Find Academic Supervisors

• Semantics of Programming Languages
• Program Analysis
• Functional Parallel Programming
• +4 more

Wadoud BOUSDIRA is an Associate Professor at the University of Orleans in the Computer Sciences Department under the College of Science . He is a member of the LMV team and affiliated with the Laboratoire d'Informatique Fondamentale d'Orléans (LIFO) . His research focuses on Semantics of Programming Languages , Program Analysis , and Functional Parallel Programming . His work explores thread synchronization , SPMD programming , BSP models , formal verification , and static analysis of parallel programs. The trends in his recent publications emphasize formal verification of parallel programs using tools like Coq , register safety in BSPlib , and transformation of SPMD programs . Key subfields include algorithmic skeletons, distributed arrays, and rewriting rules for program alignment. He has advised PhD student Arvid Jakobsson (CIFRE Huawei, 2016-) on BSP-programs static analysis . His research is supported by projects such as PaPDAS (in partnership with JST, Japan) and ANR SIMI 2 (2011-2014). Contact: wadoud.bousdira-semmar@univ-orleans.fr | Phone: +33 (0)2 38 41 72 69 | Address: LIFO, Building IIIA, University of Orleans, France.

Denis ConanView profile

Associate Professor

• Distributed Systems
• Middleware
• Mobile Computing
• +4 more

Denis Conan is an Associate Professor (HDR) at Télécom SudParis, part of the Institut Polytechnique de Paris. He is affiliated with the SAMOVAR laboratory, specifically the ACMES team and groups PDS and DiSSEM. His research focuses on distributed systems, middleware, mobile and ubiquitous computing, IoT, fault tolerance, and context management. He holds a HDR from Sorbonne Universités and has extensive experience in academic projects like ANR INCOME and Totem. He teaches courses on distributed systems, software architecture, and compilation. Notable contributions include middleware frameworks like MIMOSAE and muDEBS, and he advises numerous PhD students in IoT and distributed systems. Education: HDR in Distributed Systems (2015), PhD from Sorbonne Universités, and Engineer from ENSIIE. His research interests span IoT middleware, adaptive systems, and energy-efficient architectures. Recent work emphasizes IoTVar middleware for application development and EDICT simulation tools for IoT environments. He has contributed to privacy-preserving publish/subscribe systems and energy-aware IoT frameworks. Awards include a best paper at IEEE Pervasive Intelligence and Computing 2017. Advising includes projects on self-adaptive IoT systems, edge infrastructure planning, and context-aware data exchange. He collaborates on projects like INCOME (context management for IoT) and Totem (mobile mixed reality games). His software contributions include COSMOS and MIMOSAE, addressing context composition and microservice evolution.

William ManskyView profile

Assistant Professor

• Program Verification
• Concurrency
• Theorem Proving
• +7 more

William Mansky is a faculty member in the Department of Computer Science at the University of Illinois Chicago, College of Engineering. He is actively engaged in research in formal methods, program verification, and programming languages. His work focuses on applying theorem proving and separation logic to verify concurrent and systems software, particularly under relaxed memory models. His research interests include: Program Verification Concurrency and Parallelism Theorem Proving (especially using Iris and Coq) Language Semantics Compiler and Systems Verification Memory Models and Race Detection The recent articles indicate a strong trend in mechanized verification of low-level systems code, compositional reasoning for concurrent programs, and integration of formal methods with practical software like CompCert and CUDA. His work often bridges theoretical logic with real-world implementation challenges. He has served on program committees for premier conferences including POPL, CPP, and CoqPL, and has chaired sessions on weak memory and program logics. He also contributes to open-source formal verification projects on GitHub, including Coq-related packages and the Iris framework. Notable roles: Program Committee Member – POPL, CPP, CoqPL Session Chair – POPL (Weak Memory and Concurrent Separation Logic) Artifact Evaluation Committee – POPL William Mansky leads a research lab at UIC, accessible at https://mansky.lab.uic.edu/ , where he supervises research in formal verification and programming language theory.

Martin SchulzView profile

Professor

• Parallel and Distributed Architectures
• High Performance Computing
• Performance Modeling and Analysis
• +4 more

Martin Schulz is a Full Professor and Chair for Computer Architecture and Computer Organization at the Technical University of Munich (TUM), where he has been employed since 2017. Previously, he held research positions at Lawrence Livermore National Laboratory (LLNL) and Cornell University. He holds a Doctorate in Computer Science from TUM (2001) and an MS in Computer Science from the University of Illinois Urbana-Champaign (UIUC). His research encompasses: Parallel/distributed systems architecture HPC performance monitoring and optimization Memory hierarchy efficiency Parallel programming models and tools Power/energy-aware computing System-level fault tolerance Schulz leads the MPI Forum standardization body and has authored over 200 peer-reviewed publications. Major scientific recognitions: IEEE/ACM Gordon Bell Prize (2006) for high-performance computing achievements R&D 100 Award (2011) for innovative research

Kaïs KlaiView profile

Professor

• Formal Verification
• Model Checking
• Concurrent and Distributed Systems
• +5 more

Kaïs Klai is a Professor of Computer Science at the University of Sorbonne Paris Nord, affiliated with the LIPN laboratory and the Institut Galilée. He holds leadership roles including President of the Computer Science Department (since 2019) and heads the SAFER research team. His research focuses on formal verification techniques, particularly addressing state space explosion through abstraction and modularity. He applies these methods to domains like blockchain, cloud systems, and business processes. Education: Habilitation à Diriger des Recherches (2013) from Université Sorbonne Paris Nord, focusing on hybrid verification techniques. Research interests include concurrent systems verification, model checking, and domain-specific adaptations of formal methods. His work emphasizes efficiency gains through domain-aware verification approaches. Recent publications explore test path generation, smart contract analysis, and hybrid model checking. He teaches advanced courses such as Transition Systems & Model Checking (M1) and RPHN: High-level Petri Nets (M2). Administrative roles include managing international relations for the southern Mediterranean and leading curriculum development in computer science programs. Labs/Teams: LoVe team (Verification axis leader until 2024), SAFER research team (since 2025).

Elisabeth BRUNETView profile

Lecturer

• Parallel Computing
• High-Performance Computing
• Computer Architecture
• +3 more

Elisabeth BRUNET is a Lecturer at Telecom SudParis, part of the Institut Mines-Télécom. Her research focuses on parallel computing, high-performance computing systems, and communication optimization. She has contributed to projects involving GPU porting, MPI communication protocols, and fault-tolerant checkpointing strategies. Her interdisciplinary work extends to biophysics and stochastic processes, with notable publications in journals like Physical Review Fluids and Scientific Reports . She has also explored applications in sports biomechanics and medical imaging analysis. Key collaborations include work on NewMadeleine communication libraries and unified checkpointing models for extreme-scale systems. Her technical contributions span across both theoretical and applied domains, addressing challenges in distributed computing architectures and performance optimization. Education: While specific academic degrees are not detailed in the provided text, her extensive publication record indicates advanced expertise in computer science and mathematics. Research Interests: Parallel computing architectures, stochastic processes in biological systems, high-performance communication networks, and GPU-accelerated algorithms. Awards: No specific awards are mentioned in the text, though her contributions have been recognized through collaborative projects and peer-reviewed publications.

• Constraint Programming
• Artificial Intelligence
• Combinatorial Optimization
• +7 more

Jean-Charles Régin is a full Professor at Université Côte d'Azur, affiliated with the I3S Laboratory, where he leads the Constraints and Applications (C&A) research team. His work is central to the 3IA Côte d’Azur initiative, focusing on Decision Intelligence and explainable AI under real-world constraints. His research interests include: Constraint Programming (CP) Global Constraints and Efficient Algorithms Multi-valued Decision Diagrams (MDD) Parallel and Distributed Constraint Programming Statistical Constraints (Sampling, Markov Chains, Spread, Deviation) Modeling and Solving Real-World Problems (Bin Packing, TSP, Car Sequencing) Over-Constrained and Multi-Objective Optimization Régin is renowned for his theoretical and practical contributions to Constraint Programming. His work shows a consistent trend in enhancing the scalability and expressiveness of CP systems, integrating machine learning-inspired methods, and applying CP to industrial problems. He has pioneered algorithms such as the one for the alldifferent constraint, widely used in CP solvers. His scientific recognition includes: Research Excellence Award, Association for Constraint Programming (ACP), 2013 Jean-Charles Régin leads the C&A team at I3S and contributes to the 3IA Côte d’Azur chair on Decision Intelligence. He has advised numerous researchers and students in the field, though specific names are not listed in the provided text. His work often involves interdisciplinary collaboration and the development of practical tools for optimization under uncertainty. The C&A team under his leadership focuses on advancing constraint-based reasoning, explainable decision-making, and integration with data-driven methods to solve complex industrial and societal challenges.

• Optimization
• Operations Research
• Artificial Intelligence
• +2 more

Laure Brisoux-Devendeville serves as a Lecturer at the University of Picardie Jules Verne, specializing in Optimization and Cryptography within the AI and Operations Research domain. Her research bridges theoretical algorithms with real-world applications in healthcare logistics and computational problem-solving. Her core research interests include: Combinatorial optimization for facility location (p-center problems with capacity constraints, stratification) Metaheuristic development (Ant Colony Optimization, Adaptive Large Neighborhood Search, Variable Neighborhood Search) Healthcare system optimization (training simulation scheduling, patient pathway planning) Logistics and transportation (pickup-and-delivery problems, parcel distribution) Constraint programming for conference scheduling and resource allocation Analysis of her 15 most recent publications reveals a dominant focus on healthcare applications (47% of works), particularly using nature-inspired algorithms for training simulation centers and patient journey planning. Logistics optimization constitutes 33% of her output, with significant contributions to vehicle routing and parcel distribution. Her methodological approach increasingly integrates machine learning (notably Deep Reinforcement Learning for operator selection) with classical optimization techniques, demonstrating evolution from pure algorithmic development toward hybrid AI solutions since 2021. Dr. Brisoux-Devendeville actively contributes to applied research through projects including: SMILE PICK UP (CIFRE industrial research partnership) Simusanté (health simulation training systems) LORH (logistics optimization research hub)

• Combinatorial Optimization
• Artificial Intelligence
• Operations Research
• +3 more

Corinne Lucet is a full-time Professor at the University of Picardie Jules Verne (UPJV), affiliated with the UR 4290 research unit. Her work focuses on Combinatorial Optimization , Artificial Intelligence , and Operations Research applications in healthcare and logistics.

Dominic OrchardView profile

Senior Lecturer

• Programming Languages
• Type Systems
• Semantics
• +8 more

Dominic Orchard is a Senior Lecturer in the School of Computing at the University of Kent, UK, and co-director of the Institute of Computing for Climate Science at the University of Cambridge. He leads the Programming Languages and Systems research group at Kent and the Laboratory for Programming Languages and Systems for Science. His academic roles include teaching courses on Functional Programming and Theory and Practice of Concurrency. Orchard's research focuses on programming language theory and practice, specializing in type systems, semantics, verification, mathematically structured programming, effect/coeffect systems, and domain-specific languages. His work applies programming language research to computational science, particularly climate science. Key projects include Granule (advanced type systems), CamFort (scientific computing verification), and PLAS4Sci (programming languages for science). His publications demonstrate a consistent focus on type theory, formal verification, and programming language semantics, with recent work exploring graded modal types, session types, program synthesis, and compiler intermediate representations. The research consistently bridges theoretical foundations with practical applications in scientific computing and verification. Awards and Honors: Fellow of the Software Sustainability Institute Distinguished Paper Award at ECOOP 2022 Distinguished Artifact Award at ECOOP 2022 Best paper award at LOPSTR 2020 Advising and Leadership: Orchard currently advises PhD students including Vilem Liepelt, Danielle Marshall, and Paulo Torrens. He has served as program chair for PROPL 2024, TyDe 2021, and PLACES 2019, and served on program committees for POPL, ICFP, ECOOP, and Haskell Symposium. Research Groups: Directs the Laboratory for Programming Languages and Systems for Science at Kent and co-leads the Institute of Computing for Climate Science at Cambridge, focusing on computational methods for environmental science.

Colin GordonView profile

Researcher

• Type Theory
• Separation Logic
• Verification
• +3 more

Colin Gordon is a researcher at Drexel University with a focus on type theory, formal verification, and concurrency. His work bridges theoretical and practical aspects of programming languages. His research interests include: Type Theory Separation Logic Verification Concurrency and Parallelism Capabilities Type and Effect Systems Colin's recent publications address challenges in effect systems, formal verification, and programming language design. His work spans conferences like POPL, PLDI, and SPLASH, reflecting a strong commitment to advancing software correctness and language design.

Zhong ShaoView profile

Professor

• Programming Languages
• Formal Methods
• Operating Systems
• +4 more

Zhong Shao is the Thomas L. Kempner Professor of Computer Science at Yale University. He leads the FLINT research group and is a prominent researcher in programming languages, formal methods, operating systems, and computer security. His work focuses on building certified system software through mechanized proofs to create dependable software systems that can manage increasing complexity in modern computing. Professor Shao's research spans multiple domains including programming language design, OS kernel development, formal semantics, compiler construction, and proof engineering. His work addresses challenging problems in concurrency and distributed computing, with a particular emphasis on creating hacker-resistant systems. He has collaborated with researchers at Princeton, University of Pennsylvania, and MIT on the NSF Expedition project 'The Science of Deep Specification.' Shao's recent publications demonstrate a strong focus on compositional verification techniques for distributed systems and certified compilation. His work on DeepSEA language, CertiKOS operating system, and various verification frameworks shows a consistent trajectory toward building fully verified system software from the ground up. Key themes include linearizability, Byzantine fault tolerance, compositional reasoning, and refinement-based verification approaches across concurrent and distributed systems. As an educator, Professor Shao teaches courses including CS430 Formal Semantics (Spring 2025), CS421 Compilers and Interpreters, CS422 Operating Systems, and CS428 Language-Based Security. He participates in systems seminars on APLAR and SPAM, contributing to the academic community through both research and teaching. Professor Shao leads the FLINT research group at Yale, which focuses on building novel certified system software. The group's work has resulted in breakthroughs such as the CertiKOS operating system, which represents a significant advancement in hacker-resistant concurrent operating systems. The group collaborates with the DeepSpec project, an NSF Expedition focused on deep specifications for trustworthy systems, and has developed frameworks like LiDO, Adore, and AdoB for verifying distributed systems with strong guarantees.

• Logic
• Algorithms
• Graph Theory
• +3 more

Alexandre Vigny is an Assistant Professor at University Clermont Auvergne in France, focusing on the intersection of logic, algorithms, and graph theory. He has previously held postdoctoral positions at the University of Bremen (2019-2023) and the University of Warsaw (2018-2019), and completed his PhD at University Paris Diderot (2015-2018) under Arnaud Durand and Luc Segoufin. Current role: Junior Professor at University Clermont Auvergne (2023-present) Postdoctoral experience: University of Bremen (2019-2023), University of Warsaw (2018-2019) PhD: University Paris Diderot (2015-2018) His research interests span theoretical computer science, with a focus on first-order logic, graph algorithms, and complexity analysis. Recent work includes advances in algorithmic meta theorems, reconfiguration problems on sparse graphs, and distributed domination algorithms. Publications highlight applications of logic in solving graph-theoretic problems and query enumeration in database theory. Key trends in his 2025 publications include lower bounds analysis for dominating sets in sparse graphs, token sliding reconfiguration on DAGs, and elimination distance metrics. Earlier works (2017-2024) cover dynamic query evaluation, monadic stability, and parameterized distributed complexity frameworks. Teaching roles have included courses in algorithm design, object-oriented programming, database systems, and model theory across Clermont Auvergne, Bremen, and Paris institutions. Co-supervises PhD student Jona Dirks (2024-present) in reconfiguration problems on directed graphs.

Jérémie GaidamourView profile

Researcher

• Quantum Mechanics
• Numerical Methods
• High Performance Computing
• +5 more

Jérémie Gaidamour is a CNRS Research Engineer at the Institut Élie Cartan de Lorraine (University of Lorraine), specializing in high-order numerical methods and high-performance computing (HPC) for quantum mechanics simulations. His work focuses on parallel solvers for large sparse linear systems, including hybrid direct-iterative methods and algebraic multigrid (AMG). PhD Thesis: "Conception d'un solveur linéaire creux parallèle hybride direct-itératif" (2009, Université de Bordeaux I) His research interests span Quantum Mechanics (Bose-Einstein condensates via Gross-Pitaevskii equations), Numerical Methods (pseudo-spectral techniques, domain decomposition), and High-Performance Computing (MPI, parallel algorithms). Recent publications highlight advancements in fractional gradient flows and energy-minimizing AMG preconditioners for nonlinear Schrödinger equations. Software development projects include BEC2HPC (parallel spectral methods for BECs), MueLu (AMG solver in Trilinos), and HIPS (hybrid direct-iterative sparse solver). He has contributed tutorials on HPC tools (MPI, OpenMP, GPU/Xeon Phi) and participated in Grid'5000/IDRIS support teams.

Richard AlligierView profile

Lecturer

• Machine Learning
• Air Traffic Management
• Optimization Algorithms
• +5 more

Richard Alligier is a lecturer and researcher at Ecole Nationale de l'Aviation Civile (ENAC) specializing in artificial intelligence applications for air traffic management. His work bridges machine learning, optimization algorithms, and trajectory prediction to address critical challenges in conflict detection and resolution for both manned and unmanned aerial systems. Research Focus : Trajectory prediction, conflict resolution, UAV collision avoidance, mass/thrust estimation, and uncertainty modeling Key Collaborations : Nicolas Durand, David Gianazza, Xavier Olive, Kim Gaume, Sarah Degaugue His publications (2011–2024) analyze trajectory uncertainty quantification, 3D maneuver visualization, and human-aligned deconfliction strategies using ADS-B data. Notable contributions include: Dual-horizon collision avoidance algorithms integrating human factors High-confidence interval prediction frameworks Wind parameter extraction from flight paths Machine learning models for climb/descent phase optimization Awarded the 2019 best paper in trajectory prediction , his work emphasizes operational alignment between automated systems and air traffic controller decision-making. He employs GPU acceleration, metaheuristics, and deep learning architectures while maintaining a focus on practical implementation through partnerships with ONERA and ISAE-SUPAERO.