Find Academic Supervisors

Isabelle Bloch is a full Professor at Télécom Paris (Institut Polytechnique de Paris) and Emeritus Professor at the University of Bordeaux . She heads the Image, Modeling, Analysis, Geometry, Synthesis (IMAGES) research team within the Information Processing and Communication Laboratory (LTCI) in the Image, Data, Signal (IDS) Department . Education & Affiliations Professor – Télécom Paris, Institut Polytechnique de Paris (current) Professeure Émérite – University of Bordeaux (honorary) Research Interests Her work lies at the intersection of computer science, applied mathematics and medicine . Core themes include mathematical morphology , fuzzy and bipolar logics , 3-D image interpretation , discrete 3-D geometry & topology , information fusion , structural pattern recognition , spatial reasoning and medical imaging . Recent projects extend these concepts to explainable AI , argumentation theory , computational musicology and robotic surgery guidance . Scientific Awards Blondel Medal (2008) – awarded by the French Electrical & Electronics Engineering Society to outstanding young scientists. Grants & Collaborative Projects While specific grant numbers are not listed in the text, Prof. Bloch coordinates and participates in large-scale interdisciplinary projects funded by national (ANR) and European programs, spanning medical AI, pediatric oncology imaging, neuro-informatics and ethical AI. Labs & Teams She leads the IMAGES team (≈ 25 researchers) inside the LTCI – a joint research unit of Télécom Paris and CNRS. The group develops theory and open-source software in mathematical morphology, deep learning and symbolic AI, and collaborates closely with clinical partners at Necker–Enfants Malades Hospital, AP-HP and Gustave Roussy.

• Mathematical morphology
• Fuzzy set theory and bipolar fuzzy sets
• 3D image interpretation and computer vision
• +7 more

Allel Hadjali is a Full Professor in Computer Science specializing in Data Engineering at ISAE-ENSMA (École Nationale Supérieure de Mécanique et d'Aérotechnique) in Poitiers, France. He is affiliated with the Laboratory LIAS (Laboratoire d'Ingénierie des Applications de la Connaissance et des Systèmes) at ISAE-ENSMA. His academic career includes progression from Associate Professor to his current Full Professor position, with extensive teaching experience across multiple computer science domains. Professor Hadjali's research falls within the data science domain, with particular focus on Exploitation, Extraction, and Recommendation (E2R). His work applies Computational Intelligence and Soft Computing techniques to massive data exploitation and analysis, including flexible querying approaches (Skyline, Gradual, and Bipolar queries), modeling and querying uncertain/incomplete data, cooperative answering techniques, and data reduction through linguistic summaries. He also conducts research in recommendation systems (learning-based and group recommendation) and extraction techniques (mining gradual patterns), along with related interests in data quality, intelligent systems, and crowdsourced data management. His publication record demonstrates consistent contributions to top-tier journals and conferences, with recent work focusing on skyline query processing, uncertain data management, RDF knowledge bases, and explainable AI. His research shows a clear trajectory from foundational work in fuzzy logic and uncertain databases toward more applied research in semantic web technologies and machine learning explainability. Professor Hadjali serves on the editorial boards of several prestigious journals including the Journal of Smart Environments and Green Computing, Sensors Journal, and the Universal Journal of Aeronautics and Aerospace Research. He has also organized special issues on topics such as uncertainty in cloud computing and managing uncertain data. At ISAE-ENSMA, Professor Hadjali teaches courses including Formal aspects of software engineering, Language interpretations and compilation, Programming languages, and Data management and exploitation. Previously as an Associate Professor, he taught courses on object modeling, distributed algorithms, operating systems, and advanced databases focusing on preferences and uncertainty. He leads the Data Engineering team within the Laboratory LIAS, which focuses on developing computational intelligence approaches for modern data challenges. His current projects include work on data quality (QDoSSI project funded by CNRS Mastodons 2016-2018) and research actions in GDR MADICS 2018 related to scientific data quality.

• Data Science
• Computational Intelligence
• Soft Computing
• +12 more

Didier Dubois is a CNRS Research Director (DR2) at the Institut de Recherche en Informatique de Toulouse (IRIT) within Université Paul Sabatier, Toulouse. He leads the ADRIA team (Argumentation, Decision, Reasoning, Uncertainty, Learning) in the 'Reasoning and Decision' thematic group. His work focuses on fuzzy sets, possibility theory, imprecise probability, decision theory, and uncertainty management in AI and operational research. Education: Ingénieur Civil de l'Aéronautique from ENSAE (1975) Docteur Ingénieur from ENSAE (1977) Docteur d'Etat from Université de Grenoble (1983) Habilitation à diriger des recherches from Université Paul Sabatier (1986) Research Interests: Explores mathematical models for uncertainty and vagueness, including numerical/qualitative possibility theory, risk analysis under partial ignorance, generalized possibilistic logic, qualitative decision theory, and applications in scheduling, information retrieval, and soft constraints. Key Contributions: Co-developed fuzzy set theory applications, edited influential volumes on uncertainty and decision-making, and pioneered formal frameworks for combining probability and possibility. Current research emphasizes bipolar knowledge representation and epistemic reasoning. Editing Roles: Co-Editor-in-Chief of Fuzzy Sets and Systems since 1999, and series editor for the Handbooks of Fuzzy Sets . Awards: Docteur Honoris Causa, Polytechnic School of Mons (1997) IFSA Fellow (1999) ISI Most Cited French Scientist (2001) IEEE Neural Network Society Pioneer Award (2002) Advising: Supervised numerous PhD students since 2005, including work on possibility theory, risk analysis, and decision fusion. Collaborates with institutions like IRSN, ONERA, and Airbus.

• Fuzzy Sets
• Possibility Theory
• Imprecise Probability
• +3 more