Research output per year
Research output per year
Personal profile
Personal profile
Goran Frehse is a professor in the team Hybrid System Semantics (SSH) and serves as the director of the Computer Science and Systems Engineering department (U2IS) of ENSTA Paris.
His research focuses on the safety of cyber-physical systems, including systems driven by artificial intelligence. In particular, he is interested in the application of formal methods, coming from software analysis, to dynamical systems described by a combination of discrete events and differential equations, also referred to as hybrid systems. His research topics include:
- Modeling dynamical systems and specifying their desired behavior,
- Formally verifying dynamical systems through model-checking and reachability analysis,
- Semi-formal verification techniques such as statistical model checking,
- Monitoring and supervision of AI-based control systems,
- Verifiably safe reinforcement learning.
Research Interests
Computer Science
Research interests
Computer Science
Education/Academic qualification
HDR (PhD Supervision Credentials)
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Collaborations and top research areas from the last five years
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Benchmarking XAI Explanations with Human-Aligned Evaluations
Kazmierczak, R., Azzolin, S., Berthier, E., Hedström, A., Delhomme, Filliat, D., Bousquet, N., Frehse, G., Mancini, M., Caramiaux, B., Passerini, A. & Franchi, G., 1 Jan 2026, Proceedings of the AAAI Conference on Artificial Intelligence. Koenig, S., Jenkins, C. & Taylor, M. E. (eds.). 44 ed. Association for the Advancement of Artificial Intelligence, p. 37491-37500 10 p. (Proceedings of the AAAI Conference on Artificial Intelligence; vol. 40, no. 44).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Open Access1 Citation (Scopus) -
Enhancing Concept Localization in CLIP-based Concept Bottleneck Models
Kazmierczak, R., Azzolin, S., Berthier, E., Frehse, G. & Franchi, G., 1 Jan 2026, In: Transactions on Machine Learning Research. 2026-JanuaryResearch output: Contribution to journal › Article › peer-review
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Explainability and vision foundation models: A survey
Kazmierczak, R., Berthier, E., Frehse, G. & Franchi, G., 1 Oct 2025, In: Information Fusion. 122, 103184.Research output: Contribution to journal › Article › peer-review
Open Access16 Citations (Scopus) -
The ARCH-COMP Friendly Verification Competition for Continuous and Hybrid Systems
Abate, A., Althoff, M., Bu, L., Ernst, G., Frehse, G., Geretti, L., Johnson, T. T., Menghi, C., Mitsch, S., Schupp, S. & Soudjani, S., 1 Jan 2025, TOOLympics Challenge 2023 - Updates, Results, Successes of the Formal-Methods Competitions. Beyer, D., Hartmanns, A. & Kordon, F. (eds.). Springer Science and Business Media Deutschland GmbH, p. 1-37 37 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) ; vol. 14550 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Open Access5 Citations (Scopus) -
CLIP-QDA: An Explainable Concept Bottleneck Model
Kazmierczak, R., Berthier, E., Frehse, G. & Franchi, G., 1 Jan 2024, In: Transactions on Machine Learning Research. 2024Research output: Contribution to journal › Article › peer-review
5 Citations (Scopus) -
ON DOUBLE DESCENT IN REINFORCEMENT LEARNING WITH LSTD AND RANDOM FEATURES
Brellmann, D., Berthier, E., Filliat, D. & Frehse, G., 1 Jan 2024.Research output: Contribution to conference › Paper › peer-review
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Robust Deterministic Abstractions for Supervising Discrete-Time Continuous Systems
Priser, G., Vanneaux, E. & Frehse, G., 1 Jan 2024, Reachability Problems - 18th International Conference, RP 2024, Proceedings. Kovács, L. & Sokolova, A. (eds.). Springer Science and Business Media Deutschland GmbH, p. 187-202 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 15050 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Open Access -
Data-driven Reachability using Christoffel Functions and Conformal Prediction
Tebjou, A., Frehse, G. & Chamroukhi, F., 1 Jan 2023, In: Proceedings of Machine Learning Research. 204, p. 194-213 20 p.Research output: Contribution to journal › Conference article › peer-review
6 Citations (Scopus) -
Fourier Features in Reinforcement Learning with Neural Networks
Brellmann, D., Filliat, D. & Frehse, G., 1 Jan 2023, In: Transactions on Machine Learning Research. 2023Research output: Contribution to journal › Article › peer-review
3 Citations (Scopus) -
ARCH-COMP22 Category Report: Hybrid Systems with Piecewise Constant Dynamics and Bounded Model Checking
Bu, L., Frehse, G., Kundu, A., Ray, R., Shi, Y. & Zaffanella, E., 1 Jan 2022, In: EPiC Series in Computing. 90, p. 44-57 14 p.Research output: Contribution to journal › Conference article › peer-review
Open Access3 Citations (Scopus)