Nicolas Gutowski
Laboratoire d'étude et de recherche en informatique d'Angers (LERIA) · University of Angers
Biography
Nicolas Gutowski is an Associate Professor in the Department of Electrical Engineering and Industrial Computing at IUT of Angers (University of Angers, France) since 2020 and is a member of the LERIA Laboratory. He worked as an IT engineer in Paris (2006–2010) before teaching in four universities (Angers, Poitiers, La Rochelle, Rouen) in 2010–2011. He then served as lecturer and head of the computer engineering department at ESAIP (2011–2016) and as lecturer at ESEO (2016–2019), where he completed a PhD in Computer Science on Reinforcement Learning and Recommendation Systems (2019, supervised by T. Amghar and O. Camp). He continued as Associate Professor at ESEO (2019–2020) before joining the University of Angers. In March 2025, he obtained his H.D.R. (Accreditation to Supervise Research) in Computer Science on multicriteria optimization for machine learning and feature selection, physics-guided deep learning, and generative AI for symbolic music and molecular generation.
Education
31/03/2025 HDR - Habilitation à Diriger des Recherches - in Computer Science (i.e. habilitation to supervise research), University of Angers, LERIA, France. Subject: "Machine Learning for generation and exploration : Adaptation and contextualization for complex data." HDR mentor: Pr. Frédéric Saubion. 04/11/2019 PhD in Computer Science, University of Angers, LERIA, France Subject: "Context-aware recommendation systems for cultural events recommendation in Smart Cities." PhD Supervisor: Dr. Tassadit Amghar. PhD Co-supervisor: Olivier Camp
Recent Scopus Publications
- Physics-guided approach with transfer learning in vehicle lateral dynamics
- Learning Direct Solution in Moving Horizon Estimation with Deep Learning Methods
- Bias-Variance Analysis of Multi-Step Loss Functions for Dynamical System Identification
- A Transformer Model for Predicting Chemical Products from Generic SMARTS Templates with Data Augmentation
- Guiding Evolutionary Molecular Design: Adding Reinforcement Learning for Mutation Selection
Links
- ORCID https://orcid.org/0000-0002-5765-9901
- Google Scholar https://scholar.google.com/citations?user=sTdjSqoAAAAJ
- Scopus https://www.scopus.com/authid/detail.uri?authorId=57202204416
- Personal Weblink https://ngutowski.fr/