جست‌وجوی استاد و پژوهشگر

Anne BENOITمشاهده پروفایل

دانشیار

• High-Performance Computing (HPC)
• Multi-criteria scheduling algorithms
• Resource optimization
• +۴ مورد دیگر

Anne BENOIT is an Associate Professor of Computer Science at École normale supérieure de Lyon (ENS de Lyon), affiliated with the Parallel Computation Laboratory (LIP) and the ROMA project. She holds leadership roles, including Chair of the IEEE Technical Community on Parallel Processing (2020–2024) and IUF Senior Membership (2023–2028). Her research focuses on multi-criteria scheduling algorithms for HPC, addressing performance, cost, energy, and reliability challenges. She earned a PhD in Systems and Communications from INPG Grenoble (2003) and an HDR (2009). Research Interests : Her work integrates scheduling optimization, fault tolerance, and energy efficiency in HPC systems. She designs resilient protocols to manage failures and uncertainties, particularly in heterogeneous environments. Key topics include checkpointing strategies, workflow scheduling on edge platforms, and balancing conflicting optimization criteria. Awards & Roles : Senior Member of the Institut Universitaire de France (2023) Guest Professor at Georgia Tech (2017–2018) Associate Editor-in-Chief of Elsevier JPDC and ParCo IEEE Senior Member Professional Contributions : Chair of major conferences like IPDPS and HiPC. Authored A Guide to Algorithm Design (CRC Press, 2013). Leads the Computer Science Department at ENS Lyon since 2022. Labs & Projects : Active in the ROMA project (Resource Optimization) and the LIP laboratory, focusing on parallel computation and algorithmic efficiency.

Arthur Charguéraudمشاهده پروفایل

پژوهشگر

• Program Verification
• Separation Logic
• Interactive Theorem Proving
• +۸ مورد دیگر

Arthur Charguéraud is a senior researcher (Directeur de Recherche) at Inria, based in Strasbourg within the Camus team, affiliated with the iCube laboratory at Université de Strasbourg. His research spans program verification, program optimization, and mechanized semantics of programming languages, with a strong focus on separation logic and interactive theorem proving using Coq. Affiliation: Inria, Camus team, iCube Laboratory, Université de Strasbourg Position: Senior Researcher (Directeur de Recherche) Research Focus: Formal verification, separation logic, source-to-source transformations, high-performance computing His research interests center on developing formal methods to ensure correctness and efficiency in software systems. He works extensively on separation logic to verify both time and space complexity of programs, especially in the presence of garbage collection. His work bridges theoretical foundations with practical tools, such as the CFML framework and the OptiTrust optimization framework, which enables trustworthy source-to-source transformations with formal guarantees. His publications reveal a consistent focus on interactive verification, formal semantics, and performance optimization. Key themes include granularity control in parallelism, mechanized semantics (e.g., for JavaScript), and verified compilation. He has made significant contributions to separation logic, including extensions for time and space credits, big-O reasoning, and higher-order representation predicates. Arthur Charguéraud has received notable recognition for his work, including: Distinguished Paper Award at CPP 2022 SIGPLAN Research Highlight at PPoPP 2019 He has advised several PhD students and postdoctoral researchers, including Guillaume Bertholon, Alexandre Moine, and Armaël Guéneau. He leads the ANR-funded OptiTrust project (2022–2027), which aims to build a framework for verified source-to-source optimizations. He has also been involved in other major projects such as ANR VOCAL, ANR AJACS, and ERC DeepSea. His work is supported by both national (ANR, Inria) and institutional (CEA, ENS) grants. He is actively involved in the programming languages research community, serving on the program committees of top conferences including POPL, ICFP, PLDI, CPP, and CoqPL, and has chaired several workshops. He is also engaged in education and outreach, co-authoring the book Separation Logic Foundations in the Software Foundations series and designing challenges for the Concours Castor Informatique to promote computer science among young students.

• Network Protocol Validation
• Formal Methods in Software Engineering
• Mobile and Wireless Networks (MANETs/IoT)
• +۳ مورد دیگر

Stéphane MAAG is a Professor at Telecom SudParis, associated with the SAMOVAR research laboratory. His work focuses on formal methods for protocol validation, network security, and distributed systems monitoring. He has contributed to advancing testing methodologies for mobile ad-hoc networks (MANETs), IoT protocols, and wireless communication systems. His research integrates machine learning techniques for automation and has been applied to web testing frameworks and ERP systems. Key research areas include protocol performance evaluation, trust management in networks, and curriculum design for computer science ethics. His work spans both academic surveys (e.g., European ethics education studies) and technical innovations (e.g., proactive interoperability solutions for wireless routing). Publications emphasize practical applications of formal methods, with over 50 peer-reviewed articles in journals like International Journal of Ethics Education , Computer Communications , and IEEE Transactions . His work bridges theoretical foundations with real-world systems like ODOO ERP and SIP protocols.

Soon Myoung Chungمشاهده پروفایل

استاد

• Cloud Computing Security
• Hypervisor Security
• Parallel Computing
• +۸ مورد دیگر

Soon Myoung Chung is a computer science researcher with significant contributions in the areas of cloud computing security, parallel data clustering, and GPU-accelerated algorithms. The publications indicate long-standing research activity spanning from 2002 to at least 2022, suggesting sustained academic engagement. While no formal institutional affiliation is provided in the scraped content, the depth and consistency of work imply a faculty or research-oriented academic role. The research interests center around cloud security , especially hypervisor vulnerabilities and isolation breaches, parallel and distributed clustering algorithms for large-scale data, and 3D shape analysis using orthogonal moments. These fields reflect a strong focus on algorithmic efficiency, security in virtualized environments, and pattern recognition. The most recent articles show a trend toward leveraging GPU acceleration for real-time data processing in crisis management and enhancing anomaly detection in time series data. Earlier works emphasize foundational methods in association rule mining, text clustering, and combinatorial fusion for feature selection. Collectively, the publications demonstrate expertise in both theoretical algorithm design and practical implementation in high-performance computing contexts. Although no scientific awards are mentioned in the provided texts, the body of work has accumulated over 1,800 citations, indicating influence in the field. There is no information available about students advised, grants received, or leadership roles. No labs or collaborative teams are referenced in the scraped material.

Stéphan Thomasséمشاهده پروفایل

استاد

• Graph Theory
• Combinatorics
• Algorithms
• +۳ مورد دیگر

Stéphan Thomassé is a Professor in the Computer Science Department at Ecole Normale Supérieure de Lyon, where he is affiliated with the Parallel Computing Laboratory (LIP) and leads the Computational Models, Complexity, Combinatorics (MC2) research team (2023-2025). He was a Member of the University Institute of France from 2016-2021 and has held significant administrative roles including Head of M2 Fundamental Computer Science (2013-2015) and Deputy Director of the Computer Science Department (2013-2015). Thomassé's research focuses on graph theory, combinatorics, algorithms, and theoretical computer science. His work spans structural graph theory , parameterized complexity , graph coloring , and combinatorial optimization . He is particularly known for his groundbreaking work on twin-width, a graph parameter that has revolutionized understanding of sparse and dense graph classes and their algorithmic properties. His research connects combinatorial structures with computational complexity, often bridging theoretical insights with practical algorithmic applications. His recent publications demonstrate a strong focus on structural graph theory, with the twin-width series representing a major contribution to the field. These papers have established connections between graph parameters, model theory, and algorithm design, particularly for problems that were previously thought to be intractable on dense graph classes. Thomassé's work on graph coloring, particularly regarding dense triangle-free graphs and the Erdős-Hajnal conjecture, has resolved long-standing open problems. Member of University Institute of France (2016-2021) ANR projects: GRAAL, AGAPE, STINT, COMPA, Digraphs, TWIN-WIDTH, GODASse As an advisor and educator, Thomassé has taught numerous advanced courses including Algorithmics, Optimization and Approximation, Tree Decompositions and FPT Algorithms, and Graph Decompositions. His teaching reflects his research expertise, emphasizing both theoretical foundations and practical applications of discrete mathematics. His administrative leadership in the MC2 team and the Computer Science Department demonstrates his commitment to advancing research and education in theoretical computer science. Thomassé maintains active collaborations with researchers worldwide, as evidenced by his extensive publication record with co-authors from various institutions. His work continues to shape the landscape of structural graph theory and parameterized algorithms, with recent results opening new avenues for research in combinatorics and theoretical computer science.

Florent Ginhouxمشاهده پروفایل

پژوهشگر

• Myeloid Cell Biology
• Cancer Immunology
• Tumor Microenvironment
• +۴ مورد دیگر

Florent Ginhoux is a Researcher at Gustave Roussy 's Tumor Immunology and Cancer Immunotherapy Program (U1015). He leads the Florent Ginhoux Laboratory (ginhouxlab.com), focusing on myeloid cell biology in cancer progression and immunotherapy development. His team integrates spatial transcriptomics (Visium HD, Xenium), single-cell RNA sequencing , and MACSIMA spatial proteomics to dissect tumor-immune interactions. His research spans pediatric oncology (brain tumors, neuroblastomas, sarcomas) and adult cancers (pancreatic, head/neck carcinomas). Key projects include Developing iPSC-derived macrophages for patient-specific tumor modeling Characterizing TREM2+ multinucleated macrophages as prognostic indicators Creating MoMac-VERSE and DC-VERSE compendiums for cross-tissue myeloid cell analysis His lab collaborates with pediatric oncologists and bioinformaticians on projects funded by 2024 Fight-Kid Cancer grant ( MiMiC-Kids ) 2024 ANR Excellence Chair ( MATCH ) 2024 Horizon HIT-GLIO grant 2021 INCa PEDIAHRG High-Risk/High-Gain program

Liana Ermakovaمشاهده پروفایل

مدرس

• Natural Language Processing
• Information Retrieval
• Artificial Intelligence

Liana Ermakova is a Lecturer in Computer Science at Université de Brest , associated with the research group Heritage and Creation in Text and Image (HCTI, EA 4249) . Her work focuses on Natural Language Processing , Information Retrieval , and Artificial Intelligence . Doctorate in Computer Science (2016) from the Toulouse Computer Science Research Institute (IRIT) with distinction Her research bridges computational methods and humanistic approaches, particularly through projects like JOKER (humour/wordplay translation) and SimpleText (scientific text simplification). Key publication themes include: Query expansion and tweet contextualization Humour recognition in multilingual contexts Scientific text simplification for non-experts Analysis of medical and pandemic-related discourse Evaluation metrics for summarization LLM reliability in scientific information access She actively contributes to the CLEF Association workshops and publishes in top IR/NLP venues. Current projects examine: Overcoming LLM hallucinations in scientific search Automated complexity spotting in abstracts Contextualization of short texts

Ningning Xieمشاهده پروفایل

پژوهشگر

• Functional Programming
• Type Systems
• Logics
• +۳ مورد دیگر

Ningning Xie is a researcher affiliated with the University of Toronto, specializing in functional programming, type systems, and logics. Their work spans applications in compilers, code generation, and machine learning, with a focus on compositional programming and effect handling. Research interests include: Functional programming Type systems Logics Compiler design Multi-stage programming Effect handlers Recent publications demonstrate expertise in type-level programming, staged compilation, and effect systems. Key areas include distributive disjoint polymorphism, parallel algebraic effect handlers, and macro systems for OCaml and Haskell. Their work bridges theoretical formalisms with practical language implementations. Contributions to academic service include organizing and reviewing for conferences like POPL, PLDI, ICFP, and Haskell workshops. Notable roles include Publicity Chair for POPL 2026 and Co-chair for PLMW and Artifact Evaluation committees.

• Programming Languages
• Logic and Type Theory
• Logical Frameworks
• +۵ مورد دیگر

Frank Pfenning is a Professor in the Department of Computer Science at Carnegie Mellon University's School of Computer Science. With decades of active research and service in programming languages and logic communities, he maintains a significant presence across major conferences including POPL, ICFP, and ESOP. His research spans foundational work in Programming Languages , Logic and Type Theory , Logical Frameworks , Automated Deduction , and Trustworthy Computing . Recent publications reveal a strong focus on session types, substructural logics, and their applications to concurrency and distributed systems. His work bridges theoretical foundations with practical implementations for reliable communication protocols. Analysis of his publication trends shows a consistent evolution from foundational type theory toward practical applications in concurrent and distributed systems. The integration of logical frameworks with session types represents a signature research trajectory, increasingly addressing real-world challenges in protocol verification and deadlock freedom. As an active community member, Pfenning has served on numerous program committees including POPL (2016-2025), ICFP (2015-2022), and ESOP. His mentoring activities include PLMW@POPL presentations, demonstrating commitment to training next-generation researchers. His technical contributions are primarily disseminated through premier venues in programming languages research. The absence of explicit grant information in available sources suggests focus on theoretical contributions rather than large-scale funded projects, though his sustained conference participation indicates stable institutional support.

Fabienne JÉZÉQUELمشاهده پروفایل

مدرس

• Numerical algorithms
• High-performance computing
• Numerical validation

Fabienne JÉZÉQUEL is a Lecturer in Computer Science at Paris-Panthéon-Assas University, affiliated with the Sorbonne University Computer Science Laboratory (LIP6) and leading the PEQUAN (Performance and Quality of Digital Algorithms) team. Her research focuses on Numerical algorithms , High-performance computing , and Numerical validation , with applications in precision control and simulation reliability. Habilitation to Supervise Research (HDR) in Computer Science, University of Paris 6 (2005) Doctorate in Computer Science, University of Paris 6 (1996) Research Themes : Numerical algorithms with dynamic precision control High-performance computing (HPC) reliability and reproducibility Stochastic arithmetic for error estimation GPU acceleration of numerical methods Recent Publications : Focus on compensated algorithms, half-precision validation, and numerical reproducibility in extreme-scale simulations. Notable contributions include advancing stochastic arithmetic for trustworthy HPC codes and optimizing CADNA for GPU performance. Administrative Roles : Member of the office of the department of economic sciences at Paris-Panthéon-Assas University Member of the LIP6 Scientific Council

• Hyperspectral Imaging
• Machine Learning
• Low-rank Matrix Approximation
• +۲ مورد دیگر

Kinan Abbas is a researcher at the University of Strasbourg's College of Science and Engineering, Department of Computer Science, specializing in hyperspectral imaging and machine learning. His work focuses on spectral image processing techniques including unmixing, demosaicing, and low-rank matrix approximation. His research interests center on hyperspectral imaging and machine learning applications, particularly developing novel methods for snapshot spectral image processing. Key contributions include locally-rank-one-based joint unmixing frameworks, diffusion models for texture synthesis, and entropy-weighted spectral deconvolution techniques. His work bridges theoretical signal processing with practical applications in remote sensing and computational photography. Analysis of his publication trend (2021-2025) shows evolution from foundational spectral unmixing techniques toward advanced generative models, with increasing focus on diffusion-based synthesis and multifractal analysis. His research consistently addresses computational challenges in spectral image reconstruction. Abbas actively collaborates with researchers from ICube laboratory (Strasbourg), including Matthieu Puigt, Gilles Delmaire, and Gilles Roussel, evidenced by consistent co-authorship across 14 publications. His work appears in IEEE Transactions, ICASSP, and French GRETSI conferences, indicating strong institutional support for his research program.

Ghigliotti Giovanniمشاهده پروفایل

مدرس

• Multiphase Fluid Dynamics
• Numerical Simulation
• Heat Transfer
• +۳ مورد دیگر

Giovanni Ghigliotti is a Lecturer and researcher at the University of Grenoble Alpes since 2014, affiliated with the LEGI laboratory (UMR 5519). He is part of the MOST team, specializing in Turbulence Modeling and Simulation. His research focuses on multiphase fluid dynamics, particularly phase-change phenomena like boiling and cavitation, with an emphasis on numerical simulation to study hydrodynamic interactions, wetting, and material deformation. He holds a PhD in Fluid Mechanics from Joseph-Fourier University (2010). His work spans cavitation erosion mechanisms, fluid-structure interaction modeling, and heat transfer in multiphase systems. He contributes to the development of the Yales2 code, a parallel numerical simulation tool for complex flows. In teaching, he leads the Energy pathway of the Master's program in Process Engineering at Grenoble Alpes, instructing fluid mechanics, numerical methods, and thermodynamics. His research also involves collaborations with the GIS SUCCESS group, advancing high-performance computing and turbulence modeling. Key research themes include: Boiling crisis dynamics and thermal insulation effects Cavitation bubble collapse and material erosion Centrifugal microencapsulation process analysis Fluid-structure interaction in multiphase flows Unstructured grid simulations for phase change phenomena His recent publications (2024-2019) demonstrate expertise in non-Newtonian fluid simulation, cavitation erosion mechanics, and advanced computational methods for multiphase systems.

Thierry Weilمشاهده پروفایل

استاد

• Industrial Economics
• Innovation Management
• Technology Management
• +۳ مورد دیگر

Thierry Weil is a Professor of Economics at the CERNA (Centre d’économie industrielle) within MINES ParisTech - PSL. He holds a PhD in Solid-State Physics and has held multiple roles in academia, government, and industry. His research focuses on innovation management, industrial economics, and technology policy. He led the FutuRIS prospective study on France’s research and innovation system, advised the Prime Minister’s cabinet on technology and IP policy, and contributed to the creation of the Fabrique de l'Industrie think tank. Education: PhD in Physics, University of Paris-Dauphine Habilitation Key Roles: Deputy Director of MINES ParisTech, FutuRIS Director, Member of CCRRESTI, Founder of Observatoire des Pôles de Compétitivité His research explores innovation ecosystems, open innovation practices, and policy impacts on industry. He has authored over 100 publications, including books on leadership, innovation, and industrial strategy. His work bridges academic insights with practical applications in corporate strategy and public policy. Publications highlight themes like Silicon Valley's 'coopetition' dynamics, French competitiveness clusters, and leadership in organizations. He advises firms like EDF and Thales, and chairs seminars on technology management with industry leaders. Grants & Labs: Involved in ANRT-funded studies, member of key innovation observatories Teams: Founded and chairs the Journal de l'Ecole de Paris du Management, co-leads monthly management seminars

Éric Fleuryمشاهده پروفایل

استاد

• Parallel Algorithms
• Wireless Networks
• Distributed Algorithms
• +۴ مورد دیگر

Éric Fleury is a Professor at École Normale Supérieure de Lyon and a member of the Laboratoire de l'Informatique du Parallélisme (LIP), where he co-leads the DANTE team with Inria. His career spans parallel computing, distributed algorithms, wireless networks, and dynamic network modeling. He completed his PhD in 1996, followed by postdocs at the University of Michigan and Inria Nancy, before joining INSA Lyon and leading the Inria ARES team. His recent research focuses on community detection in social and sensor networks, including a Facebook experiment on cohesion metrics and the MOSAR project analyzing hospital contact dynamics. Education: PhD in Computer Science (1996), postdoctoral work at University of Michigan (McKinley) and Inria Nancy (Schaff). Research Interests: He investigates network structures, communication protocols, and sociological impacts on network topology. His work bridges algorithmic foundations with real-world applications like wireless service deployment and hospital network dynamics. Key Projects: MOSAR hospital contact tracking (6-month study), cohesion metric development for community analysis, and leadership in the DANTE and ARES research teams.

• Computational Mathematics
• Wave Propagation
• Numerical Analysis
• +۳ مورد دیگر

Aurélien Citrain is a researcher at Inria's MAGIQUE-3D project team, focusing on computational methods for wave propagation. He completed his PhD in Applied Mathematics at INSA Rouen (2016–2019), where he studied the coupling of Discontinuous Galerkin (DGM) and Spectral Element Methods (SEM) for elasto-acoustic wave problems. His work emphasizes hybrid mesh discretizations to optimize simulations in complex geometries. Affiliation: Inria (MAGIQUE-3D team), part of the Depth Imaging Partnership (DIP) with TOTAL Education: PhD in Applied Mathematics (INSA Rouen, 2019), Engineering Master (INSA Rouen), Research Master in Fundamental/Applied Mathematics (University of Rouen) Research Interests: Development of high-order numerical methods for seismic wave simulation, including coupling DGM/SEM on hybrid meshes, parallel computing with OpenMP, and software implementation for geophysical applications. His work addresses challenges in anisotropic media, attenuation modeling, and DAS (Distributed Acoustic Sensing) acquisition systems. Publications: Active contributor to conferences like MATHIAS, WAVES, and computational mechanics symposiums, with a focus on DG-SE coupling for elasto-acoustic systems and seismic monitoring innovations.