جستجوی استاد راهنمای دانشگاهی

Olivier FARGESمشاهده پروفایل

مدرس ارشد

• Thermal Engineering
• Energy Systems
• Fluid Dynamics
• +۳ مورد دیگر

Olivier FARGES is a Senior Lecturer and HDR (Habilitation à Diriger des Recherches) holder at the University of Lorraine, affiliated with ENSGSI (École Nationale Supérieure de Géologie et Sciences Industrielles) within the Groupe INP. He serves as Director of Industrial Partnerships at ENSGSI and is part of the LEMTA Laboratory (CNRS-University of Lorraine), focusing on multiphysics and multiscale modeling of heat transfer in complex environments. His academic roles include teaching courses such as Heat and Mass Transfer, Fluid Mechanics, Scientific Computing Modeling, and Renewable Energy. Dr. FARGES holds a Ph.D. in Energy and New R&D (2014) and an Engineering degree in Energy Engineering (2010), both from the École de Mines Albi. His research emphasizes coupled conductive-radiative heat transfer in porous media, thermal property characterization of heterogeneous materials, and Monte Carlo-based computational methods for energy systems. He has contributed to advancements in photovoltaic system modeling, solar thermal power optimization, and urban climate studies. His work bridges theoretical and applied thermal engineering, with applications in sustainable energy systems, material science, and industrial partnerships. Key research themes include radiative transfer modeling, multiphysics simulation frameworks, and the development of innovative tools for thermal property measurement and energy performance assessment.

Andrzej Murawskiمشاهده پروفایل

استاد

• Semantics of Programming Languages
• Automata Theory
• Software Verification
• +۴ مورد دیگر

Andrzej Murawski is a Professor of Computer Science at the University of Oxford and a Tutorial Fellow at Worcester College . His research focuses on the semantics of programming languages and software verification, with applications in automata theory, probabilistic computation, and concurrency. Current affiliations: University of Oxford, SIGLOG Vice-Chair, FoSSaCS Steering Committee Research interests: Game semantics, higher-order recursion, probabilistic systems, differential privacy Recent publications address probabilistic verification, equivalence checking, and game semantics for concurrent systems. He has chaired program committees for conferences such as ESOP and PERR, and his work has earned recognition like the POPL 2025 Distinguished Paper Award . Current students : Benedict Bunting, Haoxuan Yin Past students : Conrad Cotton-Barratt, David Hopkins, Guanyan Li, Dominik Wagner, Fabian Zaiser

Alberto Santiniمشاهده پروفایل

دانشیار

• Operational Research
• Transportation Systems
• Logistics Optimization
• +۵ مورد دیگر

Alberto Santini is an Associate Professor of Operational Research and a Ramon y Cajal fellow at Universitat Pompeu Fabra in Barcelona, Spain. He is also an affiliate professor at the Barcelona Graduate School of Mathematics and the Data Science Centre at the Barcelona School of Economics. During 2025-2027, he coordinates the Transportation group of the Spanish O.R. Society. His research focuses on optimization methods applied to transportation, logistics, and sustainability, including scheduling, vehicle routing, and heuristic algorithms. He has contributed to solving complex problems like last-mile delivery integration with public transport, airline flight scheduling, and energy-efficient vertical farming. His work often employs advanced techniques like column generation and decomposition strategies. Notable contributions include decomposition strategies for vehicle routing heuristics and the application of metaheuristics such as Adaptive Large Neighbourhood Search (ALNS). He is the founder of EUROYoung and AIROYoung, youth branches within prominent operational research societies. His GitHub repositories, such as cvrp-decomposition , provide open-source implementations of his algorithms. Santini’s research addresses real-world challenges like epidemic resource allocation and sustainable logistics, reflecting his commitment to both theoretical and applied operational research. Awards: Ramon y Cajal Fellow Labs/Teams: Leads Transportation group (Spanish O.R. Society), Founded EUROYoung/AIROYoung.

Nofar Carmeliمشاهده پروفایل

پژوهشگر

• Database Query Optimization
• Fine-Grained Complexity
• Enumeration Complexity
• +۲ مورد دیگر

Nofar Carmeli is a researcher at Inria , affiliated with the Boreal joint project-team (LIRMM, Inria, University of Montpellier, CNRS) in Montpellier, France. Her work focuses on theoretical aspects of database query optimization, particularly through the lenses of fine-grained complexity and enumeration complexity. PhD from Technion (2015-2020), advised by Prof. Benny Kimelfeld Postdoctoral Researcher at ENS Paris (2021-2022) and Inria's Valda project-team Holds the Schmidt Postdoctoral Award (2021-2022) Her research explores optimal algorithms for database query answering, including direct access to ranked answers, quantile computation, and handling of conjunctive queries with self-joins or negation. She investigates how structural properties of queries and data constraints like functional dependencies affect computational complexity. Key contributions include: Establishing tractability boundaries for direct access to conjunctive queries Developing efficient algorithms for minimal triangulation enumeration Advancing probabilistic database representations for infinite domains Creating explainable opinion graph frameworks for review summarization Scientific awards: Google PhD Fellowship (2019) Schmidt Postdoctoral Award (2021-2022) PODS Best Student Paper (2019) She has served on program committees for STACS (2025), PODS (2023-2025), and ICDT (2022-2024), and contributed to open-access research dissemination through Arxiv and dblp.

• Linguistics
• Dialogue Semantics
• Pragmatics
• +۴ مورد دیگر

Jonathan Ginzburg is a Researcher in the Department of Linguistics at Université Paris Diderot, affiliated with the CLILLAC-ARP research group. His work bridges linguistics, cognitive science, and computational models, focusing on dialogue semantics, pragmatic functions, and developmental language acquisition. Education details are not explicitly provided in the text, but his research spans formal semantics, syntax, and multimodal interaction. His studies on laughter dynamics and infant communicative behaviors have advanced understanding of pragmatic functions in early development. Key research interests include dialogue structure, question-response systems, and the integration of cognitive science with linguistic theory. Recent work explores neural correlates of language processing through type-theoretical semantics and corpus-based methodologies. He has pioneered the analysis of non-sentential utterances and their role in social interaction. His contributions to dialogue systems design for low-resource languages and the DUEL corpus (analyzing disfluencies, exclamations, and laughter) reflect his interdisciplinary approach. Current projects investigate laughter's pragmatic functions across developmental stages and cross-linguistic variations in exclamatory constructions. Laboratory affiliations include the CLILLAC-ARP laboratory, where he develops computational tools for analyzing dialogue semantics and cognitive interactions. His work on 'response spaces' for questions integrates machine learning and formal pragmatics to model conversational coherence.

Nabil Kahaleمشاهده پروفایل

دانشیار

• Financial Derivatives
• Monte Carlo Methods
• Optimization
• +۳ مورد دیگر

Nabil Kahale is an Associate Professor of Finance at ESCP Business School in Paris. His research focuses on financial derivatives, Monte Carlo methods, optimization, and machine learning. He holds a PhD in theoretical computer science from MIT (1993) and an HDR (French habilitation) from Université Paris 1 Panthéon-Sorbonne (2020), enabling him to supervise PhD students. His academic career includes prior roles in theoretical computer science and consulting for banks. He has published widely in top journals such as Mathematical Finance , Management Science , and SIAM Journal on Computing . Education: Bachelor of Science in Engineering, École Polytechnique (1987) PhD in Theoretical Computer Science, MIT (1993) HDR in Economics, Université Paris 1 Panthéon-Sorbonne (2020) Research Interests: His work bridges finance and computational methods, emphasizing practical applications of stochastic models and algorithmic efficiency. Key areas include derivative pricing, risk management, and the integration of machine learning into financial systems. Professional Contributions: He has served as a consultant for banking institutions and a referee for the French Ministry of Economy and Finance. His research also intersects with social and economic policy analysis, such as evaluating the economic impact of public health measures. Labs/Teams: While no specific lab affiliation is mentioned, his collaborations span interdisciplinary teams in finance, computer science, and applied mathematics through his publications and consulting work.

• Cellular Automata
• Computational Dynamics
• Theoretical Computer Science
• +۴ مورد دیگر

Martin Delacourt is a Lecturer at the University of Orléans, affiliated with the LIFO (Laboratoire d'informatique fondamentale d'Orléans). He earned his PhD on December 5, 2011, under the joint supervision of Bruno Durand and Victor Poupet at LIF Marseille. His research focuses on cellular automata, including directional dynamics, limit sets, and decidability of computational problems. PhD: University of Montpellier 2 (2011) ENS Lyon: Bachelor (2006), Master (2008) His research explores cellular automata through computational complexity, symbolic dynamics, and formal verification. Key themes include limit set characterization, defect dynamics, and algorithmic properties of number systems. He has published in conferences like AUTOMATA, MFCS, and CiE. Teaching responsibilities include courses in network engineering, computability, complexity theory, operating systems, and algorithm analysis at the University of Orléans. He has supervised work-study students in the MIAGE program since 2018.

• Signal Processing
• Statistical Signal Analysis
• High-Dimensional Data Analysis
• +۳ مورد دیگر

Pascal Vallet is an Associate Professor at University of Bordeaux, affiliated with IMS Bordeaux (Integration Laboratory from Material to System) where he conducts research in the Signal and Image Processing group and Spectral team. His work focuses on theoretical and applied aspects of statistical signal processing with emphasis on high-dimensional data analysis. Vallet's research interests center on statistical signal processing methodologies, particularly in high-dimensional settings. His work addresses fundamental problems in covariance matrix analysis, spectral coherence, and change detection within Gaussian models. He develops theoretical frameworks for analyzing complex signals with applications in areas such as SAR imaging and multivariate time series analysis. His approach combines rigorous mathematical statistics with practical signal processing applications, focusing on scenarios where dimensionality challenges traditional statistical methods. Analysis of Vallet's recent publications reveals a consistent research trajectory focused on high-dimensional statistical signal processing. His work primarily addresses covariance structure analysis in Gaussian low-rank models, with applications to SAR imaging and multivariate time series. The publications demonstrate increasing sophistication in handling high-dimensional asymptotic regimes where both sample size and dimensionality grow large. His research shows strong theoretical foundations combined with practical validation through synthetic and real-world data experiments, particularly in radar imaging applications. Vallet maintains active research collaborations with several colleagues including Rémi Beisson, Audrey Giremus, Guillaume Ginolhac, and Philippe Loubaton, as evidenced by his co-authored publications across multiple years. His research contributes to advancing theoretical understanding of statistical signal processing in high-dimensional settings while maintaining relevance to practical applications in remote sensing and signal analysis.

• Formal Methods
• Verification
• Model Checking
• +۴ مورد دیگر

Nathalie Bertrand is an Inria Researcher and Head of the DEVINE team at Inria Centre Rennes and IRISA lab. She co-heads the working group on Verification of the GDR IFM of the CNRS with Pierre-Alain Reynier, and co-leads the gender equality commission of IRISA and Inria Rennes with Elisa Fromont. She is also an active member of the Inria committee on gender equality and equal opportunity. PhD from ENS Cachan (October 2006) 1-year post-doc at TU Dresden Hired as Inria researcher (October 2007) Habilitation (HDR) from University Rennes 1 (November 2015) Dr. Bertrand's research focuses on formal methods, verification, model checking, parameterized systems, quantitative models, automata, and games. Her work bridges theoretical computer science with practical applications in distributed systems, probabilistic verification, and game theory. She develops efficient model-based formal methods to verify and enforce functional and non-functional properties of dependable distributed systems that include quantitative aspects such as time, cost, or probabilities. Her recent publications demonstrate a strong trend toward parameterized verification of distributed algorithms, probabilistic systems, and game-theoretic approaches to verification problems. Her research has evolved from foundational work on timed automata and probabilistic systems to increasingly complex problems involving distributed algorithms with arbitrary numbers of participants, blockchain consensus, and randomized fault-tolerant systems. Dr. Bertrand serves on the editorial boards of JLAMP and TCS, and has been a program committee member for numerous prestigious conferences including STACS, TACAS, Concur, QEST, LICS, FoSSaCS, ICALP, MFCS, and many others. She has co-chaired program committees for Formats'20, QEST'17, QAPL'14, and QAPL'15. As an advisor, she has supervised numerous PhD students including Nicolas Waldburger, Bastien Thomas, Suman Sadhukhan, Anirban Majumdar, Engel Lefaucheux, Paulin Fournier, and Amélie Stainer. She currently supervises postdoc Gaëtan Staquet and PhD candidates Pranav Ghorpade, Luca Paparazzo, and Luc Lapointe. She leads the DEVINE project-team (created January 2024), which focuses on developing efficient model-based formal methods to verify and enforce properties of dependable distributed systems with quantitative aspects. Previously, she was part of the SUMO team. Her current projects include ANR MAVeriQ (2021-2025), ANR BISouS (2022-2025), and ANR PaVeDyS (2024-2028).

Amin Mesmoudiمشاهده پروفایل

دانشیار

• Data Engineering
• Machine Learning
• Anomaly Detection
• +۵ مورد دیگر

Amin Mesmoudi serves as Associate Professor in Data Engineering at the University of Poitiers' IUT (Institut Universitaire de Technologie), with dual laboratory affiliations at LIAS-ENSIP (Poitiers campus) and LIAS-ISAE-ENSMA (Chasseneuil campus). His research bridges theoretical database systems with practical large-scale data engineering challenges, particularly in semantic web technologies and machine learning applications. The laboratory maintains physical presences at both ENSIP's Bâtiment B25 in Poitiers and ISAE-ENSMA's Téléport 2 facility in Chasseneuil, facilitating cross-institutional collaboration. Mesmoudi's research program centers on scalable data management systems, with three interconnected pillars: (1) RDF and graph-based query optimization techniques for billion-triple datasets, (2) machine learning integration for spatial query performance and anomaly detection, and (3) explainability frameworks for complex black-box models. His work demonstrates consistent evolution from foundational database systems (2011-2016) toward contemporary AI-driven data engineering, particularly evident in his 2023-2025 publications on temporal dependency preservation and co-selection explainability. The Data Engineering team within LIAS laboratory provides the primary research context for these investigations. Publication analysis reveals strong methodological continuity in addressing scalability bottlenecks across database paradigms. Early work focused on SQL-on-MapReduce benchmarking for astronomy databases (2015-2016), transitioning to specialized RDF processing frameworks (2019-2021), and culminating in current hybrid approaches combining temporal modeling with machine learning (2023-2025). Key technical themes include fragmentation strategies for distributed data, optimizer feedback mechanisms, and graph-based query acceleration - all targeting real-world performance constraints in big data environments. As a core member of LIAS laboratory's Data Engineering team, Mesmoudi contributes to France's national research infrastructure in computer science and automation systems. The laboratory's dual-university structure enables unique cross-pollination between University of Poitiers' academic programs and ISAE-ENSMA's engineering specialization, with Mesmoudi's work exemplifying this synergy through applications spanning astronomy databases to wireless sensor networks.

Sylvain Lombardyمشاهده پروفایل

استاد

• Automata Theory
• Formal Languages
• Theoretical Computer Science
• +۳ مورد دیگر

Sylvain Lombardy is a Professor at the University of Bordeaux, affiliated with the Laboratoire Bordelais de Recherche en Informatique (LaBRI) and the Enseirb-Matmeca engineering school within the Institut Polytechnique de Bordeaux. His research focuses on automata theory, formal languages, and theoretical computer science, particularly in weighted automata, formal methods, and algebraic properties of automata. He leads the Formal Methods research team at LaBRI and contributes to projects like the Awali and Vaucanson software platforms for automata manipulation. Education: PhD in Computer Science (2001, ENST Paris), Habilitation à Diriger des Recherches (2005, University of Paris Diderot). His work bridges theoretical foundations with practical tools, emphasizing algorithmic and algebraic aspects of automata. Notable contributions include studies on automata minimization, determinization, and the interplay between rational expressions and automata constructions. Research Interests: Automata Theory, Formal Power Series, Weighted Automata, Tropical Semirings, Algebraic Automata Theory, and Computational Models for Discrete Systems. His recent work explores two-way automata, Hadamard series, and applications in formal verification. Publications highlight contributions to the structure and properties of automata, with a focus on formal methods and algorithmic decidability. Key works address unambiguity, determinism, and the minimization of weighted automata across various semirings. Collaborations include projects on automata-based kernels for machine learning and XML formats for automata descriptions. He has developed influential software tools such as Awali (finite-state machine platform) and Vaucanson (automata manipulation framework), demonstrating practical applications of theoretical research. His work is supported by grants exploring automata in computational linguistics and discrete mathematics.

Vitor Limaمشاهده پروفایل

استادیار

• Consumer Culture Theory
• Artificial Intelligence
• Biohacking
• +۶ مورد دیگر

Vitor Lima serves as Assistant Professor of Marketing at ESCP Business School's Madrid campus. His academic journey includes a Postdoctoral Fellowship at Schulich School of Business/York University, establishing his international research profile. PhD in Business Administration (Marketing) from IAG/PUC-Rio and Schulich School of Business/York University MSc in Business Administration from FGV/EBAPE MBA in Marketing from FGV BA in Advertising with Branding extension from ESPM Digital Marketing Strategy Executive Certificate from Harvard University Professor Lima's research explores the intersection of emerging technologies and consumer behavior through critical theoretical lenses. His work examines how biohacking, transhumanism, and AI reshape human identity and consumption practices. He investigates consumer experiences with cyborg technologies, self-tracking devices, and human enhancement, often employing enactive and posthumanist frameworks to analyze these phenomena. His research methodology frequently incorporates arts-based and speculative approaches to examine technological futures. His recent publications reveal a strong focus on posthuman consumer identities, with significant contributions to understanding biohacking cultures, NFT implications, and human-robot interactions. The interdisciplinary nature of his work bridges marketing, philosophy of technology, and medical humanities, creating novel theoretical syntheses for analyzing technologically mediated consumption. AMS Mary Kay Doctoral Dissertation Award AMS Review - Sheth Foundation Doctoral Competition for Conceptual Articles (ADCCA) ACR Best Working Paper Award Professor Lima actively engages with media outlets including the BBC, translating complex academic concepts for broader public discourse. His collaborations extend beyond academia into practical applications of marketing theory, particularly regarding digital transformation and emerging technology adoption. His research on biohacking and human enhancement technologies has generated significant cross-disciplinary interest, influencing both academic and industry discussions about the future of consumer experiences.

• AI-enabled communications
• Green and energy-efficient communications
• Online optimization and machine learning
• +۶ مورد دیگر

E. Veronica Belmega is a Full Professor at ESIEE Paris (Université Gustave Eiffel) and a researcher at the LIGM laboratory in Marne-la-Vallée, France. Previously, she served as an Associate Professor at ENSEA graduate school and Deputy Director of the ETIS laboratory in Cergy. She holds an Engineer Degree from the University Politehnica of Bucharest, M.Sc. and Ph.D. from Université Paris-Sud 11, and an HDR habilitation from Université de Cergy-Pontoise. Her research focuses on AI-driven communication systems, energy efficiency, online optimization, and cyber-physical security, with a strong emphasis on applications in smart grids and IoT. Her work spans securing wireless communications against adversarial attacks, optimizing resource allocation in cognitive radio networks, and leveraging machine learning for GNSS localization and MIMO systems. Notable contributions include game-theoretic frameworks for PMU deployment and energy-efficient NOMA systems. Belmega has received prestigious awards such as the 2021 CY Alliance Award and the L’Oréal-UNESCO fellowship, and serves as an Area Editor for IEEE Trans. on Machine Learning in Communications and Networking. Current projects include a CEA LETI postdoc position on AI localization and a PEPR 5G project. She actively contributes to special issues like the EURASIP JASP on sustainable wireless communications. Belmega’s advising includes PhD student S. Maleki, co-author of her 2024 IEEE SmartGridComm Best Paper Award-winning work.

Camilla Fioriniمشاهده پروفایل

دانشیار

• Computational Fluid Dynamics
• Numerical Analysis
• Partial Differential Equations
• +۴ مورد دیگر

Camilla Fiorini is an Associate Professor at the National Conservatory of Arts and Crafts (CNAM) in Paris, where she conducts research at the Mathematical and Numerical Modeling Laboratory (M2N). She serves as Principal Investigator for the ANR-funded SPARCL project (2025-2029) focusing on structure-preserving reduced order models for conservation laws. Her academic background includes a PhD in Applied Mathematics from the University of Versailles and both MSc/BSc degrees in Mathematical Engineering from Politecnico di Milano. Her research centers on computational fluid dynamics, numerical analysis of PDEs, and sensitivity methods, with specific applications in uncertainty quantification and reduced order modeling. Current projects develop novel approaches for conservation laws that maintain structural properties while improving computational efficiency and reliability. Fiorini's publication record demonstrates consistent focus on sensitivity analysis techniques for complex fluid systems, shock-capturing methods, and uncertainty propagation in hyperbolic PDEs. She received the SMAI-GAMNI PhD Award 2019 (French ECCOMAS Award) for her doctoral dissertation on sensitivity analysis for nonlinear hyperbolic systems. As Principal Investigator of the SPARCL project, she leads a team developing new reduced basis construction techniques for conservation laws. Fiorini actively advises graduate researchers including PhD students Nathalie Nouaime (2021-2024) and Nicolas Lepage (2022-present), plus multiple Master's candidates. Her research group collaborates with institutions including Inria, Sorbonne University, ONERA, and CEA. Current projects include ANR JCJC-funded SPARCL and ANR AHEAD initiatives. She leads the SPARCL research group at M2N laboratory, collaborating with researchers including Alessia Del Grosso, Iraj Mortazavi, and Taraneh Sayadi on reduced order modeling techniques. The team focuses on developing computationally efficient ROMs that preserve physical structures in conservation laws.

Joanna C. S. Santosمشاهده پروفایل

استادیار

• Software Engineering
• Software Security
• Program Analysis
• +۴ مورد دیگر

Joanna C. S. Santos is an Assistant Professor at the University of Notre Dame's Department of Computer Science and Engineering. She leads the Security and Software Engineering research lab (S²E) and focuses on Software Engineering, Security, and Program Analysis. Her work bridges empirical studies with practical tool development. PhD in Computing and Information Sciences (Rochester Institute of Technology) M.Sc. in Software Engineering (Rochester Institute of Technology) B.Sc. in Computer Engineering (Federal University of Sergipe) Her research spans Software Security (vulnerability detection, ReDoS), Code Generation (LLM evaluation, benchmarking), and Program Analysis (taint tracking, call graphs). Recent articles show a strong focus on LLM-generated code quality and quantum computing applications. Scientific Awards : 2023 - Distinguished Reviewer (ESEC/FSE) 2020 - Research Pitch Winner (JOBS @MICRO) 2017 - Best Paper (ICSA) 2014 - CAPES Scholarship 2013 - ERBASE 3rd Place She actively contributes to conference committees (OOPSLA, ICSE, SCAM) and collaborates across institutions. Her lab S²E drives research in secure software development and empirical cybersecurity validation.