Gianni Franchi is an assistant professor at ENSTA Paris , affiliated with the Computer Science and Systems Engineering Unit (U2IS) . His work focuses on theoretical deep learning , with a strong emphasis on uncertainty quantification, robustness, and explainability in machine learning models. Current affiliation: ENSTA Paris (U2IS) Academic rank: Assistant Professor Key collaborators: David Filliat, Emanuel Aldea, Andrei Bursuc, Antoine Manzanera His research spans uncertainty quantification , explainable AI , and reliable machine learning . He investigates methods like Bayesian neural networks, ensemble approaches, and deterministic uncertainty models. His work also addresses domain adaptation , self-supervised learning , and autonomous systems , particularly in trajectory forecasting and semantic segmentation for autonomous driving. Recent publications analyze probabilistic modeling for robustness, symmetry-aware Bayesian methods , and multi-modal datasets like InfraParis. He develops frameworks like Torch-Uncertainty and benchmarks such as MUAD for uncertainty types in autonomous driving. Key themes: Uncertainty Quantification Deep Learning Theory Autonomous Systems Explainable AI Dataset Creation Bayesian Methods
Antoine Doucet is a Full Professor at the University of La Rochelle, where he teaches in the Computer Science department of the University Institute of Technology (IUT). He conducts his research at the Computer Science, Image and Interaction Laboratory (L3i) within the 'Images and Content' team, which he has led since 2015. He is also a member of the Franco-Vietnamese laboratory ICTLab and serves as Director of the ICT Department at the University of Science and Technology of Hanoi since 2016. His research focuses on information retrieval, natural language processing, text mining, and artificial intelligence, with emphasis on automatic analysis of text in all forms across languages. His work prioritizes generic methods that work across languages without relying on language-specific linguistic resources. This approach is particularly valuable for under-resourced languages and noisy texts from sources like social media or OCR output. As coordinator of the Horizon 2020 NewsEye project, he led efforts to improve access to European historical newspapers through semantic enrichment and advanced search capabilities. His research has practical applications in epidemic surveillance, document fraud detection, and historical content analysis. The NewsEye project involved 11 teams across Europe, including 3 national libraries and multiple research groups. Best paper award from IMIA Yearbook 2016 (among 1,272 candidates) Best paper award at HCI International with Ilona Nawrot Press coverage for ACL 2013 paper in major publications Recipient of French scientific excellence award (Prime d'Excellence Scientifique) Doucet actively supervises PhD and Master's students, with recent advisees including Chloé Artaud (Document fraud detection), Paul Martin (Photograph Time-Stamping), Ilona Nawrot (Temporal and Multilingual Text Analysis), and Gaël Lejeune (Multilingual Epidemic Surveillance). His research has been funded through multiple projects including ANR Digistory, AmeliOCR, PHC Nusantara, and USTH SWARMS. He has also coordinated significant European projects like NewsEye and Embeddia. At L3i, he leads a research group of approximately 40 persons focused on Images and Digital Content. His work bridges theoretical advances in multilingual text processing with practical applications in historical document analysis, epidemic surveillance, and document security.
Hugo Paquet is a Researcher at INRIA Paris and a member of the ANTIQUE team at École Normale Supérieure , PSL University. He completed a PhD in Computer Science (2015–2019) at the University of Cambridge under Glynn Winskel , focusing on concurrent game semantics for probabilistic programming. His postdoctoral work includes positions at LIPN, Paris (2022–2024, funded by a Marie Skłodowska-Curie Award) and University of Oxford (2020–2022). He has contributed to conferences including LICS , ESOP , FSCD , and POPL . Education : PhD in Computer Science (University of Cambridge, 2019) Research Interests : Probabilistic programming (semantics, inference algorithms, nonparametric models), categorical semantics (game semantics, concurrency models, adjunctions), combinatorial species, and 2-dimensional categories. Teaching : Category Theory (2023–2024), Bayesian Statistical Probabilistic Programming (2021–2022), Lambda-calculus and Types (2020–2021), and small-group teaching at Cambridge (Logic, Discrete Mathematics, Semantics). Awards : Marie Skłodowska-Curie Award under the Paris Region Fellowship Programme Labs : INRIA Paris, ANTIQUE team (2024–present)
Michalis Vazirgiannis is a Professor at LIX, École Polytechnique in France, where he leads the Data Science and Mining group (DaSciM). He holds a degree in Physics and a PhD in Informatics from Athens University (Greece), and a Master's degree in AI from Heriot Watt University, Edinburgh (UK). His academic career spans multiple prestigious institutions including Fraunhofer and Max Planck MPI in Germany, INRIA/FUTURS in Paris, AUEB in Greece, Telecom-Paristech, ENS in France, Tsinghua and Jiaotong Shanghai in China, and Deusto University in Spain. Professor Vazirgiannis's research focuses on machine and deep learning methods for graph analysis, including community detection, graph clustering, node embeddings, and influence maximization. His work in text mining encompasses Graph of Words, word embeddings with applications to web advertising and marketing, event detection, and summarization. He has active collaborations with industrial partners in analytics and machine learning for large-scale data repositories across various application domains such as recommendations, meeting summarization, influence metrics for scientific and social networks, and predictive maintenance. His recent publications demonstrate a strong emphasis on Graph Neural Networks, multilingual NLP (particularly for French and Arabic), and applications of deep learning to diverse domains including social networks, legal text, and biomedical data. There's a clear trajectory toward developing more efficient, explainable, and specialized models that address real-world challenges in data analysis. ERCIM fellowship Marie Curie EU fellowship Tencent "Rhino-Bird International Academic Expert Award" (2017) Best Paper Award at IJCAI 2018 Best Paper Award at CIKM 2013 Professor Vazirgiannis has supervised 29 completed PhD theses and has attracted significant R&D funding from national and international sources, including research agencies and industrial partners such as Google, Airbus, Huawei, Deezer, BNP, and LVMH. He leads or has led several academic research chairs including DIGITEO (2013-15), ANR/HELAS (2020-25), and AXA (2015-2018). The DaSciM research group, which he leads at École Polytechnique, has extensive experience in real-world R&D projects involving large-scale data mining. The team maintains active collaborations with major industrial partners including AIRBUS, Google, BNP, Tencent, and Tradelab, working on cutting-edge machine learning projects. The group has co-organized major conferences such as ECML PKDD 2011 and ECML/PKDD 2017 and participates in the senior organization of AI and data mining events like AAAI and IJCAI.
Nicholas Evans is a Professor in the Digital Security department at EURECOM, where he teaches mathematical methods for engineers and speech and audio processing. He has been affiliated with EURECOM since October 2007 and leads research in speaker recognition, anti-spoofing, and biometric security. Previously, he was a Professor at the University of Wales Swansea (2002–2006) and taught at the University of Avignon (2006–2007). Research Interests: His work centers on biometric security, particularly in detecting spoofing and deepfake attacks in automatic speaker verification systems. Key areas include presentation attack detection, privacy-preserving voice technologies, and robust speech processing under real-world conditions. He actively contributes to advancing anti-spoofing countermeasures through large-scale datasets and challenge evaluations. The recent publications reflect a strong trend in developing and evaluating spoofing detection mechanisms, with a focus on real-world applicability, adversarial robustness, and multimodal analysis. His work spans from foundational feature engineering (e.g., Constant Q cepstral coefficients) to large-scale datasets like SpoofCeleb and ASVspoof, influencing both academic research and practical security systems. NeurIPS 2023 Scholar Award for 'StressID: a multimodal dataset for stress identification' Best Paper Award at IBERSPEECH 2022 Best System Award at IberSpeech 2018 Multiple Best Paper Awards (2016, 2017) Student Paper Award at WIFS 2013 Elected to IEEE Speech and Language Technical Committee (2013) Nicholas Evans has supervised numerous students and early-career researchers, many of whom are co-authors on his publications. He leads significant research initiatives such as the ASVspoof and SpoofCeleb challenges, which are supported by collaborative grants and institutional funding. His lab focuses on developing secure, privacy-preserving speech technologies with applications in biometrics and cybersecurity. He is a key member of international research teams and contributes to major challenges in voice privacy and spoofing detection, including the Voice Privacy Challenge and BIOSIG. His work involves close collaboration with institutions across Europe and Asia, and he maintains active profiles on Google Scholar, ResearchGate, and IEEE Xplore.
Ana Bumber is a Doctor of English Studies currently serving as an ATER (temporary teaching and research associate) at Université Paul Sabatier Toulouse 3, assigned to IUT A. She is affiliated with the Department of Chemical Engineering Process Engineering, though her academic work is firmly rooted in English literature and language pedagogy. Her dual research focus bridges the humanities and technology, particularly in AI applications for language education and the literary artistry of Vladimir Nabokov. Her research interests include Artificial Intelligence in Language Teaching , generative AI tools , automatically generated subtitles , and intermediality in Vladimir Nabokov’s work . She explores how AI influences second language acquisition and investigates Nabokov’s intricate use of visual and sensory elements in literature. Her work often intersects digital pedagogy with modernist literary analysis. The recent trends in her publications show a strong emphasis on AI in education , particularly tools like HeyGEN for influencing L2 motivation, and the evaluation of AI-generated captions in ESP contexts. Simultaneously, she continues to publish on Nabokov’s aesthetic empiricism, train imagery, nature writing, and portraiture, reflecting a sustained scholarly engagement with modernist intermediality. Scientific Affiliations and Service: Member, French Vladimir Nabokov Society (SFVN) – also on the board (CA) Member, International Vladimir Nabokov Society (IVNS) Member, European Association for Computer Assisted Language Learning (EUROCALL) Member, Modern Language Association (MLA) Member, Society for Modernist Studies (SEM) Organizing member, Pedagogical Exchange Days (Lairdil) Webmaster team member for academic website Ana Bumber is actively involved in academic mentoring and pedagogical innovation, though no formal advisees are listed. She has organized pedagogical events and contributed to curriculum development through active learning strategies such as 'Job Dating' and peer feedback workshops. She has not received any explicitly mentioned grants or scientific awards in the provided text. Her work is supported through institutional affiliations and collaborative research networks, particularly in Nabokov studies and AI-enhanced language teaching. She participates in interdisciplinary seminars such as the EFELIA-ANITI cycle on AI and Humanities, indicating a strong commitment to bridging technological and humanistic scholarship.
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.
Cecilia Gunnarsson is an Associate Professor in Language Sciences at the University of Toulouse Jean Jaurès, affiliated with the NeuroPsychoLinguistics Laboratory (LNPL) and the Department of French as a Foreign Language Studies (DEFLE). She holds leadership roles as Axis 2 Manager in URI Octogone Lordat, Head of the Master's in French and Francophone Studies (DEFLE), and Co-Director of the Master's in Teaching Abroad (ESPE). Her academic work bridges research and pedagogy in second language acquisition, particularly in L2 French writing. Her research focuses on the cognitive and linguistic aspects of written production in both L1 and L2 French, with emphasis on fluency, complexity, and accuracy (FCA), working memory, and the oral/written interface—especially liaison and instance retrieval. She investigates how L2 learners develop writing automatization and how cognitive and emotional factors influence orthographic production. Her recent work uses experimental paradigms, such as dual-task methodologies, to differentiate controlled from automated writing processes. The analysis of her publications reveals a strong trajectory in psycholinguistics and applied linguistics, with a consistent focus on empirical and corpus-based methods. Her work spans developmental, cognitive, and educational dimensions of writing, with increasing interest in digital communication (e.g., instant messaging) and its impact on spelling. She frequently collaborates with researchers in neurolinguistics and cognitive psychology. Member, Scientific Committee, International Conference Les troubles du langage écrite : de l’enfance à l’âge adulte , 2012 Member and Organizer, Phonlex 2010 : Liaison and other sandhi phenomena Organizer, Conscila Workshop, ENS Paris, 2010: Multidisciplinary analysis of a student writing corpus She has supervised doctoral research, including a thesis on metacognitive strategies in vocabulary learning, and has co-edited several academic volumes. Her participation in national and international research networks—including ANR PHONLEX, GDR-CNRS APPVE, and GIS ReAL2—demonstrates her active role in the academic community. She also contributes to research valorization through conference organization and editorial work.
Juan-Manuel Torres Moreno is an Associate Professor (Maître de Conférences HDR HC) at the University of Avignon (UAPV), where he conducts research in Natural Language Processing at the Laboratoire Informatique d'Avignon (LIA). His academic position includes the HDR (Habilitation à Diriger des Recherches), a post-doctoral qualification in France that enables supervision of PhD students. His primary research interests focus on Natural Language Processing, with particular emphasis on automatic text summarization, sentence generation, and phrase compression algorithms. His work spans both theoretical and applied aspects of NLP, incorporating machine learning techniques and artificial intelligence approaches. His research has significant applications in multilingual processing, text mining, and information extraction systems. Torres Moreno's publication record demonstrates a consistent trajectory in advancing text summarization techniques, with recent work exploring cross-lingual approaches, multimedia content processing, and deep learning applications. His research often bridges the gap between theoretical linguistic concepts and practical implementation, with publications spanning from fundamental NLP algorithms to applied systems for video summarization, speech processing, and multilingual document analysis. He actively collaborates with researchers across multiple institutions including École Polytechnique de Montréal (with 50 joint publications), Laboratoire Informatique d'Avignon (83 publications), and Universidad Nacional Autónoma de México. His work appears in reputable journals such as Computer Speech and Language, Data and Knowledge Engineering, and Pattern Recognition Letters. Within the Laboratoire Informatique d'Avignon, Torres Moreno contributes to the Language Processing research theme, working with colleagues on projects related to multilingual information access, opinion mining, and text analysis. His research group has participated in several evaluation campaigns including DEFT (Défi Fouille de Textes) challenges, focusing on information retrieval and sentiment analysis tasks.
Nicolas Ballier is a Professor at Université Paris Cité (formerly Université Paris Diderot), where he teaches and conducts research in linguistics and digital humanities. Previously, he taught at the Université de Rouen and Paris 13. His work focuses on the intersection of linguistics, computational methods, and language learning technologies, with particular expertise in neural machine translation and speech processing. His primary research interests include: Corpus prosody Neural machine translation Automatic analysis of learner corpora Digital humanities Epistemology of linguistics (third revolution of grammatisation) Interpretability of neural machine translation systems Representation of speech in Whisper audio models Dr. Ballier's recent work explores how computers transform linguistic data (the 'third revolution of grammatisation'), with a focus on neural machine translation interpretability and speech analysis using large language models like Whisper. His research bridges theoretical linguistics with practical applications in language learning and translation technologies, particularly focusing on how these technologies can be made transparent and useful for translators and language learners. His 15 most recent publications (2022-2024) demonstrate a strong focus on neural machine translation interpretability, Whisper applications for language assessment, and learner corpus analysis. The publications span multiple prestigious venues including EAMT, ACL, LREC-COLING, and specialized journals in speech technology and computational linguistics, showing consistent productivity and impact in his fields. Dr. Ballier has been PI or team member on numerous European-funded projects including DOKTORAND (2012-2016), KVARK project (2014-2026), PHC Ulysses (2019), multitraiNMT (2021), and LT-LIder project (2024-Nov 2026). He has developed platforms like PAPTAN for neural machine translation experiments and MAKE-NMT VIZ for investigating machine translation interpretability. He has supervised PhD students through collaborative projects and has been involved in research initiatives like DLLA (Deep Learning for Language Assessment) exploring CEFR levels with keylog data, Neuroviz (2021-2022), and SPECTRANS (2020-2022) focusing on specialized neural translation and probing information flow in neural networks.
Marie Tahon is a Professor at Le Mans University and Director of the LST (Langage, Signal et Texte) team at LIUM (Laboratoire d'Informatique de l'Université du Maine). Her research spans expressive speech processing with applications in speech synthesis, emotion recognition, and speaker identification, complemented by expertise in musical acoustics for automatic song analysis and organology. Education : Engineering degree from École Centrale de Lyon (2007), M.S. in Acoustics from École Centrale & INSA Lyon (2007), and Ph.D. in Computer Science from University of Paris-Sud (Orsay, 2012). Postdoctoral positions at LIMSI-CNRS (affective computing), LMSSC CNAM (acoustics), and IRISA (Expression team). Research Focus : Tahon's work centers on developing interpretable systems for expressive speech processing. Key contributions include the ALLIES corpus for speech segmentation/diarization and AlloSat for call-center emotion analysis. Her recent publications demonstrate strong emphasis on low-resource speech translation (e.g., Kurdish), speaker verification after resynthesis, and turn-taking analysis in French media using explainable AI techniques. She integrates acoustic and linguistic features for continuous emotion prediction and develops noise-robust models for digital holography. Collaborations & Infrastructure : Leads the COMMUTE and ESPERANTO projects while directing LIUM's LST team. Her work leverages specialized resources like the ALLIES corpus (segmentation, diarization, recognition) and AlloSat (satisfaction/frustration analysis). Current efforts focus on lifelong learning for MOS prediction, multilingual speech translation, and perceptual evaluation of turn-taking phenomena in broadcast media.
Patrice Terrier is a Professor of Cognitive Psychology and Ergonomics at Toulouse Jean Jaurès University since 2008, affiliated with the Cognition, Languages, Language, Ergonomics (CLLE) laboratory. He has held significant leadership roles including Head of the 'compatibility between human and artificial systems' axis (2008-2014), Co-head of the 'cognitive ergonomics: memory, aging, rhythms' axis (2014-2016), Deputy Director of the doctoral school of aeronautics and astronautics site (2010-2015), and Scientific Director at the National Research Agency (2014-2017). He was appointed to the National Council of Universities (16th section) from 2012-2015 and has represented UT2J on various steering committees including the Graduate School ANITI and Toulouse Hybridation Education Campus projects. Terrier's research focuses on memory phenomena and consciousness in relation to person-system interaction. His work conceptualizes memory as a set of procedures and operations rather than a storage place, employing frameworks such as the attributive approach to memory, appropriate processing for transfer, and dual conceptions of memory processes. His research spans diverse application contexts including air traffic control, nuclear power operations, human-machine dialogue, internet information retrieval, risk perception, and decision-making problems. He has developed significant expertise in distinguishing between implicit (automatic) and explicit (controlled) memory use and characterizing gist versus verbatim representations. His publication record shows consistent output across cognitive psychology, ergonomics, and human-computer interaction, with recent work focusing on conspiracy theories, truth effects, humor appreciation, and unconscious thought processes in decision making. His research demonstrates strong interdisciplinary connections between cognitive theory and practical applications in complex systems. Terrier has been actively involved in academic governance, serving on the training commission of university life (2018-2022), as vice-president delegated to digital technology development (2019-2022), and as an elected member of the CFVU. He has contributed to numerous research groups including the European Association of Cognitive Ergonomics and has been an associate editor for the International Journal of Human Factors and Ergonomics since 2018. He has supervised 10 doctoral theses since qualifying to direct research in 2006, with his work supported by various research grants through the National Research Agency where he served as a scientific manager. His laboratory work within CLLE focuses on cognition in complex situations, particularly examining how memory processes operate in real-world contexts.
Patrice CLEMENTE serves as a Lecturer at INSA Centre Val de Loire, France, affiliated with the LIFO research laboratory (Laboratoire d'Informatique Fondamentale d'Orléans). His academic work focuses on cybersecurity with emphasis on cloud infrastructure security, biometric authentication systems, and attribute-based access control models. His research trajectory spans two decades, evolving from foundational SELinux policy analysis and honeypot forensics (2004-2012) toward contemporary medical security applications. Recent publications demonstrate specialization in photoplethysmography-based biometric authentication and Internet of Medical Things security architectures, reflecting adaptation to emerging healthcare technology challenges. Methodologically, his work combines systematic literature reviews with practical security framework development. Analysis of his 25 HAL publications reveals consistent contributions to security policy specification, virtualization security, and intrusion detection systems. The 2023-2024 publications indicate a strategic shift toward healthcare security domains while maintaining core expertise in access control and threat modeling. Scientific awards: No specific awards or fellowships were documented in the source material. Advising and grants: The provided information contains no records of supervised students, doctoral committees, or secured research funding. Labs and teams: CLEMENTE operates within LIFO, a joint research unit of the University of Orléans and INSA Centre Val de Loire under CNRS supervision, focusing on fundamental computer science research with security as a primary pillar.
Radu Mateescu is a Research Director at Inria Grenoble - Rhône-Alpes where he heads the CONVECS research team. He has been with Inria since 1998, previously working as a researcher in the VASY project-team. His research focuses on formal methods, particularly model checking and verification of concurrent systems. Mateescu holds a PhD in Computer Science from INPG (Institut National Polytechnique de Grenoble) with a thesis on "Verification of the temporal properties of parallel programs". His educational background includes a graduate engineer diploma from the POLITEHNICA University of Bucharest in Automatic Control and Computers. He has been instrumental in developing several formal verification tools including XTL, CAESAR_SOLVE, EVALUATOR, and BISIMULATOR. His research interests span formal specification and verification of temporal properties of concurrent systems, temporal logics extended with data-handling primitives, on-the-fly model checking, equivalence checking, diagnostic generation, partial order reduction, and massively parallel verification. He served as chairman of the FMICS (Formal Methods for Industrial Critical Systems) Working Group of ERCIM from 2011 to 2014. Mateescu has published extensively in formal methods, with recent work focusing on applications in autonomous vehicles, IoT systems, and hardware verification. His publications show a consistent trend toward applying formal verification techniques to increasingly complex real-world systems, particularly in safety-critical domains. Test-of-Time Tool Award at ETAPS'2023 Inria - Académie des Sciences - Dassault Systèmes Innovation Prize Information Technology Award from Fondation Rhône-Alpes Futur Mateescu has taught courses at ENSIMAG (Grenoble), ESIREM (Dijon), and the University of Savoie. He has contributed to major research projects involving industrial applications of formal methods, particularly through the CADP toolbox which has been used to verify numerous critical systems including the IEEE-1394 FireWire protocol, Bull's cluster file system, and autonomous vehicle systems. His work bridges theoretical formal methods with practical industrial applications.
Corine ASTESANO is an Associate Professor in the Department of Language Sciences at Université Toulouse-Jean Jaurès (UT2J), where she is affiliated with the NeuroPsychoLinguistics Laboratory (LNPL) and the CER research center. She holds a leadership role as LiCo Master Manager and is actively involved in national and international research collaborations. Her work bridges linguistics, neuroscience, and clinical applications, with a strong focus on prosody and rhythm in language. Her research interests include: Prosody and experimental phonetics Neuropsychology of language and music Speech pathologies and prosodic fluency Neural correlates of prosody (EEG, fMRI) Rhythm as a supra-organizer of cognition Her recent publications demonstrate a consistent focus on the neural and perceptual processing of French prosody, particularly initial and final accent, metrical stress, and rhythm. These works span behavioral, electrophysiological (EEG, ERP), and clinical domains, often involving cross-disciplinary collaborations. Key trends include the use of rhythm in speech therapy, the interface between language and music, and prosodic processing in both healthy and pathological populations. She actively supervises numerous PhD students and postdoctoral researchers, and leads or participates in major funded projects such as FluD4 (ANR), RUGBI, and PhonIACog. Her mentorship extends to HDR supervision and collaborative thesis co-direction across institutions including Université Paul Sabatier, EPHE-PSL, and Université de Louvain-la-Neuve. She is a core member of the monthly Groupe de Travail sur le Rythme and the long-standing Groupe Fluence' , fostering interdisciplinary dialogue on rhythm and fluency in cognition. Her research has practical implications for speech therapy, language acquisition, and the remediation of language disorders through musical and motor rhythm training.
