Find Academic Supervisors

Cedric PietteView profile

Lecturer

• Artificial Intelligence
• Constraint Programming
• SAT Solving
• +4 more

Cédric Piette is a Lecturer in Computer Science at the IUT of Lens, part of the University of Artois. He has been affiliated with the GEA (Gestion et Administration) department since 2009, where he teaches and conducts research in artificial intelligence, particularly in constraint programming. His work focuses on algorithmic techniques for SAT and CSP problems, parallelizing solvers, and explaining inconsistency. Affiliations: CRIL (Lens Computer Science Research Center), IUT of Lens, University of Artois Leadership: President of the French Association for Constraint Programming (AFPC, 2013–2019) Research interests include advancing parallel SAT solving (e.g., PeneLoPe solver), MUS extraction (AOMUS, HYCAM), and knowledge compilation. He contributed to projects like SATAS (SAT-as-a-service) and PAJERO (resource management systems). He has participated in major conferences (e.g., IJCAI, ECAI, CP) and served on program committees for ICTAI, SAT, and IEEE AI4I. His team won awards in SAT 2009 for the ReVivAl preprocessor, achieving 2nd place in APPLICATION and CRAFTED categories. Supervised PhD students include Gaël Glorian (distributed optimization) and Samuel Thomas (knowledge compilation for model counting).

• Big Data
• Machine Learning
• Distributed Systems
• +6 more

Sonia Ikken Benali is a Researcher-Lecturer at CESI (Lille, France), affiliated with the Engineering and Numerical Tools research team. Her work focuses on Big Data, Machine Learning, Distributed Systems, Business Intelligence, and Optimization Problems. She teaches courses in Data Storage/Processing, Business Intelligence, and Operations Research at the Integrated Preparatory Program and Engineering Program levels. Education : Ph.D. in Efficient Placement Design for Big Data in Clouds (Télécom SudParis - Institut Mines-Télécom - Pierre and Marie Curie University, 2018) M.Sc. in Networks and Distributed Systems (Abderrahmane Mira University, Algeria, 2011) State Engineer in Advanced Information Systems (Abderrahmane Mira University, 2010) Her research emphasizes optimizing cloud storage efficiency, cost reduction in distributed systems, and scheduling algorithms for big data workflows. Key contributions include collaborative cloud storage frameworks and Markov model-based I/O scheduling for MapReduce tasks. Lab/Team : Part of the Engineering and Numerical Tools research group at CESI, focusing on practical applications of advanced computational methods.

Laurent PautetView profile

Professor

• Real-Time Systems
• Critical Systems Design
• Embedded Systems
• +7 more

Laurent Pautet is a Professor at Télécom Paris since 2005 and Head of the Autonomous Critical Embedded Systems (ACES) research team at the Information Processing and Communication Laboratory (LTCI). He holds a PhD in Computer Science from Télécom Paris (1993) and an HDR (2001) from Université Pierre et Marie Curie (UPMC). His research focuses on real-time systems, critical systems design, security, and model-based engineering. He leads the ACES team, which addresses challenges in concurrent systems, scheduling algorithms, and safety-critical applications. His academic background includes a PhD supervised by Dassault Electronics and an HDR emphasizing formal methods and distributed systems. His work spans real-time scheduling (e.g., mixed-criticality systems), embedded software reliability, and intrusion detection systems. He has contributed to tools like the Ocarina AADL tool suite and frameworks such as Flex-eWare for embedded distributed systems. Research interests also include cybersecurity threats to intrusion detection systems (IDS), motion control for autonomous vehicles, and application of mixed-criticality scheduling in AI-driven systems like Monte Carlo Tree Search. He actively supervises internships and theses on topics like renewable energy-aware real-time scheduling and 5G NR in SCADA systems. Pautet’s publications span journals like Journal of Systems Architecture and conferences such as RTSS and IEEE CSR. His work bridges theoretical foundations (e.g., linear programming for scheduling) with practical implementations in domains like aerospace and automotive systems.

Guillaume CharpiatView profile

Researcher

• Machine Learning
• Deep Learning
• Computer Vision
• +8 more

Guillaume Charpiat is a Research Officer at INRIA Saclay and Head of the Data Science department at the LISN laboratory (Paris-Saclay University). He holds a PhD in computer vision from the École Polytechnique (2006), conducted under Olivier Faugeras and Renaud Keriven. His postdoctoral research at the Max Planck Institute for Biological Cybernetics focused on statistical learning. He joined the TAO/TAU team in 2015, specializing in machine learning and optimization. His research spans deep learning theory, neural networks, and applications in satellite imagery, genetics, fluid dynamics, and medical imaging. Education: PhD in Computer Vision (École Polytechnique, 2006), Postdoc in Statistical Learning (Max Planck Institute). Teaching includes advanced deep learning courses at MVA/CentraleSupélec and AI master's programs. Research interests emphasize neural architecture design, generative models, and interdisciplinary applications. His work bridges machine learning with physics and biology, addressing challenges like dynamical systems modeling and population genetics inference. Key contributions include neural architecture growth strategies, equivariant GNNs for materials science, and deep learning frameworks for genomic data. Advised over 20 students across PhD and master's levels, focusing on topics like neural networks, causal discovery, and generative models. Active in seminars and interdisciplinary collaborations, he co-leads the TAU team's research on machine learning and optimization.

• Numerical Methods for Partial Differential Equations
• Fractional Partial Differential Equations
• Inverse Problems
• +3 more

Abdallah BRADJI is a Full Professor of Mathematics at the University of Annaba-Algeria (since January 2015), affiliated with the Department of Mathematics in the Faculty of Sciences. He holds a PhD from Aix-Marseille University (2005) and a French Habilitation (HDR) from Aix-Marseille University (2016). His research focuses on numerical methods for partial/fractional PDEs, inverse problems, and computational modeling with COMSOL Multiphysics. He has held postdoctoral positions at the Weierstrass Institute (Berlin, Germany) and the Nečas Center (Prague, Czech Republic). Teaching roles include lecturing in undergraduate and graduate courses (e.g., Numerical Analysis, Finite Elements, Operational Research) since 1994, with recent responsibilities in Master’s programs in Metallurgy and Process Engineering. He has been invited as a Visiting Professor at Sorbonne University Paris Nord (2024) and LAGA Paris 13 (multiple visits), and has reviewed for prestigious journals like Comptes Rendus (CRAS) and ESAIM:M2AN. Research interests span numerical methods for fluid mechanics, fractional differential equations, and convergence analysis of finite volume/element schemes. His work emphasizes high-order accuracy and stability in complex applications.

Isabelle PuautView profile

Professor

• Real-Time Systems
• Computer Science
• Embedded Systems
• +3 more

Isabelle Puaut is a full professor at the University of Rennes I, affiliated with the IRISA research institute's PACAP group. Her research focuses on real-time systems, particularly Worst-Case Execution Time (WCET) estimation, distributed systems, and fault-tolerant architectures. She developed the open-source WCET estimation tool Heptane. She has held significant academic roles, including organizing major conferences like RTSS (2018 General Chair, 2017 PC Chair), ECRTS, and ISCA. Her career spans roles as a program committee member for numerous international conferences since 2000. She has supervised over 15 PhD students, with current advisees including Matthieu Rodet and Hector Chabot. Her HDR (Habilitation à Diriger des Recherches) was awarded in 2001. Teaching includes courses on low-level programming, real-time systems, and operating systems at the master's level.

Nicolas VAYATISView profile

Professor

• Machine Learning
• Healthcare Technology
• Theoretical Computer Science
• +3 more

Nicolas VAYATIS is a Professor at the Ecole normale supérieure Paris-Saclay, affiliated with the Centre Borelli and the Department of Mathematics (DER de Mathématiques). He holds an ELLIS Fellowship (Paris unit) and specializes in theoretical foundations of machine learning, with applications to healthcare and industrial systems. He teaches in programs such as the Master M2 MVA, the normalien DER mathématiques, and the AI track at ENS Paris-Saclay. His research focuses on statistical learning, domain adaptation, change-point detection, and graph signal processing. He has advised over 20 PhD/Master’s students, including notable names like Antoine de Mathelin and Charles Truong. His work bridges academic theory and practical applications, collaborating on projects like fall detection using smart floor sensors and gait analysis with inertial measurement units. He contributes to open-source tools like the ruptures library for change-point detection and the ADAPT domain adaptation toolbox. Key collaborations include projects with INSEAD, Université Paris-Saclay, and industry partners like Michelin. His research has been published in venues such as NeurIPS, ICML, and AISTATS, with a focus on robust algorithms and real-world impact.

Boris BarbourView profile

Researcher

• Neuroscience
• Computational Neuroscience
• Neurophysiology
• +4 more

Boris Barbour is a researcher at the École Normale Supérieure (IBENS) in Paris, France, where he leads the Neuronal Algorithms group. His work bridges cellular neuroscience , neural network modeling , and electrophysiology , with a focus on cerebellar function and synaptic plasticity. He teaches extensively in the Imalis master's program and contributes to international training courses in microelectrode techniques and optical imaging . Primary Affiliation: IBENS, École Normale Supérieure, Paris Teaching Roles: Organizes M1 course S10 (Synaptic Foundations of Network Function), contributes to M2 Neurophysiology practicals, and co-tutors interdisciplinary neuroscience projects His research explores ephaptic coupling in cerebellar Purkinje cells via the pinceau structure, combining in vitro , in vivo , and in silico approaches. Key themes include stochastic gradient descent algorithms in cerebellar learning, synaptic weight distributions , and non-synaptic inhibition mechanisms . He has developed open-source tools like a patch-clamp amplifier tutorial and optimized Arduino USB code for experimental setups. Barbour is a co-organizer of the Paris Spring School and actively contributes to PubPeer for post-publication peer review. His work is supported by the Agence Nationale de la Recherche (ANR) and has produced foundational studies on cerebellar network dynamics , ion channel distribution , and neuronal information processing . Collaborations span institutions in France, the UK, and Japan, with authorship on studies challenging paradigms in synaptic transmission and extracellular impedance research.

Elsa L GunterView profile

Research Professor

• Formal Methods
• Programming Languages
• Software Engineering
• +7 more

Elsa L Gunter is a Research Professor and Senior Lecturer at the University of Illinois at Urbana-Champaign's Department of Computer Science. Her academic background includes a Ph.D. in Mathematics from the University of Wisconsin, Madison. She leads research in formal methods, programming languages, and human-computer systems. Research Interests: Her work spans formal verification, programming language semantics, automated theorem proving, and security. She develops tools for compiler optimization verification, human-automation system safety, and concurrent program analysis. Key projects include the VeriF-OPT framework for parallel program transformations and Tutela for human-computer system protection analysis. Publications Focus: Her recent research emphasizes compiler verification, concurrency models, and human-system interaction. Work includes symbolic analysis for CSP, dependently-typed session systems, and robustness verification for safety-critical interfaces. Awards: Most Influential 10 Year Paper award at Requirements Engineering (RE 2010) EASST Best Software Science Paper at ETAPS 2001 Best Paper award at Fourth International Conference on Requirements Engineering (2000) Funding and Labs: Secured NSF grants for projects on parallel program verification ($450K) and human task analysis ($500K). Leads the Formal Methods and Verification Lab, collaborating with NASA on NextGen aviation systems. Student Advising: Mentored 7 PhD graduates and 12+ Master's students. Current PhD candidates work on secure distributed programming (Dennis Griffith) and formal methods for concurrent systems (Liyi Li, Susannah Johnson).

Nikita KovalView profile

Researcher

• Concurrent Programming
• Kotlin Coroutines
• Concurrent Data Structures
• +6 more

Nikita Koval is a Researcher at JetBrains , specializing in concurrent programming, Kotlin coroutines, and testing frameworks. His work bridges academic research with industrial application, focusing on synchronization primitives, lock-free data structures, and JVM-based concurrency tools. Academic rank: Researcher Affiliation: JetBrains Research interests include: Concurrent algorithm design and optimization Formal verification of synchronization mechanisms Testing frameworks for JVM-based languages Memory-efficient lock-free data structures Scalability in coroutine communication Distributed systems debugging Publication trends show a focus on Kotlin coroutines, JVM concurrency, and testing frameworks like Lincheck. His work spans algorithm design (union-find, queues), formal verification (CQS), and practical tools for concurrency testing (Lincheck) across conferences like PPoPP, PLDI, and ECOOP. Scientific recognition: Nikita received the Best Paper Award at OPODIS 2019 for his work on concurrent union-find algorithms. His contributions to Lincheck and CQS have been adopted into Kotlin's core libraries. Workshop leadership: He offers a 4-day corporate workshop on concurrent algorithms, covering testing, debugging, and implementation of lock-free data structures, now booked for Q3/Q4 2025. The curriculum includes hands-on Java/Kotlin coding with topics like segment queues, fetch-and-add queues, flat combining, and concurrent hash tables.

Oded PadonView profile

Assistant Professor

• Programming Languages
• Verification
• Formal Methods
• +4 more

Oded Padon is a Senior Scientist (≈Assistant Professor) at the Weizmann Institute of Science , affiliated with the Faculty of Mathematics and Computer Science . He joined Weizmann in September 2024 after prior roles as a researcher at VMware Research Group , a postdoc in Alex Aiken's group at Stanford University , and a PhD student at Tel Aviv University under Mooly Sagiv . Research Interests : Oded's work focuses on developing principled algorithms for automated verification of complex systems, particularly distributed protocols, storage systems, and cluster management. He emphasizes decidable logics, primal-dual methods, and decomposition techniques. His recent interests include verification of deep neural networks , quantum computing , and leveraging large language models for verification tasks. Key projects: Ivy (safety/liveness verification), mypyvy (invariant inference), Verus (Rust verification), TASO (deep learning optimization), Quartz (quantum circuit superoptimizer). Scientific Awards : Azrieli Early Career Faculty Fellowship 2020 ETAPS Doctoral Dissertation Award 2017 Google PhD Fellowship in Programming Languages Radhia Cousot Young Researcher Best Paper Award (SAS 2017) Publications span decidable verification, invariant inference, quantum optimization, and machine learning for verification. His work has received Jay Lepreau Best Paper Award at SOSP 2024 (Anvil) and Distinguished Paper Awards at POPL 2024 (An Infinite Needle) and OOPSLA 2023 (Leaf).

Peisen YaoView profile

Researcher

• Program Analysis and Verification
• Program Synthesis and Optimizations
• Logic and Automated Reasoning
• +2 more

Peisen Yao is an academic researcher affiliated with Zhejiang University in China. His work spans programming languages, software engineering, and cybersecurity, with a focus on developing techniques to enhance software security, usability, and performance. He actively contributes to premier conferences as a committee member (e.g., PLDI, ICSE, ASE, ISSTA, OOPSLA, SAS). Research Focus: Yao's research integrates program analysis, verification, synthesis, and optimization. Key areas include: Advanced static analysis for security vulnerabilities (e.g., buffer overflows, divide-by-zero errors) Efficient symbolic abstraction and SMT solver testing Context-sensitive program analysis using formal language theory Automated invariant generation and code synthesis Publication Trends: His 15 most recent articles (2021–2025) emphasize scalable program analysis techniques, security validation, and practical tools for industry applications. Common themes include static analysis optimizations, formal verification, and novel testing methodologies for complex systems.

KC SivaramakrishnanView profile

Assistant Professor

• Functional Programming
• Language Runtimes
• Concurrency
• +4 more

KC Sivaramakrishnan is an Assistant Professor at Indian Institute of Technology Madras and concurrently serves as CTO of Tarides. He works at the intersection of programming languages and systems, focusing on concurrency, distributed systems, and OCaml runtime development. Primary Affiliation: Indian Institute of Technology Madras Co-founder: Tarides His research explores: Concurrency and parallelism in OCaml Effect handlers for modular programming Mergeable Replicated Data Types for distributed systems Weak memory models and consistency guarantees Lock-free algorithms and safe multicore programming Recent publications focus on OCaml 5.0's concurrency features, effect handler integration, and verified CRDT implementations. He contributes to compiler design, runtime optimization, and testing frameworks for multicore systems. Service roles include committee memberships in SPLASH, ICFP, OCaml, and PROPL conferences. He actively bridges functional programming with systems research through practical implementations.

Daniel W. BarowyView profile

Associate Professor

• Programming Languages
• End-User Programming
• Spreadsheet Debugging
• +5 more

Daniel W. Barowy is an Associate Professor in the Department of Computer Science at Williams College . His research focuses on programming languages , particularly end-user programming , crowdsourcing , and spreadsheet debugging . He integrates program analysis with statistical techniques to improve software usability and robustness. Current affiliations: Williams College (2017-present) Education: University of Massachusetts Amherst (PhD, 2017) His research explores language abstractions for human-computer integration , with notable projects like ExceLint (spreadsheet error detection), FlashRelate (spreadsheet data extraction), and Riker (incremental build systems). He emphasizes artifact verification , securing PLDI 2015 Distinguished Artifact Award and USENIX ATC 2022 Best Paper . Recent publications demonstrate trends in spreadsheet reliability , crowdsourcing frameworks , and scalable educational tools . He has received "Artifact Verified" badges for multiple projects and actively contributes to software tool development , including AutoMan , ExceLint , and CheckCell . USENIX ATC 2022 Best Paper PLDI 2015 Distinguished Artifact Award Multiple "Artifact Verified" badges As an educator, he teaches CSCI 334: Principles of Programming Languages and CSCI 331: Computer Security . His work bridges theoretical PL research with practical applications in spreadsheet programming and crowdsourcing platforms .

Tiago CogumbreiroView profile

Assistant Professor

• Program Analysis
• GPU Programming
• Parallel Programming
• +5 more

Tiago Cogumbreiro is an Assistant Professor at the University of Massachusetts Boston, specializing in formal methods and high-performance computing. His research focuses on detecting concurrency errors like data-races and deadlocks in GPU programs, with a strong emphasis on static analysis and correctness proofs. PhD from University of Lisbon Postdoc at Georgia Tech and Rice University Research assistant at Imperial College London His work spans program analysis, GPU programming, and parallel computing, addressing challenges in concurrency verification and error localization. Key contributions include developing tools for static analysis of GPU kernels, formalizing automata theory in education, and creating frameworks for model checking hierarchical systems. Recent publications highlight trends in data-race detection via array projections, concurrency repair with resource cost analysis, and mechanized computational theory for educational purposes. His personal website details ongoing projects and affiliations with the Software Verification Lab .