جست‌وجوی استاد و پژوهشگر

• Material Science
• Solid-State Chemistry
• Thermoelectric Materials
• +۳ مورد دیگر

Nita Dragoe is a Professor at Université Paris-Saclay, affiliated with the Institut de Chimie Moléculaire et des Matériaux d'Orsay (ICMMO - UMR 8182) . She co-leads the Synthèse, Propriétés et Modélisation des Matériaux research group, focusing on advanced functional materials synthesis and characterization. PhD (1996): Université Paris Sud XI & Université de Bucarest (Advisors: Alexandre Revcolevschi, Eugen Segal) HDR (2003): Université Paris-Sud Her research spans high-entropy materials , thermoelectric oxides , and functional ceramics , with recent work on entropy-stabilized pyrochlores, superionic conductors, and pH sensor development. Key article trends highlight oxide synthesis , magnetic properties , and disorder-engineered materials . Scientific Awards : CREST Fellow (1997-2000) JSPS Fellow (2021) She has secured grants including the ANR-funded project NEO and maintains active collaborations across France, Japan, and China, with visiting professorships at Beihang University (2017-2022) and University of Tokyo (2019, 2005).

Rémi Flamaryمشاهده پروفایل

استاد

• Machine Learning
• Optimal Transport
• Domain Adaptation
• +۷ مورد دیگر

Rémi Flamary is a Professor in the Applied Mathematics department at École Polytechnique, France, and a member of the CMAP Laboratory. Previously, he held an Associate Professor position at Université Côte d'Azur in the Department of Electronics and Lagrange Laboratory. He completed his PhD at Rouen University under Alain Rakotomamonjy, focusing on statistical signal processing and optimization. His research interests span machine learning, optimal transport, domain adaptation, and their applications in biomedical engineering, energy, and remote sensing. He leads the development of the POT (Python Optimal Transport) library and contributes to projects like SKADA for domain adaptation. Education: PhD in Applied Mathematics, Rouen University (LITIS Laboratory) Research Focus: Flamary's work emphasizes leveraging optimal transport theory for machine learning tasks such as graph prediction, signal normalization, and cross-domain adaptation. His contributions include novel algorithms for unbalanced transport, semi-relaxed Gromov-Wasserstein distances, and end-to-end graph generation frameworks. He actively collaborates on applications in neuroscience, astronomy, and energy systems. Professional Activities: He has presented at NeurIPS and other top conferences, supervised PhD students like Cédric Vincent-Cuaz, and contributed to open-source software. His teaching includes courses on signal processing and machine learning at École Polytechnique.

Raphaël Troncyمشاهده پروفایل

استادیار

• Semantic Data Integration
• Knowledge Graphs
• Semantic Web
• +۳ مورد دیگر

Raphaël Troncy is an Assistant Professor at EURECOM's Data Science Department, specializing in Semantic Web technologies, Knowledge Graphs, and Natural Language Understanding. He teaches courses like 'Human-computer interaction for the Web' and 'Semantic Web technologies.' His research focuses on semantic data integration, knowledge graph applications, and recommender systems. Notable projects include DOREMUS (musical work graph), entity2rec (knowledge graph-based recommendations), and 3cixty (city exploration knowledge bases). He actively contributes to semantic web challenges and conferences, winning multiple awards including the 2018 Best Poster Award at ESWC and 2015 First Prize in the Semantic Web Challenge. Troncy's work spans cultural heritage digitization (e.g., Odeuropa olfactory data modeling), cybersecurity anomaly detection (NORIA-O ontology), and interdisciplinary projects like SILKNOW's silk textile knowledge graph. He leads development of tools like DAGOBAH for semantic table interpretation and KG Explorer for knowledge graph exploration. Education: Not explicitly stated in text Labs/Teams: Active in EURECOM's Data Science group, collaborating on projects involving knowledge graphs, AI, and semantic technologies

• Programming Languages
• Formal Verification
• Compilers
• +۵ مورد دیگر

Clément Pit-Claudel is an Assistant Professor at École Polytechnique Fédérale de Lausanne (EPFL), leading the SYSTEMF lab focused on programming languages, formal methods, and systems engineering. His work bridges mathematical formalisms with practical system development to achieve full assurance in critical software and hardware. PhD in Computer Science from MIT (2016) William A. Martin Memorial Thesis Award recipient Former Senior Applied Scientist at Amazon AWS Teaching accolades including the Frederick C. Hennie III Teaching Award Research spans three axes: extensible proof-producing compilers for performance-critical systems, verified hardware compilation with cycle-accurate semantics, and interactive theorem prover tooling for democratizing verification technology. Key projects include Kôika for hardware verification, Alectryon for Coq proof visualization, and Fiat for correct-by-construction program synthesis. Recent publications address JavaScript regex verification (ICFP 2024), cryptographic server integration (PLDI 2024), and hardware simulation optimization (ASPLOS 2021). Articles demonstrate expertise in functional-to-imperative translation, domain-specific compiler extensions, and hardware-software co-verification. Scientific contributions recognized through: Distinguished artifact award (SLE 2020) MIT William A. Martin Thesis Award Frederick C. Hennie III Teaching Award Teaching philosophy emphasizes hands-on lab instruction , oral assessment , and automated tooling . Courses taught include Software Construction (undergraduate) and Interactive Theorem Proving (graduate) at EPFL. Research service includes program committee roles at Dafny, POPL, and SPLASH conferences.

• Software Engineering
• Cybersecurity
• Formal Methods
• +۵ مورد دیگر

Role & Affiliation: Jean-Christophe BACH is an Associate Professor at IMT Atlantique's Computer Science department since 2015. He leads the PASS research group (IRISA) and focuses on software security, model-driven engineering, and cybersecurity applications. Previously, he held roles as a teaching assistant (ATER) at University of Lille (2014–2015) and completed his PhD on model transformations at Inria/LORIA under Pierre-Étienne Moreau and Marc Pantel (defended 2014). Research Interests: His work centers on improving software trustworthiness through 'security by design' principles. Key areas include model federation, formal methods for software verification, transformation traceability, and cybersecurity in industrial systems. He actively contributes to frameworks like Openflexo and PAMELA, emphasizing practical tooling for secure systems engineering. Teaching & Education: Teaches advanced topics such as object-oriented design, functional programming (OCaml), concurrency modeling, and cybersecurity. Supervises student projects on Openflexo, game development, and network security (IPv6/Tor). Courses include INF301, INF447, and others. Labs & Collaborations: Engaged with IRISA and Lab-STICC research centers. Collaborates on projects like the European Space Agency's SSE4Space framework for secure space missions and the Quarteft project (aerospace software). Active in open-source initiatives and scientific mediation for K-12 programming education.

Thomas Cokelaerمشاهده پروفایل

پژوهشگر

• Bioinformatics
• Data Analysis
• Machine Learning
• +۱۲ مورد دیگر

Thomas Cokelaer is a researcher at the Institut Pasteur, affiliated with the Bioinformatics and Biostatistics HUB and based at the Platform Biomics. Since October 2018, he has led the SALSA (dry-lab) group, focusing on bioinformatics software development and data analysis. His interdisciplinary background spans astronomy, plant modeling, systems biology, and drug discovery. Institution: Institut Pasteur Unit: Bioinformatics and Biostatistics HUB Platform: Platform Biomics Group: SALSA (dry-lab group) leader His research interests center on bioinformatics, next-generation sequencing (NGS) analysis, machine learning, data visualization, and reproducible research. He develops and maintains several widely used open-source tools including Sequana (NGS pipelines), BioServices (biological web services), Bioconvert (format conversion), Sequanix (GUI for Snakemake), and GDSCTools (pharmacogenomics). He is deeply committed to promoting reproducibility in computational research through initiatives like reprohackathons. The recent publications reflect a strong trend in computational biology, with a focus on developing bioinformatics methodologies, improving data analysis workflows, and applying these tools to diverse biological problems such as fungal pathogenesis, cancer pharmacogenomics, mitochondrial metabolism, and viral evolution. The work spans genomics, transcriptomics, systems biology, and software engineering. He has contributed to numerous scientific software projects as Principal Investigator, including Sequana, Bioconvert, GDSCTools, DREAMTools, and Sequanix. He has also taught courses in scientific programming with Python and reproducible data analysis at the Institut Pasteur. His collaborative network includes researchers from EMBL-EBI, Sanger Institute, INRIA, and international partners within the Pasteur Network. The SALSA group hosts master’s students and visiting researchers annually.

Florian Kaltenbergerمشاهده پروفایل

استاد

• Wireless Communications
• 5G and 6G Networks
• Massive MIMO
• +۱۰ مورد دیگر

Florian Kaltenberger is a Professor in the Communication Systems department at EURECOM, a leading research institute in digital technology based in France. He actively contributes to research and teaching in wireless communications, with a focus on 5G/6G technologies, massive MIMO, and OpenAirInterface-based prototyping. Research Affiliation: EURECOM - Communication Systems Key Projects: SOLDER FP7, Newcom++, COST 2100 Professional Memberships: IEEE, reviewer for major journals and conferences His research centers on signal processing for wireless communications, MIMO systems, channel modeling, and hardware implementation. He specializes in exploiting channel reciprocity in TDD systems and developing practical testbeds for next-generation networks. Recent publications highlight a strong trend toward AI-integrated RAN, open-source 5G/6G testbeds (e.g., OpenAirInterface, X5G), UAV-aided localization, and real-time control using decentralized applications. His work bridges theoretical innovation with field deployment in programmable living labs. Award Highlights: Neal Shepherd Best Propagation Award (2013) He leads research grants under EU frameworks like FP7 and collaborates internationally on open RAN and 6G innovation. Though no formal student list is provided, his role as project lead and frequent co-authorship suggests active mentorship. He also manages EURECOM’s contributions to large-scale collaborative projects. Kaltenberger is deeply involved in lab development, particularly around OpenAirInterface, where he leads efforts in creating end-to-end, multi-vendor, private 5G O-RAN testbeds with real-time AI control and green networking capabilities.

• Digital Innovation
• Crowdsourcing
• Data-Driven Decision-Making
• +۳ مورد دیگر

Michael Zaggl is a Full Professor at NEOMA Business School, specializing in Strategy & Entrepreneurship. He holds a Habilitation from TU Munich, a PhD from TU Hamburg, and degrees from the University of Koblenz. Previously, he served in tenured roles at Aarhus University and held visiting positions at Harvard, USC, and other institutions. His research focuses on digital innovation, crowdsourcing, and data-driven decision-making, with publications in top journals like Strategic Management Journal and Academy of Management Discoveries . He is an active member of professional organizations such as the Academy of Management and Association for Information Systems. Educations: Habilitation (TU Munich), PhD (TU Hamburg), Master's & Bachelor's (University of Koblenz). His research interests span digital innovation , crowdsourcing mechanisms , and open-source governance , with notable contributions to understanding distributed strategic search and organizational decision-making. Recent work examines crowdfunding dynamics , AI-human collaboration , and privacy calculus in mHealth . His articles analyze topics like crowd wisdom optimization and hierarchical biases in idea evaluation , reflecting a focus on practical applications for organizations. He has presented at leading conferences, including the Academy of Management and Hawaii International Conference on System Sciences.

• Hydrogen energy systems
• PEM fuel cells
• Energy efficiency
• +۵ مورد دیگر

Daniel Hissel is a Professor of Electrical Engineering and Hydrogen Energy at the University of Franche-Comté, France. He serves as the Head of the SHARPAC research team (Systèmes Hydrogène, ActionneuRs, Production, stockAge et Conversion de l'énergie électrique) within the Energy Department of the FEMTO-ST laboratory. Since January 2020, he has been Deputy Director of the national hydrogen research federation FRH2 (FR CNRS). He was named IEEE Fellow in 2021 and serves as President of the French chapter of IEEE/VTS. His educational background includes: Engineering degree from École Nationale Supérieure d'Ingénieurs Electriciens de Grenoble (ENSIEG) in 1994 PhD from École Nationale Supérieure d'Electrotechnique, Electronique, Informatique, d'Hydraulique de Toulouse (ENSEEIHT) in 1998 Habilitation à Diriger des Recherches (HDR) in 2004 Daniel Hissel's research focuses on energy efficiency and the diagnostics/prognostics of energy systems, particularly in the field of hydrogen energy for applications in mobility and stationary systems. His work encompasses fuel cell technology, energy conversion systems, and the development of predictive maintenance strategies for hydrogen-based energy systems. He has made significant contributions to understanding degradation mechanisms in fuel cells and developing methods to extend their operational lifetime. His recent publications (2025) demonstrate a strong focus on PEM fuel cell technology for transportation applications, with particular emphasis on heavy-duty vehicles. His research spans multiple disciplines including power electronics, control systems, electrochemistry, and artificial intelligence applied to energy systems. Key themes include nonlinear control of power converters, predictive maintenance using machine learning, physics-based modeling of fuel cells, and analysis of degradation mechanisms. His notable scientific awards include: Blondel Medal (2017) CNRS Innovation Medal (2020) IEEE Fellow (2021) Senior Member of the Institut Universitaire de France (IUF) (2022) Gold Medal of the Société d'Encouragement au Progrès (2024) Professor Hissel has published over 600 articles in international journals and conferences. He previously served as Director of the FCLAB Research Federation (FR CNRS) from 2012 to 2019. He is also an administrator of the "Véhicule du Futur" competitiveness cluster, demonstrating his strong connections with industry. His research has significant practical applications in the development of hydrogen-based energy systems for sustainable transportation and stationary power generation. He leads the SHARPAC research team at FEMTO-ST laboratory, which focuses on hydrogen systems, actuators, production, storage, and electrical energy conversion. This team conducts cutting-edge research in hydrogen energy technology, contributing to France's national efforts in developing hydrogen as a key component of the future energy system.

Pasquale Lisenaمشاهده پروفایل

پژوهشگر ارشد

• Knowledge Graphs
• Knowledge Engineering
• Recommender Systems
• +۳ مورد دیگر

Pasquale Lisena is a Research Fellow in the Data Science department at EURECOM, where he contributes to the Data2Knowledge research group. His work bridges academic research with practical applications in knowledge-intensive domains. Education: PhD in Computer Science from EURECOM / Sorbonne University (2019), thesis: "Knowledge-based music recommendation: Models, algorithms and exploratory search" supervised by Raphaël Troncy His research centers on Knowledge Graphs, Knowledge Engineering, and Recommender Systems with strong applications in cultural heritage and music. Key specializations include: Semantic Web technologies for domain-specific knowledge representation Information extraction from multimedia and text sources Development of ontologies for complex cultural domains Music metadata modeling and recommendation systems Recent publications reveal a trajectory from foundational music metadata work (2018-2019) toward cutting-edge applications in olfactory heritage (Odeuropa) and language model-driven recommendation (2025). His research consistently integrates knowledge graphs with machine learning, demonstrating expertise in both classical music informatics and emerging sensory heritage domains. Awards: Best Resource Paper Award (2022) for Odeuropa Data Model publication Funding and Collaboration: ANR JCJC project coordinator for kFLOW (2022-2024) Key contributor to EU H2020 projects including Odeuropa, SILKNOW, and MeMAD Extensive cross-institutional collaboration across European cultural heritage initiatives He operates within EURECOM's Data2Knowledge group, participating in international research consortia focused on knowledge-intensive applications in cultural heritage preservation and digital humanities.

François Pottierمشاهده پروفایل

پژوهشگر

• programming languages
• functional programming
• type systems
• +۵ مورد دیگر

François Pottier is a senior researcher at Inria in Paris, France, where he leads the Cambium research team. He is affiliated with the Gallium research group and has maintained an active research profile spanning several decades in programming languages and formal methods. His research focuses on programming languages , particularly functional programming and OCaml, type systems design and implementation, program verification using separation logic, and compiler construction . His work bridges theoretical foundations with practical implementation, evidenced by numerous open-source software tools he has developed. Pottier's publication record shows consistent contributions to top programming languages conferences (POPL, ICFP, ESOP) with recent work emphasizing separation logic frameworks, resource analysis, and formal verification of OCaml systems. His research demonstrates a clear trajectory from foundational type theory toward practical verification techniques for real-world programming languages. He has advised numerous PhD students including Remy Seassau, Tiago Soares, Clément Allain, and Alexandre Moine, among others, many of whom have gone on to research positions at institutions like New York University, Imperial College London, and Inria itself. Pottier maintains active service roles in the programming languages community as a member of IFIP Working Group 2.8 on Functional Programming and IFIP Working Group 2.16 on Language Design, and serves on program committees for major conferences including upcoming roles for JFLA 2026 and ITP 2026. He leads the Cambium research team at Inria, which focuses on programming language theory and implementation, particularly around OCaml and formal verification. The team develops both theoretical frameworks and practical tools that have influenced the broader programming languages ecosystem.

Ewelina Rupnikمشاهده پروفایل

پژوهشگر

• Photogrammetry
• Pose Estimation
• Image-based 3D Reconstruction
• +۷ مورد دیگر

Ewelina Rupnik is a prominent researcher in photogrammetry and remote sensing, currently holding a researcher position at the Laboratory on Geographic Information Science (LaSTIG) at the French National Institute of Geographic and Forest Information (IGN) since 2017. She also serves as an associate researcher at the Paris Institute of Earth Physics (IPGP). Rupnik has established herself as a leading expert in historical imagery processing, neural radiance fields, and bundle adjustment techniques. Her educational background includes a PhD in photogrammetry from the Vienna University of Technology (2015), an MSc in Engineering in Photogrammetry from AGH University of Science and Technology, Poland (2005-2010), and an Erasmus exchange at the Technische Universitaet Muenchen, Germany (2009/2010). She recently completed her Habilitation from Université Gustave Eiffel in June 2025. Rupnik's research focuses on advancing photogrammetric techniques for processing historical imagery, developing novel neural radiance field approaches for satellite imagery, and improving bundle adjustment methodologies. Her work bridges traditional photogrammetry with modern deep learning techniques, particularly in the context of sparse satellite views and historical multi-epoch imagery. She has made significant contributions to the open-source MicMac photogrammetry software project. Her recent publications demonstrate a strong trend toward integrating deep learning with traditional photogrammetric methods, with a particular emphasis on satellite and historical imagery analysis. The research spans from fundamental algorithm development (like SparseSat-NeRF and Pointless Global Bundle Adjustment) to practical applications in earth sciences (landslide, earthquake, and glacier volume mapping). 2022 EuroSDR PhD Award for Corona satellite imagery processing Best Paper Award for BRDF-NeRF research Outstanding Reviewer at CVPR 2025 Rupnik actively contributes to the academic community through editorial and leadership roles, including serving as Editor-in-Chief of the French Journal for Photogrammetry and Remote Sensing (2021-2025), Advisory Board Member of the International Journal of Photogrammetry and Remote Sensing (2024-present), and Co-chair of the ISPRS Working Group on Image Orientation and Sensor Fusion (2022-2026). She regularly teaches at Université Paris Cité & ENSG (~30 hours/year since 2015) and has conducted numerous workshops worldwide on photogrammetry with historical images and MicMac software.

Sylvain Meignierمشاهده پروفایل

استاد

• Speech Processing
• Audio Signal Processing
• Speaker Diarization
• +۳ مورد دیگر

Sylvain Meignier is a Professor in Computer Science at the University of Mans, where he has been affiliated since 2004. He currently serves as Deputy Director of the LIUM (Laboratoire d'Informatique de l'Université du Mans) and leads research in speech and audio processing. His academic journey began with a PhD from Université d’Avignon et des Pays de Vaucluse in 2002. Research Focus: Speech processing, speaker diarization, audio signal analysis, and lifelong learning systems. Collaborations: Active in projects like DIGING and the ANTRACT project. Software Development: Co-developer of the SIDEKIT and S4D toolkits for speaker diarization. His recent work explores cross-domain speech processing, including overlap detection, gender analysis in broadcast media, and lifelong learning frameworks. Publications span interdisciplinary applications in digital humanities and core technical advancements in machine learning. No specific scientific awards are mentioned in the provided text. Sylvain also contributes to open-source tools and large-scale multimedia indexing challenges.

• Architectural Photogrammetry
• Geomatics
• Urban 3D Modeling
• +۴ مورد دیگر

Tania Landes is a Professor at the University of Strasbourg (Unistra) affiliated with the ICube Laboratory UMR 7357 CNRS/Unistra and the PAGE Group (Architectural Photogrammetry and Geomatics). Her work focuses on integrating advanced 3D modeling and geomatics techniques for urban applications. Academic Rank: Professor Institution: University of Strasbourg Research Affiliation: ICube Laboratory UMR 7357 CNRS/Unistra Research Interests : Indoor and outdoor 3D modeling with RGB-D sensors and LiDAR Semantic segmentation of point clouds for BIM (Building Information Modeling) Thermal imaging integration for urban microclimate studies Historical and cultural heritage documentation via photogrammetry Urban tree modeling and vegetation impact on thermal comfort Scan-to-BIM workflows and automation Key Projects include the TIR4sTREEt thermal infrared studies of street trees in Strasbourg and COOLTREES for quantifying urban cooling benefits from vegetation. Her publications emphasize improving 3D reconstruction workflows and modeling accuracy across domains. Scientific Contributions span 15+ years with over 50 publications, covering: Urban heat island mapping (2022 onwards) Historical building modeling (2014-2017) Mobile laser scanning applications (2020 onwards) Kinect sensor calibration for 3D modeling (2015) Microclimate simulation via LASER/F (2016) Archaeological documentation (2011)

Xavier Rivalمشاهده پروفایل

پژوهشگر

• Computer Science
• Artificial Intelligence
• Software Engineering
• +۳ مورد دیگر

Xavier Rival is a Senior Researcher at Inria, affiliated with multiple project teams including Antique , GraphDeco , Sierra , and Quantic . He focuses on data structures and algorithms within operating systems and embedded programs, with a strong emphasis on artificial intelligence and software engineering. Rival received the ERC Proof of Concept grant in 2018 for his work on formal verification tools. Current teams: GraphDeco (since 2016), Quantic (since 2021), Sierra (2016-2024) Key collaborations: European Research Council grants, Inria Startup Studio Research trends include neural network security, curiosity-driven machine learning, and AI safety verification. Notable projects involve SOFA open-source coordination and DeepTech initiatives at Inria Saclay. Scientific awards ERC Proof of Concept grant (2018)