024, (E-pub ahead of print) In: IEEE Transactions on Biomedical Circuits and Systems. XX, X, 13 p., 10661301.Research output: Contribution to journal › Article › Academic › peer-review
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Aircraft Marshaling Signals Dataset of FMCW Radar and Event-Based Camera for Sensor Fusion
Müller, L., Sifalakis, M., Eissa, S., Yousefzadeh, A., Detterer, P., Stuijk, S. & Corradi, F., 21 Jun 2023, RadarConf23 - 2023 IEEE Radar Conference, Proceedings. Institute of Electrical and Electronics Engineers, p. 1-6 6 p. 10149465Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
6 Citations (Scopus) -
DNAsim: Evaluation Framework for Digital Neuromorphic Architectures
Eissa, S., Stuijk, S. & Corporaal, H., 4 Jan 2023, Proceedings - 2022 25th Euromicro Conference on Digital System Design, DSD 2022. Fabelo, H., Ortega, S. & Skavhaug, A. (eds.). Institute of Electrical and Electronics Engineers, p. 438-445 8 p. 9996702Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Open AccessFile17 Downloads (Pure) -
PetaOps/W edge-AI µProcessors: Myth or reality?
Gomony, M. D., de Putter, F., Gebregiorgis, A., Paulin, G., Mei, L., Jain, V., Hamdioui, S., Sanchez, V., Grosser, T., Geilen, M., Verhelst, M., Zenke, F., Gurkaynak, F., de Bruin, B., Stuijk, S., Davidson, S., De, S., Ghogho, M., Jimborean, A. & Eissa, S. & 8 others, , 2 Jun 2023, 2023 Design, Automation and Test in Europe Conference and Exhibition, DATE 2023 - Proceedings. Institute of Electrical and Electronics Engineers, 6 p. 10136926Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
3 Downloads (Pure) -
QMTS: Fixed-point Quantization for Multiple-timescale Spiking Neural Networks
Eissa, S., Corradi, F., de Putter, F., Stuijk, S. & Corporaal, H., 22 Sept 2023, Artificial Neural Networks and Machine Learning – ICANN 2023: 32nd International Conference on Artificial Neural Networks, Heraklion, Crete, Greece, September 26–29, 2023, Proceedings, Part I. Iliadis, L., Papaleonidas, A., Angelov, P. & Jayne, C. (eds.). Cham: Springer, p. 407-419 13 p. (Lecture Notes in Computer Science (LNCS); vol. 14254).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
2 Downloads (Pure)
Datasets
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Aircraft Marshaling Signals Dataset of FMCW Radar and Event-Based Camera for Sensor Fusion
Müller, L. (Creator), Sifalakis, M. (Creator), Eissa, S. (Creator), Yousefzadeh, A. (Creator), Stuijk, S. (Creator), Corradi, F. (Creator) & Detterer, P. (Creator), Zenodo, 1 May 2023
DOI: 10.5281/zenodo.7656911, https://zenodo.org/records/10359770
Dataset