Currently, I am an associate professor Maître de Conférence (MCF) HDR at the Mathematics Interacting with computer Science (MICS) laboratory of the University Paris-Saclay and "Grande Ecole" of engineers CentraleSupélec.
Thus, I have both research and teaching responsibilities. Regarding research, I am either a leader or member of many publicly funded research projects, such as my recent CLearDeep ANR JCJC, or in collaboration with industrials. Regarding teaching, I am co-responsible for the MSc in AI at CentraleSupélec and in charge of many teaching units in the machine learning field. Before, I was a Machine Learning postdoctoral researcher at LIG lab, University of Grenoble Alpes, collaborating with TotalEnergies. I received a Ph.D. in Bio-statistics from the Univ. of Montpellier in 2016.
My research focuses on reliable and trustworthy statistical learning, at the intersection of machine learning, statistics, and causality. I develop methods that combine predictive performance, interpretability, and robustness in the presence of real-world constraints such as heterogeneous, imperfect, and weakly labeled data.
My work spans from interpretable, knowledge-driven models to deep learning approaches, and more recently toward gray-box AI, which aims to reconcile black-box learning with causal transparency.
A central theme of my current research is the fusion of deep learning and causality, including causal representation learning, counterfactual robustness, and causal discovery, with the goal of designing intrinsically interpretable models that support informed and reliable decision-making.
I'm looking for MSc, Ph.D. students and postdocoral candidates to work on research at the intersection of causality and ML.
Some postdoc, Ph.D thesis and intern offers are bellow or coming soon. Come to join the dynamic researchers at the comfortable MICS lab workspace and more globally at University Paris Saclay. Women and students from underrepresented groups are strongly encouraged to apply (my lab is committed to being inclusive spaces).
Hiring:
- Research internship offer (coming soon)
- Ph.D thesis offer (coming soon)
Current Projects:
- ANR CLearDeep (2024-2028, leader) (web page coming soon)
- Project with CEA (2024-2027, participant) on Causal graphs and quantification of uncertainties
- Projets IMPT 2023 - Institut des Mathématiques pour la Planète Terre (consortium members from INRAE, IECL and MICS lab, participant)
- Research collaboration with TotalEnergies for SinclAIr lab on Causality for learning and intervening on wind turbine's welding quality prediction (2024-2025, leader)
- Research collaboration with Saint-Gobain on Causal learning for the analysis and prediction of customer behavior (2021-2024, co-leader).
My other scientific activities:
- Area Chair, UAI 2026
- Member of the MALIA (Machine Learning et Intelligence Artificielle) group of the SFdS.
- Member of MIMS consortium
- Member of Causal-tau research group
- CVPR 2023 reviewer
- NeurIPS 2021 reviewer, NeurIPS 2022 reviewer, NeurIPS 2023 reviewer
- IJCAI 2020 reviewer, IJCAI 2021 reviewer, IJCAI 2022 reviewer, IJCAI 2023 reviewer
- EURO Journal on Decision Processes reviewer (2021)
- Member of the seminaire palaisien scientific comitee
- Mentor of a woman doctoral student via the Femmes & Sciences mentoring program for young women researchers at the University of Paris-Saclay (January 2021 - January 2022)
- Sustainable development correspondent of the MICS laboratory (summer 2020 - winter 2021)
- Industry 4.0 correspondent for the MICS laboratory (since summer 2020)
- Treasurer of the SFdS young Statisticians group (September 2019 - September 2021)
Major Teaching and Academic Service Responsibilities at CentraleSupélec:
- Since Sept. 2024: Co-Director, MSc in Artificial Intelligence, CentraleSupélec (program leadership, admissions, scheduling, coordination, internships, international development, institutional representation (India, Morocco, China), and MSc promotion.).
- Since Sept. 2023: Member of the Steering Committee of the CentraleSupélec AI Hub, contributing to strategic coordination, visibility and promotion of AI initiatives, support to student activities, access to computing resources, and organization of scientific events.
- July 2023: Co-Organizer and Academic Lead, CentraleSupélec AI Summer School — program design, candidate selection, international promotion, and teaching an introductory AI course.
- 2019–2022: Cross-cutting missions at MICS on Industry 4.0 and Sustainable Development, including research and teaching mapping, institutional reporting, and promotion of environmental impact assessment tools (Labo1point5).