جست‌وجوی استاد و پژوهشگر

Andrei-Constantin Braitorمشاهده پروفایل

پژوهشگر

• Control Engineering
• Power Systems
• DC Microgrids
• +۳ مورد دیگر

Andrei-Constantin Braitor is a researcher specializing in control engineering and power systems, with a focus on DC microgrids, stability analysis, and power electronics. His work addresses challenges in voltage stability, overvoltage/overcurrent protection, and control design for DC microgrids in hybrid electric aircraft and meshed networks. He has collaborated with notable researchers such as Houria Siguerdidjane and Alessio Iovine on projects involving droop control, admittance matrix computation, and consensus-based control algorithms. Research Interests: DC Microgrid Stability and Control Distributed Control Systems Power Electronics Integration Aerospace Power Systems Nonlinear Dynamics in Power Networks His recent publications (2020-2025) explore advanced hierarchical control frameworks, fault-tolerant designs, and educational applications of control engineering through animated cartoons. He has contributed to both theoretical stability analysis and practical control implementations in meshed and parallel-operated converter systems. No scientific awards, grants, or lab affiliations were explicitly mentioned in the provided texts. His student advising record is currently empty.

• Operational Research
• Scheduling
• Production Planning
• +۳ مورد دیگر

Mr. Jean-Charles Billaut is a Professor at the Polytechnic School of Tours (EPU) within the University of Tours, affiliated with the Computer Science Department and the Fundamental and Applied Computer Science Laboratory of Tours (LIFAT). His primary research focuses on Operational Research, particularly in scheduling theory, production planning, and logistics optimization, with notable contributions to healthcare and food supply chain systems. He has held leadership roles, including Director of the Computer Science Laboratory since 2007 and Editor-in-Chief of the European Journal of Operational Research since 2007. His work bridges theoretical advancements and real-world applications, addressing challenges in multi-agent scheduling, robust production systems, and emergency logistics. Key collaborations include optimizing chemotherapy production and medical sample dispatching, reflecting his commitment to impactful operational research. His research often employs metaheuristics and exact methods to solve complex scheduling and routing problems, emphasizing sustainability and resilience in supply chains.

Quentin Stiévenartمشاهده پروفایل

پژوهشگر

• Abstract Interpretation
• Concurrency
• Static Analysis

Quentin Stiévenart is a researcher at Université du Québec à Montréal, focusing on abstract interpretation, concurrency, and static analysis. His work spans programming language design, software verification, and tool development for WebAssembly and functional languages like Racket and Scheme. Active in organizing and reviewing for conferences including SPLASH, ICFP, ECOOP, and SAS Developed tools such as Wassail for WebAssembly static analysis and RacketLogger for educational purposes Contributions include theoretical work on effect-driven flow analysis and practical advancements in concolic execution abstraction His research addresses challenges in concurrency verification, cyclic reinforcement in incremental analysis, and security-focused taint tracking across multiple language paradigms.

• Parallel algorithms
• Distributed databases
• MapReduce model
• +۵ مورد دیگر

Mostafa BAMHA is an Associate Professor (Maître de Conférences) at the University of Orleans, affiliated with the LIFO Laboratory (Laboratoire d'Informatique Fondamentale d'Orléans). He leads research in parallel and distributed computing, focusing on MapReduce optimization , data skew handling , and scalable graph processing . Member of the PRV team (Parallelism, Virtual Reality, System Verification) Active in projects: HPIAF (High Performance computing for AI in Finance) INEx (Cloud Computing experiments) Girafon (Graph & BigData processing) Research Trends His publications from 2018–2024 show focus on: MapReduce optimizations for join operations and LSH similarity joins Graph processing challenges in Pregel with high-degree vertices Skew-insensitive algorithms across distributed architectures Academic Contributions Co-author in 15+ peer-reviewed publications (2000–2024) including International Journal of Parallel Programming , DEXA , and HLPP conferences. Key collaborators: Sébastien Rivault , Mohamad Al Hajj Hassan , Sophie Robert .

Tony LELIEVREمشاهده پروفایل

استاد

• Applied Mathematics
• Multiscale Modeling
• Molecular Simulation
• +۷ مورد دیگر

Tony Lelièvre is a Professor of Applied Mathematics at the Ecole Nationale des Ponts et Chaussées, part of the Institut Polytechnique de Paris. He holds a PhD (2004) and Habilitation (2009), specializing in multiscale modeling, molecular simulation, and stochastic processes. His research focuses on free energy computations, numerical analysis of complex fluids, and computational statistical physics. He co-authored two books and over 100 papers, receiving significant awards like the ERC Consolidator Grant (2013-2019) and the Grand prix Alcan. Lelièvre has organized numerous international workshops and serves on editorial boards of journals like ESAIM:M2AN and SIAM/ASA Journal of Uncertainty Quantification. His work bridges applied mathematics, numerical analysis, and computational science with applications in materials science and industrial fluid dynamics. Education: PhD in Applied Mathematics, 2004 Habilitation à Diriger des Recherches, 2009 Research Interests: Multiscale modeling of complex fluids Molecular dynamics and free energy calculations Stochastic methods for metastable systems Numerical analysis of PDEs and SDEs Computational statistical physics Recent Contributions: His work on adaptive biasing force methods and hybrid Monte Carlo techniques has advanced the simulation of rare events and free energy landscapes. He contributed to variance reduction techniques in molecular simulations and mathematical analysis of parallel replica algorithms. Awards: ERC Consolidator Grant (2013-2019), Prix CS 2002, Grand prix Alcan (2010), Ordway Visiting Professorship (2012-2013), and several teaching awards. Professional Activities: Organized major conferences like CEMRACS 2013 and IPAM Long Program on Energy Landscapes (2017). Co-edits journals and authored influential textbooks on magnetohydrodynamics and free energy computations.

• 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.

• Computer Science
• Parallel Computing
• Dynamic Programming
• +۳ مورد دیگر

Jerry Lacmou Zeutouo is a Lecturer in the field of Networks and Data at Université de Picardie Jules Verne (UPJV), contributing to computer science research through advanced algorithm development and optimization. His work primarily focuses on parallel computing, dynamic programming, and computational biology. Academic Rank: Lecturer at UPJV Institution: Université de Picardie Jules Verne Research Interests: Dr. Zeutouo specializes in designing and optimizing parallel algorithms for dynamic programming and database security. His research spans: Coarse-Grained Multicomputer (CGM) architectures K-anonymity in distributed databases RNA folding and bioinformatics applications Longest Common Subsequence (LCS) constraints Publication Trends: His work emphasizes solving computational bottlenecks via parallelism, particularly in cloud environments, bioinformatics, and database security. Key themes include: Transformer-based models for cold start mitigation in FaaS Multicomputer algorithms for dynamic programming Four-splitting and Four-Russians techniques for optimization

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

Laure Gonnordمشاهده پروفایل

استاد

• Static Analysis
• Compilation
• Software Engineering
• +۷ مورد دیگر

Laure Gonnord is a Full Professor in Computer Science at Grenoble INP , affiliated with the Esisar Engineer School in Valence, France, since September 2021. She is a member of the CTSYS research team at the LCIS laboratory and an external member of the CASH team at the University of Lyon / CNRS / LIP / Inria. Her research focuses on compilation , static analysis , and applications to safety , security in high-performance and embedded systems . Fields of Interest : Compiler Design Static Analysis for Safety & Security Abstract Interpretation Embedded Systems High-Performance Programming Hardware Security Engineering Research Trends (from recent publications): Her work explores modular verification through monadic abstract interpreters, complexity bounds in term rewriting , and educational tools for theorem proving . Notable contributions include compiler hardening schemes for hardware security and memory layout optimizations for algebraic data types. Academic Leadership : Scientific Director of the Summer School EJCP (École Jeune Compilation et Programmation) Board Member of the French national research group GDR GPL Teaching Responsibilities at Grenoble INP include courses in architecture , compilation , programming languages , algorithms , and databases . She has also taught at University of Lyon, ENS Lyon, Polytech'Lille, and INSA.

• 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.

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.