جست‌وجوی استاد و پژوهشگر

Jorge Galicia Auyonمشاهده پروفایل

مدرس

• Semantic Web
• Graph Databases
• Big Data
• +۲ مورد دیگر

Jorge Galicia Auyon serves as a Lecturer in the Data Engineering team at ISAE-ENSMA (Poitiers, France), affiliated with the LIAS Laboratory of Automatic Systems. He holds a PhD in Computer Science from ISAE-ENSMA completed in 2021. Education: PhD in Computer Science, ISAE-ENSMA, 2021. Thesis: "Revisiting Data Partitioning for Scalable RDF Graph Processing". His research centers on Semantic Web infrastructure and Big Data systems, with specialized expertise in RDF query optimization, graph database partitioning, and distributed data processing. He develops novel techniques for scalable RDF graph traversal and fragmentation strategies applicable to large-scale clustered environments. Analysis of his 2019-2021 publications reveals consistent innovation in bridging physical/logical data partitioning for RDF systems, advancing query performance through graph exploration frameworks. These contributions strengthen foundations for industrial-scale semantic technologies. Research Environment: He actively contributes to the Data Engineering team at LIAS laboratory, which operates across ISAE-ENSMA's Chasseneuil campus and ENSIP's Poitiers facility, focusing on automatic control, real-time systems, and data engineering solutions.

Houssameddine Yousfiمشاهده پروفایل

مدرس

• Data Engineering
• Semantic Web
• Spatial Databases
• +۳ مورد دیگر

Houssameddine Yousfi serves as an ATER (temporary academic researcher) in Data Engineering at the University Institute of Technology (IUT) of the University of Poitiers, France. He maintains dual institutional affiliation through the LIAS laboratory (Laboratoire d'Ingénierie des Systèmes Automatisés), operating jointly at ENSIP (University of Poitiers) and ISAE-ENSMA engineering school. His doctoral research culminated in a 2023 PhD thesis titled Efficient Query Processing when Spatial Data Meets RDF Graph , co-supervised by ISAE-ENSMA and Université Aboubekr Belkaid de Tlemcen (Algeria). This work established foundational integration methods between spatial databases and semantic web technologies. Yousfi's research centers on overcoming scalability barriers in heterogeneous data systems, specifically developing novel query optimization techniques for RDF graphs and spatial databases. His methodology emphasizes hybrid indexing structures and distributed processing frameworks to handle industrial-scale datasets, with applications spanning geospatial analytics and knowledge graph querying. Current projects focus on optimizing R-tree exploration for spatial RDF datasets through parallel computation strategies. His publication pattern reveals consistent specialization in big data infrastructure, with both 2020-2021 conference papers addressing computational bottlenecks in spatial and semantic data domains. The 2021 WISE conference paper introduced RDF_QDAG for distributed RDF querying, while the 2020 AI2SD paper pioneered R-tree enhancements for spatial big data. As a core member of LIAS' Data Engineering research team, he collaborates with international researchers including Boumediene Saidi, Amin Mesmoudi, and Allel Hadjali on EU-funded data infrastructure projects. His laboratory work integrates automated control systems with advanced data processing pipelines at the Poitiers and Chasseneuil research sites.

David Gross-Amblardمشاهده پروفایل

استاد

• Knowledge Graphs
• Crowdsourcing Systems
• Database Security
• +۱ مورد دیگر

David Gross-Amblard is Professor of Computer Science at the University of Rennes, leading research on knowledge graphs and crowdsourcing systems. Current projects include the ANR-funded HEADWORK platform for complex crowdsourcing tasks and CLARA project on AI for open educational resources. Research bridges database systems with human computation, developing frameworks for privacy-preserving task assignment and semantic knowledge integration. Recent publications focus on optimizing crowdsourcing workflows for knowledge-intensive applications.

Hind CASTEL SAMOVARمشاهده پروفایل

استاد

• Computational Statistics
• Multimedia Data Engineering
• E-Health
• +۶ مورد دیگر

Prof. Hind CASTEL is a Professor at Telecom SudParis affiliated with the SAMOVAR Lab (formerly UMR 5157). Her research focuses on computational statistics, multimedia engineering, e-health, and distributed systems. She contributes to projects involving optical technologies, cybersecurity, and IoT networks. She participates in academic events such as the SOP Seminar on June 12, 2023, discussing advanced mathematical methods for optimization and boundary problems. Her work addresses challenges in memory management (disaggregated systems), high-speed optical communication (III-V-on-SOI lasers), and natural language interfaces for process data. Part of the NeSS group Active in doctoral student mentoring through Samovar's annual PhD Day events Recent publications explore garbage collection in distributed systems, laser-based optical networking, and AI-driven query interfaces for business processes.

Julien Romeroمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Knowledge Graphs
• Natural Language Processing
• +۳ مورد دیگر

Julien Romero serves as Maître de Conférences (Associate Professor) at Telecom SudParis, Institut Polytechnique de Paris, where he conducts research within the SAMOVAR laboratory. His work bridges artificial intelligence, database systems, and natural language processing with practical applications in knowledge representation and recommender systems. Romero earned his PhD in Artificial Intelligence from Institut Polytechnique de Paris in 2020 with a thesis on harvesting commonsense knowledge from web services. His research focuses on extracting and refining commonsense knowledge from unconventional sources including children's texts, query logs, and web content. He develops techniques for knowledge graph construction, query rewriting, and heterogeneous graph-based recommendation systems. Analysis of his 12 publications (2019-2024) reveals a strong trajectory from foundational database research toward applied AI systems. His work consistently addresses real-world challenges like job recommendation cold-start problems and commonsense knowledge base cleaning, demonstrating increasing technical sophistication through generative translation methods and heterogeneous graph approaches. Key publication venues include IEEE TKDE, CIKM, ISWC, and EMNLP. Romero actively mentors students through SAMOVAR laboratory projects, with research opportunities spanning knowledge engineering, natural language processing, and educational tool development. His Pyformlang library exemplifies his commitment to making theoretical computer science accessible. Current projects like TIMBRE (2024) indicate active industry-relevant research in professional recruitment systems. The SAMOVAR laboratory provides Romero's research environment, focusing on networks, computer science, and communication systems. His work within this framework emphasizes practical applications of theoretical concepts, particularly in knowledge representation and AI-driven recommendation systems. Ongoing projects suggest continued innovation in leveraging generative AI for knowledge base refinement and heterogeneous information network analysis.

• Data Mining
• Graph Mining
• Video Tracking
• +۳ مورد دیگر

Baptiste Jeudy is an Associate Professor at the University of Saint-Étienne since 2006, affiliated with the Hubert Curien Laboratory's machine learning group. His research focuses on data mining, graph mining, and their applications in video tracking and grammatical inference. Teaching: Responsible for the ATII professional license program, teaching courses in algorithms, computer architecture, operating systems, data mining, and graph theory. Research Projects: Led the ANR MDCO BINGO2 project (2008-2011) and participated in European projects like cInQ FET IST (2001-2004) and ANR SoLSTiCe (2014-2018). Research Interests: Data mining, graph mining, video tracking, grammatical inference, and constraint-based association rule mining. His work bridges theoretical advancements with practical applications in large-scale datasets and biomedical informatics. Publications: Active in data mining and knowledge discovery, with contributions to association rule optimization, condensed representations, and constraint-based pattern mining. His publications span journals like Intelligent Data Analysis and conferences such as ECML/PKDD and IDEAS. Advising: Has co-supervised PhD and Master’s students including Romain Deville, Fabien Diot, and Hoang-Tung Tran, focusing on projects related to data mining, pattern mining, and industrial collaborations.

• Knowledge Representation
• Database Theory
• Database Systems
• +۸ مورد دیگر

Michaël Thomazo is a Researcher at Inria, currently affiliated with the Valda team since April 2018. Previously, he was part of the Oak/Cedar team at Inria Saclay and held a postdoctoral position at TU Dresden funded by an Alexander von Humboldt fellowship. Education: Ph.D. in Knowledge Representation and Database Theory from University of Montpellier (2014), supervised by J.-F. Baget and M.-L. Mugnier in Inria's GraphIK team. Research Interests: Thomazo specializes in knowledge representation and its intersections with database theory/systems , employing logical and graph-based formalisms . His work focuses on description logics , knowledge graphs , and reasoning for heterogeneous data integration, particularly in ontology-mediated query answering (OMQA) frameworks for federated polystore systems. Scientific Awards: Co-awarded the 2014 AFIA prize for his Ph.D. thesis Second prize recipient for the 2014 Gilles Kahn Prize Projects and Community: He leads ANR-funded CQFD project (developing OMQA for heterogeneous data) and previously contributed to the Pagoda project. Thomazo serves on program committees for AAAI, IJCAI, ECAI, and other top conferences. A vocal open-access advocate, he mandates HAL publication of his work and boycotts closed-access venues. His teaching includes Formal Languages/Complexity and Knowledge Graphs courses at ENS.

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

Alexandre Vigny is an Assistant Professor at University Clermont Auvergne in France, focusing on the intersection of logic, algorithms, and graph theory. He has previously held postdoctoral positions at the University of Bremen (2019-2023) and the University of Warsaw (2018-2019), and completed his PhD at University Paris Diderot (2015-2018) under Arnaud Durand and Luc Segoufin. Current role: Junior Professor at University Clermont Auvergne (2023-present) Postdoctoral experience: University of Bremen (2019-2023), University of Warsaw (2018-2019) PhD: University Paris Diderot (2015-2018) His research interests span theoretical computer science, with a focus on first-order logic, graph algorithms, and complexity analysis. Recent work includes advances in algorithmic meta theorems, reconfiguration problems on sparse graphs, and distributed domination algorithms. Publications highlight applications of logic in solving graph-theoretic problems and query enumeration in database theory. Key trends in his 2025 publications include lower bounds analysis for dominating sets in sparse graphs, token sliding reconfiguration on DAGs, and elimination distance metrics. Earlier works (2017-2024) cover dynamic query evaluation, monadic stability, and parameterized distributed complexity frameworks. Teaching roles have included courses in algorithm design, object-oriented programming, database systems, and model theory across Clermont Auvergne, Bremen, and Paris institutions. Co-supervises PhD student Jona Dirks (2024-present) in reconfiguration problems on directed graphs.

Rajeev Alurمشاهده پروفایل

استاد

• Formal Methods
• Cyber-Physical Systems
• Programming Languages
• +۷ مورد دیگر

Overview Rajeev Alur is the Zisman Family Professor and Director of the ASSET Center for Trustworthy AI at the University of Pennsylvania . His career spans groundbreaking work in formal methods, cyber-physical systems, and programming languages. PhD from Stanford University (1991) Bachelor's degree from IIT Kanpur (1987) Research Interests His research focuses on ensuring safety and trustworthiness in AI systems, particularly autonomous systems like self-driving cars and medical devices. Key areas include: Neurosymbolic integration Temporal logic in reinforcement learning Verification of neural network controllers Trustworthy machine learning Extending formal methods to modern AI Recent Publications Rajeev's recent work (2023-2025) emphasizes compositional verification, neurosymbolic learning, and secure microservice architectures. Notable trends include: Combining formal specifications with deep learning Scalable verification techniques for neural networks Relational query synthesis Application to autonomous systems with neural perception Chordal sparsity models for efficient analysis Scientific Recognition Alonzo Church Award (2016) Knuth Prize (2024) EATCS Award (2025) ACM/IEEE Fellow Advising & Grants He has advised 30+ PhD students now in academia (Georgia Tech, UCSD, etc.) and industry. As lead PI of the NSF Expeditions project ExCAPE , he drove program synthesis research. Currently serves as General Chair for FLoC 2026 . Labs & Teams Directs the ASSET Center and collaborates with Penn's PRECISE Center and PL Club . His work integrates with industry verification tools at Amazon, Microsoft, and Google.

Marijan Sorićمشاهده پروفایل

مربی

• Geological Data Management
• Machine Learning
• Natural Disaster Response
• +۴ مورد دیگر

Marijan Sorić is a Ph.D. candidate affiliated with Inria Valda (Inria Paris, DI ENS, CNRS), Inria CEDAR (Inria Saclay, LIX, CNRS), and École Normale Supérieure (ENS) at PSL University . His research focuses on heterogeneous geological data structuring , machine learning for environmental modeling , and social media analysis during natural disasters . Education: Centrale Lyon (2021), NTNU (2024) His work includes a Ph.D. thesis on Exploitation and Structuring of Heterogeneous Geological Data and Knowledge , supervised by Pierre Senellart, Ioana Manolescu, and Cécile Gracianne. He contributes to table extraction benchmarks for scientific documents and has presented seminars on Extracting Table Information from Scientific Reports . His teaching roles include tutorials in Differential Calculus and Programming for the CPES joint program at PSL University. He also serves as Substitute Secretary for entrance exams at ENS. Contact: marijan.soric@inria.fr

Cyril Faucherمشاهده پروفایل

دانشیار

• Temporal Knowledge Modeling
• Model-Driven Engineering
• Semantic Web
• +۳ مورد دیگر

Cyril Faucher is an Associate Professor at the University of La Rochelle , associated with both the L3i Laboratory and the IUT of La Rochelle 's Computer Science department. He has served since 2013 as the head of the Integrator Developer (ID) course within the DUT Informatique program. His research focuses on Temporal Knowledge Modeling Model-Driven Engineering Semantic Web Applications Periodic Event Simulation Human Activity Modeling He has contributed to multiple research projects including ANR DéAIS (2014-2016), HOSEN (2013-2016), and Tourinflux (2013-2015). His work has been implemented in the RelaxMultiMedias ANR project (2009-2012) for cultural event modeling. Professor Faucher teaches across various IT domains including Database Systems (Oracle, MySQL) Web Development (PHP, JavaScript, jQueryMobile) Object-Oriented Programming (Java) Enterprise Architecture (UML, TOGAF) Software Project Management (Agility, SCRUM) Model-Driven Engineering He has developed several open-source tools for model engineering including Kermeta, OpenEmbeDD, and MDE Utils.

• Theoretical Computer Science
• Distributed Computing
• Descriptive Complexity Theory
• +۳ مورد دیگر

Fabian Reiter is an Associate Professor at Gustave Eiffel University , specializing in Theoretical Computer Science within the DataBases, Automata, algorithm Analysis and Models (BAAM) team at the Gaspard Monge Laboratory of Computer Science (LIGM) . His research bridges logic and distributed computing , focusing on extending descriptive complexity theory to distributed systems. His work establishes equivalences between distributed algorithm classes and logical formula classes, mirroring classical results like Fagin’s theorem . This includes groundbreaking connections between asynchronous automata and least fixpoint logic . Academic appointments : 2019–now : Associate Professor at Gustave Eiffel University 2019-03–2019-07 : Postdoc at Technical University of Munich (funded by ERC project PaVeS ) 2018–2019 : Postdoc at University of Paris-Saclay (funded by ERC project EQualIS ) Education : PhD (2014–2017) under Olivier Carton at IRIF, Paris Diderot University Master’s (2013–2014) under Fabian Kuhn and Andreas Podelski at University of Freiburg

• Computer Science
• Artificial Intelligence
• Data Science
• +۳ مورد دیگر

CHAIEB Ramzi is a Teacher-Researcher affiliated with CESI and LINEACT research laboratory. His work focuses on Artificial Intelligence, Data Science, Image Processing, and Digital Twins, with applications in medical imaging, historical document analysis, and industrial predictive maintenance. Education: Post-Doctoral Researcher at INSERM + IMT Atlantique (2019–2021), INSA Rouen (2018–2019), Doctorate from National School of Engineers of Tunis (2017). Research interests span AI-driven solutions for medical imaging (e.g., mammography classification), computer vision techniques in document analysis (e.g., fuzzy graph matching), and predictive maintenance using deep learning. Publications emphasize interdisciplinary applications of Machine Learning in healthcare, digital humanities, and industrial engineering. Collaborations include INSERM, IMT Atlantique, INSA Rouen, and INSERM/CHUs. Scientific achievements include qualification for French lecturer roles (Sections 27 and 61) and supervision of Amal Ayadi's thesis on industrial maintenance diagnostics.

Stéphane Baciocchiمشاهده پروفایل

پژوهشگر

• Social History
• Religious Sociology
• French Revolution
• +۶ مورد دیگر

Stéphane Baciocchi is a Researcher at the École des Hautes Études en Sciences Sociales (EHESS) , affiliated with the Centre for Historical Research (CRH) and its Laboratory of Demography and Social History (LaDéHiS) . He coordinates major projects including GeoHistoricalData , Structure and Dynamics of Forms , and the ANR TIME-US initiative on textile trade remuneration and time budgets in France (17th-20th centuries). His work bridges historical demography, religious sociology, and digital methodologies. Current Projects : GeoHistoricalData, Structure and Dynamics of Forms, ANR TIME-US Collectives : LaDéHiS, CRH Digital Collective, French Sociology Association Social Networks RT Committees : EHESS GIS Steering Committee, Labex HASTEC, Monitoring Unit against Sexual Harassment at EHESS His research interests focus on collective investigative practices , historical GIS, and relational data analysis across social sciences. He specializes in the sociology of the summer 1789 Grand'Peur , the history of social sciences (Le Play, Durkheim, Hertz), and digital editions of historical sources . Notably, he oversees the Prosopographic dictionary for students of the École Normale and the Cassini Roads and Cities Dataset . Baciocchi has taught seminars on relational data analysis (2003-2010), ethnography of religious facts (2005-2008), and history of investigative collectives (2007-present). He contributes to the Durkheimian Studies journal as associate editor and collaborates with the British Center for Durkheimian Studies at Oxford.

• Social Network Analysis
• Relational Data
• Historical Demography
• +۵ مورد دیگر

Pascal Cristofoli is a Researcher at the School for Advanced Studies in Social Sciences (EHESS) and the National Institute of Demographic Studies (INED), affiliated with the Laboratory of Demography and Social History (LaDéHiS) and the Centre for Historical Research (CRH). He specializes in creating and analyzing relational databases for human and social sciences (SHS), with a focus on historical networks, kinship data, and GIS methodologies. Methodological Leadership: Co-head of the EHESS-INED workshop Analysis of Relational Data and Social Networks (since 2001). Teaching: Conducts workshops on social network analysis, digital history, and interactive data exploration. His research explores the transition from historical sources to structured data, emphasizing visualization, network properties, and socio-spatial history. Key projects include ANR Kinsources (kinship data platforms) and the TRA Survey (19th-century Paris networks). He has contributed to geohistorical datasets like the Cassini Carte de France and developed tools such as the Puck software for kinship analysis. Scientific Collaboration: Active in organizing interdisciplinary conferences and training sessions across France, Senegal, and Spain. He is a webmaster and co-editor-in-chief of Kinsources.net , a collaborative platform for kinship data sharing.