Find Academic Supervisors

Valentin HONOREView profile

Associate Professor

• High-Performance Computing (HPC)
• Big Data Convergence
• HPC Workload Management
• +4 more

Valentin HONORE is an Associate Professor at École Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE) in Evry, France, and a member of the SAMOVAR laboratory's Benagil team. His research focuses on High-Performance Computing (HPC), Big Data convergence, workload management, and in-situ analytics. He holds a PhD from the University of Bordeaux (2020) and has held post-doctoral and visiting scholar positions at institutions including CC-IN2P3 (France), Vanderbilt University (USA), and JAIST (Japan). His work includes developing frameworks like SIM-SITU for in-situ processing and PALLAS for HPC trace analysis. He is actively involved in program committees for conferences like ESA, Cluster, and SC, and leads the ANR JCJC project VHS (starting 2026). Valentin's educational background includes a Master’s degree from École Normale Supérieure de Lyon and a Bachelor’s from Université Montpellier 2. His research interests span scheduling algorithms for stochastic jobs, reservation strategies, and distributed systems. He has contributed to projects like TADaaM Inria and the CCLab group, emphasizing practical solutions for heterogeneous HPC environments. Grants & Projects: ANR JCJC VHS Project (2026–): Focuses on HPC-Big Data convergence and workload management. Post-doctoral funding at CC-IN2P3 (2020–2022). Labs & Teams: BENAGIL Team within SAMOVAR laboratory. Former affiliations: TADaaM Inria (Bordeaux), CCLab (Villeurbanne).

Catherine COMBESView profile

Assistant Professor

• Artificial Intelligence
• Deep Learning
• Data Mining
• +6 more

Catherine COMBES is an Assistant Professor at the University Jean Monnet Saint-Etienne , affiliated with the Laboratoire Hubert Curien UMR CNRS 5516 and its Machine Learning Team . Her research bridges Artificial Intelligence and Healthcare Systems through applications of Data Mining , Complex Data Analysis , and Probabilistic Modeling . PhD in Computer Science (1994, University of Clermont-Ferrand) Specializes in Amoroso family distributions for financial and healthcare data Her work spans Deep Learning for elderly autonomy modeling, Network-on-Chip optimization, and Operational Research in surgical scheduling. Publications include 15+ journal and conference contributions since 2000, with a 2006 best paper award in healthcare engineering. Scientific Contributions: Developed Generalized Extreme Value models for surgical durations Created UML-statechart tools for dialysis unit simulation Integrated constraint programming for endoscopy scheduling Advanced Markov Chain applications in geriatric care Current affiliations include Laboratoire Hubert Curien , where she applies 4th-parameter Generalized Gamma Distributions to stock returns and medical data.

Vasco T. VasconcelosView profile

Professor

• Programming Languages
• Formal Methods
• Concurrency
• +3 more

Vasco T. Vasconcelos is a Professor at the University of Lisbon, affiliated with LASIGE (Laboratory of Computer Science and Informatics). His research focuses on programming languages, type systems, and concurrency, particularly in session types and their applications to functional and parallel programming. Academic Rank: Professor Affiliation: LASIGE, University of Lisbon Vasconcelos has extensively contributed to session type theory, including context-free grammars, asynchronous communication, and gradual typing. His work bridges theoretical formalisms and practical implementations in functional languages like FreeST. He has served on program and steering committees for conferences such as POPL, SPLASH, and ECOOP, and has presented keynotes, including the Mooly Fest at ETAPS 2019. Vasconcelos also mentors students and participates in academic panels, though no specific advisees are listed here.

Jérôme LelongView profile

Professor

• Computational Finance
• Stochastic Optimization
• Monte Carlo Methods
• +3 more

Jérôme Lelong is a Professor at Grenoble Institute of Technology - ENSIMAG, Université Grenoble Alpes, and Director of AMIES. He is a member of the DAO team at Laboratoire Jean Kuntzmann, where he leads the development of the open-source numerical library PNL. He also maintains the LaTeX extension for Visual Studio Code (LaTeX Workshop) and vscode-latex-basics. His research focuses on: Computational finance and stochastic optimization Advanced Monte Carlo methods and parallel computing Stochastic modeling for financial and industrial applications Machine learning approaches for option pricing and risk management Lelong's publications demonstrate consistent focus on stochastic methods in finance, with recent emphasis on machine learning integration. His work bridges theoretical mathematics with practical applications in derivatives pricing, risk analysis, and high-performance computing. He actively advises doctoral students, including: Valentin Reis (co-directed, defended 2018) Zineb El Filali Ech-Chafiq (CIFRE Natixis, defended 2022) Tom Picard (CIFRE Nexialog Consulting, defended 2023) William Thévenot (CIFRE SCOR, ongoing) Ghada Ben Youssef (CIFRE Exiom Partners, ongoing) At ENSIMAG, he co-heads the Financial Engineering major and teaches specialized courses including FX derivatives, Monte Carlo methods for finance, and C++ implementation techniques for pricing models.

Jean-Christophe PesquetView profile

Professor

• Optimization
• Signal Processing
• Image Processing
• +4 more

Jean-Christophe Pesquet is a Professor affiliated with the Laboratory Digital Vision Center. His work spans optimization, inverse problems, artificial intelligence, signal and image processing . He actively collaborates on advanced algorithm design and computational methods for imaging and signal recovery. Key research areas: Optimization, Wavelet Analysis, Blind Source Separation, Deep Learning Recent publications focus on nonconvex optimization, primal-dual splitting, and deep unfolding techniques. His methodological contributions include proximal algorithms, stochastic subspace approaches, and Bregman divergences. Applications range from biomedical imaging (e.g., PET, CT scans) to seismic data analysis and aerospace defect detection. Notable collaborations include researchers like Emilie Chouzenoux , Audrey Repetti , and Caroline Chaux . Current projects integrate neural networks with classical signal processing frameworks (e.g., lifting schemes, MCMC algorithms).

Clément AubertView profile

Associate Professor

• Formal Methods
• Complexity Theory
• Reversible Computing
• +4 more

Clément Aubert is an Associate Professor with tenure at Augusta University's School of Computer and Cyber Sciences. He specializes in formal methods, complexity theory, and reversible computing, with significant contributions to concurrency theory and implicit computational complexity. His research bridges theoretical computer science with practical applications in programming languages and security. Aubert's research focuses on reversible concurrent calculi, computational complexity analysis, and formal verification. His work explores how reversibility can provide insights into traditional computing problems, with applications in security protocols and distributed systems. He has developed static analysis techniques like the mwp-analysis for determining polynomial growth bounds in programs, contributing to the field of implicit computational complexity. His publication record shows consistent contributions to top theoretical computer science venues including CONCUR, RC (Reversible Computation), and POPL-affiliated workshops. His research combines deep theoretical insights with practical implementations, as evidenced by tools like pymwp. The publications demonstrate a clear trajectory from foundational work in complexity theory to applied research in concurrency and security. Tenure at Augusta University (2023) NSF funding for 'Concurrency in Reversible Computations' project Two research grants from Augusta University Research Development Travel Grant for NSF visit Aubert actively mentors students including Neea Rusch, Assya Sellak, and Gabriele Cecilia. He has organized multiple ICE (Interaction and Concurrency Experience) conferences and served on numerous program committees. His research group focuses on reversible computing implementations and complexity analysis tools. He collaborates extensively with researchers across Europe and the United States, maintaining strong connections with French institutions through CNRS.

Olivier FercoqView profile

Professor

• First-order optimization algorithms
• Primal-dual methods
• Coordinate descent methods
• +7 more

Olivier Fercoq is a Professor at Télécom Paris in the Information Processing and Communication Laboratory (LTCI) . He holds a PhD in Applied Mathematics from École Polytechnique (2012) and a Master's degree from Paris 6 and ENSTA Paris. His research focuses on first-order optimization algorithms , primal-dual methods , coordinate descent , and applications in web ranking , chronotherapy for cancer , and statistical learning . Education : PhD in Applied Mathematics (École Polytechnique), Master's (Paris 6), Engineering degree (ENSTA Paris) Research Themes : Optimization for machine learning, primal-dual algorithms, web ranking, chemotherapy scheduling His recent work spans stochastic optimization , nonconvex-nonconcave minimax problems , and scalable semidefinite programming . Articles highlight advancements in primal-dual coordinate descent , power-aware signal processing , and duality gap analysis . Awards include the IMA Leslie Fox Prize (2015) and the Gaspard Monge PhD Thesis Award (2013) . Olivier has supervised numerous PhD students including Eyal Vayness (2024-), Iyad Walwil (2022-), and Eugène Ndiaye (2016-2018). He organized the Paris-Saclay Junior Conference on Data Science and Engineering (2018) and co-led the workshop Optimization, Distributed Computation, and Machine Learning (2016) . His software contributions include APPROX for parallel coordinate descent and tools for scikit-learn .

Sébastien LIMETView profile

Professor

• Parallel and Distributed Computing
• Interactive Scientific Visualization
• Geographic Information Systems (GIS)
• +3 more

Sébastien LIMET is a Full Professor at the University of Orléans, affiliated with the LIFO laboratory (Laboratoire d'Informatique Fondamentale d'Orléans). He is part of the Pamda research team and specializes in parallel computing, scientific visualization, and geospatial data processing. His contact details include sebastien.limet@univ-orleans.fr and his office at Bâtiment IIIA in Orléans. His research focuses on scalable parallel algorithms, interactive visualization frameworks, and high-performance computing for scientific applications. Key projects include ExaViz (ANR-funded molecular dynamics visualization), FvNano (virtual labs for nanosciences), and eXtenGIS (GIS scalability). He has contributed to frameworks like SkelGIS for algorithmic skeletons and FlowVR for distributed visualization systems. LIMET's work bridges theoretical computer science with practical applications in environmental modeling, biomedical simulations, and bioinformatics. His publications span parallel algorithms, visualization systems, and formal methods, with a focus on exascale computing and distributed architectures.

Jean-Marie LagniezView profile

Associate Professor

• Artificial Intelligence
• Constraint Programming
• SAT Solving
• +3 more

Jean-Marie Lagniez is an Associate Professor at the IUT de Lens, Université d'Artois, France. He holds a post-graduate degree in Algorithmic for Inference and Decision from the Informatics Graduate School of Artois University and completed his PhD at the CRIL Laboratory (Centre de Recherche en Informatique de Lens). His research focuses on integrating local search and backtracking methods in SAT and CSP, improving CDCL solvers, and model counting. He has held postdoctoral positions at the Institute for Formal Models and Verification (Johannes Kepler University Linz, Austria) and CRIL. His work spans constraint programming, artificial intelligence, and formal logic. Education: Post-graduate degree in Algorithmic for Inference and Decision, Université d'Artois. PhD in Computer Science, CRIL Laboratory, Université d'Artois. Research Interests: Jean-Marie's research emphasizes enhancing SAT solving techniques, constraint satisfaction, model counting, and parallel computing. He explores applications in belief merging, modal logic, and algorithmic improvements for efficient problem-solving. His contributions include distributed model counters (DMC) and hybrid approaches combining local search with CDCL. Publications: His work in 2018-2017 includes advancements in consensus-finding, distributed SAT solvers, and modal logic satisfiability, published in venues like IJCAI, CP, and AI Communications. These studies highlight his expertise in bridging theoretical foundations with practical algorithmic solutions.

Eric KoskinenView profile

Associate Professor

• Software Verification
• Concurrency
• Programming Languages
• +5 more

Eric Koskinen is the Charles Berendsen Associate Professor (with tenure) of Computer Science at Stevens Institute of Technology in Hoboken, New Jersey. He is also a co-founder of the Commute Workshop at PLDI 2022 and has previously held positions as Researcher at Yale University and Visiting Professor at New York University. Education: Ph.D. in Computer Science, University of Cambridge (UK) Research Interests: Koskinen's research lies at the intersection of software verification , programming languages , and concurrency . He develops automated techniques to ensure reliable and efficient software, with a particular emphasis on commutativity analysis , parallelization , and language-level abstractions for multicore and distributed systems. His recent focus includes the Veracity programming language that introduces commute blocks to simplify concurrent programming. Scientific Awards & Honors: POPL 2023 Distinguished Paper Award Provost's Early Career Award for Research Excellence (2020) CAV 2011 Award Paper Advising & Funding: Prof. Koskinen currently advises three Ph.D. students—Adam Chen, Parisa Fathololumi, and Mihai Nicola—and has recently graduated Cyrus Liu (Ph.D. 2022). His research group has been generously supported by more than $5 million in competitive grants from the NSF, ONR, and DARPA. Recent awards include: NSF: Concurrent Objects ($593k, 2023) ONR: AVTA Transition ($215k, 2022) NSF: Dynamic Analysis ($399k, 2021) NSF: Commutativity Analysis ($495k, 2020) ONR: Temporal Alignment ($3.2M, 2017) Labs & Tools: His group maintains an active open-source tool suite including Veracity (interpreter for commute blocks), Servois2 (commutativity synthesizer), Dynamite (termination/non-termination checker), DarkSea (temporal verifier for binaries), CityProver (commutativity verifier), Knotical (trace-refinement synthesizer), and DrNLA (non-linear to linear integer arithmetic rewriter).

Lindsey KuperView profile

Assistant Professor

• programming languages
• distributed computing
• concurrency
• +5 more

Lindsey Kuper is an Assistant Professor in the Computer Science and Engineering Department at the Baskin School of Engineering, University of California, Santa Cruz. Her research focuses on programming languages, distributed systems, concurrency, parallelism, and software verification. Ph.D., Indiana University (2015) Research interests include: Programming-language-based approaches for concurrent/distributed systems Library-level choreographic programming (Haskell, Rust, TypeScript) Dependently-typed diagrams for inductive reasoning Causal message delivery with refinement types Key research projects: 2025: KameraBag (Kubernetes observability) 2024: Sender-side causal message protocol 2023: HasChor (Haskell choreographic programming) 2022: Liquid Haskell causal broadcast verification Scientific awards: NSF CAREER Award Stellar Development Foundation Grant Google Faculty Research Award Amazon Web Services gift Zulip in-kind sponsorship Teaching history includes courses on: Foundations of Programming Languages (CSE114A) Distributed Systems (CSE232/CSE138) SMT Solving and Solver-Aided Systems Programming Abstractions (Python) Service contributions: Co-founded !!Con and !!Con West Chaired: Choreographic Programming 2024, PLMW workshops, DSLDI, OBT ICFP/OOPSLA/PLDI program committee member Research group: CASL Group (Concurrency and Safety Lab) Languages, Systems, and Data (LSD) Lab Current members: 6 PhD students

Vincenzo CianciaView profile

Researcher

• Formal Methods in Computer Science
• Spatial Logics
• Spatio-Temporal Model Checking
• +5 more

Vincenzo Ciancia is a researcher at ISTI-CNR in Pisa, working within the Formal Methods & Tools Laboratory. He has previously worked at IIT-CNR (Pisa), ILLC (University of Amsterdam), and Universidad Complutense (Madrid). He received his Ph.D. in 2009 from the Department of Computer Science at the University of Pisa under Prof. Ugo Montanari, focusing on coalgebras, presheaf categories, and history-dependent automata. Research Interests Formal Methods in Computer Science Spatial Logics and Spatio-Temporal Model Checking Coalgebras and Category Theory GPU-accelerated Model Checking Medical Imaging Applications Projects EU NRPP THE (Tuscany Health Ecosystem) MUR PRIN STENDHAL (Spatio-Temporal Enhancement of Neural Nets) Bilateral CNR-SRNSF (Georgia) - Model Checking for Polyhedral Logics MUR PRIN IT-MATTERS (Trustworthy Smart Systems, completed) Scientific Tools VoxLogicA: Spatial model checker for medical imaging Topochecker: Topological model checker for evolving systems

• Parallel Computing
• Bioinformatics
• Data Science
• +7 more

Sophie ROBERT is a Lecturer at the University of Orleans , affiliated with the LIFO lab (Building IIIA, 6 rue Léonard de Vinci). She serves as a Team Leader and Board Member for the Pamda Working Group - Sustainable Development . Her work spans interdisciplinary domains including parallel computing, bioinformatics, and scientific visualization. Research Focus: Parallel algorithms, distributed systems, and scalable data processing Key Tools: FastFlow, MapReduce, LSH Applications: Genomic analysis, neural network training, geospatial data Her publications demonstrate expertise in parallelization techniques for large-scale data analysis, including contributions to RNA-Seq processing , LSH-based similarity joins , and DNN distributed training . She also explores domain-specific languages like GeoSkelSL for geoscience applications. As an active academic, she collaborates with institutions across France and participates in interdisciplinary projects bridging computational methods with environmental and healthcare domains. Her email is sophie.robert@univ-orleans.fr .

Emmanuel MELINView profile

Lecturer

• Parallel Computing
• Virtual Reality
• Scientific Visualization
• +5 more

Emmanuel MELIN is a Lecturer at the University of Orléans, affiliated with the PaMDA team at LIFO (Laboratory of Fundamental Computer Science of Orléans). He teaches primarily at the IUT (University Institute of Technology) of Computer Science in Orléans. His research focuses on parallel computing, virtual reality, and scientific visualization using PC clusters and distributed architectures. Research Interests: His work spans parallel algorithms for geospatial processing, high-performance computing for environmental simulations, and distributed virtual reality systems. He has contributed to large-scale VR frameworks and open-source software like FlowVR, NetJuggler, and SoftGenLock. Publications: Dr. MELIN has authored 31 HAL publications, with 15 most recent covering GPU-accelerated finite element methods, tele-immersive grids, distributed application mapping, and geospatial data processing. His work intersects computer science, environmental modeling, and 3D rendering. Labs & Collaborations: He collaborates with INRIA and has participated in projects like RNTL Geobench, ANR DALIA, and Extengis. His software tools are available as open-source projects.

• Vectorization
• Parallel Programming
• High-Performance Computing
• +4 more

Sylvain JUBERTIE serves as a Lecturer at the University of Orleans, affiliated with the LIFO (Laboratoire d'Informatique Fondamentale d'Orléans) research laboratory. His academic career spans over two decades with continuous contributions to high-performance computing, particularly in vectorization techniques and seismic simulation methodologies. His research interests demonstrate deep specialization in: Hardware-specific vectorization (ARM NEON/SVE, SIMD) for seismic kernels GPU acceleration and code portability across architectures High-order spectral finite element methods (EFISPEC3D) Energy efficiency optimization in parallel computing Algorithmic skeleton libraries (OSL, NSIMD) for parallel programming Memory layout reorganization for numerical kernels Analysis of his 15 most recent publications (2013-2025) reveals a consistent research trajectory focused on seismic wave propagation simulation. His work systematically addresses vectorization challenges across ARM architectures, GPU offloading, and memory access patterns, with EFISPEC3D serving as the primary application framework. Notable trends include the development of the NSIMD abstraction layer and rigorous energy-performance trade-off studies on embedded platforms like Jetson boards. Dr. Jubertie maintains active collaboration with key researchers including Fabrice DUPROS, Florent DE MARTIN, and Guillaume QUINTIN through the LIFO laboratory, contributing to France's geophysics research infrastructure while advancing compiler-level optimizations for emerging processor architectures.