Wissenschaftlicher Mitarbeiter
Anouar Nechi, M. Sc.
- anouar.nechi@uni-luebeck.de
- Telefon
- +49 451 3101 6320
- Büro
- Gebäude 64, Raum 128 (2. OG)
- Anschrift
- Universität zu Lübeck
Institut für technische Informatik
Ratzeburger Allee 160
23562 Lübeck
Germany
Anouar Nechi wurde in Nabeul (Tunesien) geboren und zog 2017 nach Deutschland. Er besitzt einen Masterabschluss in Information Systems Techniques von der National Engineering School of Tunis. Seit 2018 arbeitet er als wissenschaftlicher Mitarbeiter an der Universität zu Lübeck. Dort entwickelt und optimiert er Deep-Learning-Modelle für künftige Kommunikationssysteme und forscht an Themen wie Vertrauenswürdigkeit, Erklärbarkeit sowie der Beschleunigung von KI-Anwendungen auf spezialisierter Hardware. Seine Forschungsergebnisse veröffentlichte er in mehreren begutachteten Beiträgen zu 6G-Technologien, rekonfigurierbarer Hardware und maschinellem Lernen.
Forschung
Lehre
WiSe 2026/27
Frühere Semester (6)
- SoSe 2026
- Systemarchitekturen für Multimedia, Wireless Sensor Networks (Drahtlose Sensornetze)
- WiSe 2025/26
- Parallel Computing Systems for Master-AI, Parallelrechnersysteme
- WiSe 2024/25
- Parallel Computing Systems for Master-AI, Parallelrechnersysteme
- SoSe 2021
- Systemarchitekturen für Multimedia
- WiSe 2020/21
- Computergestützter Schaltungsentwurf
- SoSe 2020
- Real-Time Systems
Abgeschlossene Projekte
Publikationen
A. Nechi,
Y. Ghafourian,
B. A. Naim,
T. Gutt,
G. Dimitrakopoulos,
A. Moualhi,
M. Berekovic,
P. Varga,
et al.
Multi-Partner Project: Artificial Intelligence in Manufacturing Leading to Sustainability and the Consideration of Human Aspects (AIMS5.0)
2025 Design, Automation & Test in Europe Conference (DATE), IEEE, 2.025
technological innovation cyber-physical systems hardware manufacturing sustainable development artificial intelligence optimization co-pilot
URL, DOI, RIS, BibTex
Multi-Partner Project: Artificial Intelligence in Manufacturing Leading to Sustainability and the Consideration of Human Aspects (AIMS5.0)
2025 Design, Automation & Test in Europe Conference (DATE), IEEE, 2.025
technological innovation cyber-physical systems hardware manufacturing sustainable development artificial intelligence optimization co-pilot
URL, DOI, RIS, BibTex
A. Nechi,
Z. Narjis,
R. Buchty,
M. Berekovic, and
S. Mulhem
Fast Reinforcement Learning for Robust Beam Codebooks in Future Communication Systems
IEEE Transactions on Communications, IEEE, 2025, 2.025
URL, RIS, BibTex
Fast Reinforcement Learning for Robust Beam Codebooks in Future Communication Systems
IEEE Transactions on Communications, IEEE, 2025, 2.025
URL, RIS, BibTex
W. Foudhaili,
A. Nechi,
C. Thermann,
M. A. Johmani,
R. uchty,
M. Berekovic, and
S. Mulhem
Reconfigurable Edge Hardware for Intelligent IDS: Systematic Approach
Applied Reconfigurable Computing. Architectures, Tools, and Applications, Springer, 2.024
RIS, BibTex
Reconfigurable Edge Hardware for Intelligent IDS: Systematic Approach
Applied Reconfigurable Computing. Architectures, Tools, and Applications, Springer, 2.024
RIS, BibTex
A. Nechi,
A. Mahmoudi,
C. Herold,
D. Widmer,
T. Kürner,
M. Berekovic, and
S. Mulhem
Practical Trustworthiness Model for DNN in Dedicated 6G Application
2023 19th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), 312-317, 2.023
wireless communication sensitivity 6g communication terahertz band modulation recognition trustworthiness
URL, DOI, RIS, BibTex
Practical Trustworthiness Model for DNN in Dedicated 6G Application
2023 19th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), 312-317, 2.023
wireless communication sensitivity 6g communication terahertz band modulation recognition trustworthiness
URL, DOI, RIS, BibTex
A. Nechi,
L. Groth,
S. Mulhem,
F. Merchant,
R. Buchty, and
M. Berekovic
FPGA-based Deep Learning Inference Accelerators: Where Are We Standing?
ACM Transactions on Reconfigurable Technology and Systems, 16(4), 1-32, 2.023
RIS, BibTex
FPGA-based Deep Learning Inference Accelerators: Where Are We Standing?
ACM Transactions on Reconfigurable Technology and Systems, 16(4), 1-32, 2.023
RIS, BibTex
A. Dörflinger,
M. Albers,
B. Kleinbeck,
Y. Guan,
H. Michalik,
R. Klink,
C. Blochwitz,
A. Nechi,
et al.
A comparative survey of open-source application-class RISC-V processor implementations
CF '21: Proceedings of the 18th ACM International Conference on Computing Frontiers, ACM, 2021, 2.021
URL, DOI, RIS, BibTex
A comparative survey of open-source application-class RISC-V processor implementations
CF '21: Proceedings of the 18th ACM International Conference on Computing Frontiers, ACM, 2021, 2.021
URL, DOI, RIS, BibTex