Wasim Essbai
Projektass. / MSc
Research Areas
- Machine Learning, Cybersecurity, Neural Networks, Cyber-Physical Systems
About
My research focuses on trustworthy AI, with an emphasis on runtime monitoring, anomaly detection, and verification of neural networks in safety-critical systems. I study methods to detect unreliable model behavior and assess the monitorability of learned representations, combining machine learning, statistical modeling, and formal verification.
Role
- PreDoc Researcher
Cyber-Physical Systems, E191-01
Contact
- wasim.essbai@tuwien.ac.at
- vCard from TISS
Publications
- Bartocci, E., Essbai, W. (2024). A Comparison of Monitoring Techniques for Deep Neural Networks. In Bridging the Gap Between AI and Reality : Second International Conference, AISoLA 2024, Crete, Greece, October 30 – November 3, 2024, Proceedings. AISoLA 2024: International Conference on Bridging the Gap between AI and Reality, Kreta, Greece. Peer-reviewed.
- Essbai, W., BOMBARDA, A., Bonfanti, S., Gargantini, A. (2024). A Framework for Including Uncertainty in Robustness Evaluation of Bayesian Neural Network Classifiers. In DeepTest ’24: Proceedings of the 5th IEEE/ACM International Workshop on Deep Learning for Testing and Testing for Deep Learning (pp. 25–32). Peer-reviewed.
And more…
Soon, this page will include additional information such as reference projects, activities as journal reviewer and editor, memberships in councils and committees, and other research activities.
Until then, please visit Wasim’s research profile in TISS.