Find Academic Supervisors

• Neuro-Fuzzy Systems
• Fuzzy Logic
• Neural Networks
• +5 more

Dr. Detlef D. Nauck is a Chief Research Scientist and Technical Group Leader at BT Group's Intelligent Systems Research Centre, and a Visiting Senior Lecturer at Otto-von-Guericke University of Magdeburg's Faculty of Computer Science. His career spans both academic and industrial research environments, with significant contributions to Neuro-Fuzzy Systems and interpretable artificial intelligence. His academic foundation includes: Master's degree in Computer Science (1990) from Technical University of Braunschweig Ph.D. in Computer Science (1994) from Technical University of Braunschweig Habilitation in Computer Science (2000) from Otto-von-Guericke University of Magdeburg Dr. Nauck's research focuses on creating transparent AI systems that combine neural networks' learning capabilities with fuzzy logic's interpretability. His work addresses critical challenges in data analysis, particularly in handling mixed data types, missing values, and symbolic attributes while maintaining model transparency. He has developed practical applications across various domains where understanding decision processes is as important as the decisions themselves. His publication record shows consistent evolution from foundational work on neuro-fuzzy controllers to advanced applications in data mining and knowledge discovery. The research demonstrates a clear progression toward increasingly complex data analysis challenges while maintaining the core principle of model interpretability. Professional recognition includes: Author of the influential book 'Foundations of Neuro-Fuzzy Systems' (Wiley, 1997) Development of NEFCLASS, a widely recognized framework for interpretable classification Extensive contributions to both theoretical and applied aspects of soft computing Significant impact on the field through numerous tutorials and conference presentations Dr. Nauck maintains an active research program that bridges academic theory and industrial application. His dual affiliation allows him to contribute to practical implementations of intelligent systems at BT Group while mentoring the next generation of researchers through his academic position. He leads research in the Neural Networks and Fuzzy Systems group at Otto-von-Guericke University, accessible through their website at http://fuzzy.cs.uni-magdeburg.de, continuing to advance the field of interpretable artificial intelligence with practical relevance.

• Programming Language Semantics
• Computational Effects and Coeffects
• Relational Reasoning
• +3 more

Francesco Gavazzo is an Assistant Professor at the Department of Mathematics, University of Padua. His research focuses on theoretical computer science, particularly in programming language semantics, computational effects, relational reasoning, and inductive/coinductive methods. PhD in Computer Science and Engineering, with Honor Mention MSc in Logic and Computer Science BA in Philosophy His work bridges formal methods with practical applications in program equivalence, quantitative semantics, and effect systems. Recent contributions include frameworks for effectful program distancing and relational theories of effects. Scientific awards include recognition by the Accademia delle Scienze dell'Istituto di Bologna (Top 10 in Science) and the Best Italian PhD Thesis in Theoretical Computer Science (EATCS Italian Chapter). He serves on program committees for POPL and ICFP.

Hiroshi UnnoView profile

Professor

• Programming Languages
• Software Verification
• Artificial Intelligence
• +3 more

Hiroshi Unno is a Professor at Tohoku University 's Research Institute of Electrical Communication and a Visiting Professor at the National Institute of Informatics. He has served on program committees for major conferences like POPL , PLDI , ICFP , and CAV . Dr. Unno's research focuses on Programming Languages Software Verification Artificial Intelligence Higher-Order Model Checking Refinement Type Systems Temporal Logic His recent work (2023-2025) includes advancements in algebraic effects , probabilistic program verification , and prophecy-based type systems . Key contributions appear in POPL , PLDI , and ICFP journals. Scientific awards include Distinguished Paper Award at POPL 2024 Distinguished Paper Award at POPL 2023 PPL 2014 Best Paper Award He leads development of tools like RCaml , Thrust , and EffCaml for refinement type checking. Current projects involve Kakenhi grants 20H04162 and 25H00446 . Dr. Unno actively contributes to academic communities through Program Committee roles at AAAI, CAV, and SAS Editorial work for IPSJ Transactions Organizing PPL Summer School (2022)

Mathias Sablé-MeyerView profile

Research Fellow

• Mechanistic implementation of compositional mental representation
• Geometry perception in humans and non-human primates
• Human reasoning and cognitive fallacies
• +5 more

Mathias Sablé-Meyer is a Postdoctoral Researcher at University College London's Sainsbury Wellcome Centre, working in Tim Behrens's lab. He completed his PhD under the supervision of Stanislas Dehaene at PSL/Collège de France and NeuroSpin, CEA, where he investigated humans' ability to manipulate highly abstract structures, particularly focusing on the perception of geometry. His research spans cognitive neuroscience, computational modeling, and experimental psychology, with a focus on understanding the mechanistic implementation of compositional mental representations. He employs methodologies including MEG, fMRI, behavioral experiments, and computational models to investigate how humans mentally represent abstract structures like geometric shapes, language, and mathematical concepts. Sablé-Meyer's work reveals fascinating insights about human cognitive uniqueness, particularly in geometric perception compared to non-human primates. His recent research examines sequence processing mechanisms and aims to establish foundations for mechanistic implementations of Language of Thought models. He has published in top journals including Cognitive Psychology , Trends in Cognitive Sciences , PNAS , and Journal of Neuroscience . Glushko Dissertation Prize from the Cognitive Science Society (2023) As a supervisor, he co-advises Master's students including Maxime Cauté, who is exploring cross-modal representation of sequences, and is involved with several other students including Svenja Kuchenhoff, Amy Wong, and others. His lab follows open science principles, with code systematically published on the Open Science Framework alongside articles. His research program bridges cognitive science, neuroscience, and artificial intelligence, with implications for understanding both human cognition and developing more human-like AI systems. He maintains active collaborations across institutions including UCL, Collège de France, MIT, and École Normale Supérieure.

Ranjit JhalaView profile

Professor

• Programming Languages
• Software Engineering
• Type Systems
• +3 more

Ranjit Jhala is a Professor of Computer Science Engineering at UC San Diego's Jacobs School of Engineering, where he leads the Programming Systems Group. His research spans Programming Languages and Software Engineering, focusing on building reliable systems through Type Systems, Model Checking, Program Analysis, and Automated Deduction. His current projects include Flux for Rust verification, Liquid Haskell refinement types, and techniques for analyzing timing channels. Professor Jhala teaches courses on Programming Languages (CSE 130) and Graduate Programming Languages (CSE 230), with extensive experience teaching compilers and verification topics. Professor Jhala advises several students including Alexander Bakst, Ben Cosman, and Marc Andrysco. Notable former students include Niki Vazou (Postdoc at Maryland), Ravi Chugh (University of Chicago), and Patrick Rondon (Google).

Maxime FolschetteView profile

Associate Professor

• Computer Science
• Formal Methods
• Bioinformatics
• +3 more

Maxime Folschette is an Associate Professor at Centrale Lille Institut, affiliated with the CRIStAL research laboratory (UMR 9189) and the BioComputing research group. His position combines teaching responsibilities at Centrale Lille and its internal school IG2I with active research in computational biology and formal methods. His primary research focuses on the analysis and learning of dynamical biological models, with particular emphasis on formal methods applied to biological regulatory networks. His work spans multiple domains including Parameters Inference, Static Analysis, Polyadic μ-calculus, and Hoare Logic, all applied to biological systems modeling. Folschette's publications demonstrate a strong trend toward developing computational frameworks that bridge theoretical computer science with practical biological applications. His recent work shows increasing focus on hybrid modeling approaches that combine discrete and continuous dynamics, logical learning techniques for network inference, and applications in medical domains such as diabetes modeling and cancer research. ILP best paper award during IJCLR'2021 Best Paper Award for BIOINFORMATICS'2024 As an advisor, Folschette currently mentors two PhD students (Madeleine Eyraud and Karim Raqbi) and has successfully guided two PhD students to defense (Honglu Sun in 2023 and Danilo Dursoniah in 2024). His research is supported through multiple collaborations across France and Japan, particularly with the BioComputing team at CRIStAL. His laboratory work focuses on developing computational tools like Pint, Hybrid Hoare Logic tool, key-pipline, INEX-MED, and pyBRAvo for biological network analysis.