Projecten per jaar
Persoonlijk profiel
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 gerelateerd aan duurzame ontwikkelingsdoelstellingen van de VN
In 2015 stemden de VN-lidstaten in met 17 wereldwijde duurzame ontwikkelingsdoelstellingen (Sustainable Development Goals, SDG's) om armoede te beëindigen, de planeet te beschermen en voor iedereen welvaart te garanderen. Het werk van deze persoon draagt bij aan de volgende duurzame ontwikkelingsdoelstelling(en):
Vingerafdruk
- 1 Soortgelijke profielen
Samenwerkingen en hoofdonderzoeksgebieden uit de afgelopen vijf jaar
Projecten
- 1 Afgelopen
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TTW P16-25 (project 7): Efficient Deep Learning Platforms (eDLP)
Stuijk, S. (Project Manager), Eissa, S. (Projectmedewerker), van der Hagen, D. (Project communicatie medewerker) & de Mol-Regels, M. (Project communicatie medewerker)
1/09/18 → 31/12/23
Project: Onderzoek 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., jun. 2025, In: IEEE Transactions on Biomedical Circuits and Systems. 19, 3, blz. 523-535 13 blz., 10661301.Onderzoeksoutput: Bijdrage aan tijdschrift › Tijdschriftartikel › 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, blz. 1-6 6 blz. 10149465Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review
6 Citaten (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. (uitgave). Institute of Electrical and Electronics Engineers, blz. 438-445 8 blz. 9996702Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review
Open AccessBestand22 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 anderen, , 2 jun. 2023, 2023 Design, Automation and Test in Europe Conference and Exhibition, DATE 2023 - Proceedings. Institute of Electrical and Electronics Engineers, 6 blz. 10136926Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › 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 sep. 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. (uitgave). Cham: Springer, blz. 407-419 13 blz. (Lecture Notes in Computer Science (LNCS); vol. 14254).Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › 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. (Ontwerper), Sifalakis, M. (Ontwerper), Eissa, S. (Ontwerper), Yousefzadeh, A. (Ontwerper), Stuijk, S. (Ontwerper), Corradi, F. (Ontwerper) & Detterer, P. (Ontwerper), Zenodo, 1 mei 2023
DOI: 10.5281/zenodo.7656911, https://zenodo.org/records/10359770
Dataset