جستجوی استاد راهنمای دانشگاهی

Antoine Doucetمشاهده پروفایل

استاد

• Information Retrieval
• Natural Language Processing
• Text Mining
• +۷ مورد دیگر

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 His research has practical applications in epidemic surveillance, document fraud detection, and historical content analysis.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 His work bridges theoretical advances in multilingual text processing with practical applications in historical document analysis, epidemic surveillance, and document security.

Michalis Vazirgiannisمشاهده پروفایل

استاد

• Machine Learning
• Deep Learning
• Graph Analysis
• +۱۱ مورد دیگر

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.

• Natural Language Processing
• Automatic Text Summarization
• Sentence Generation
• +۵ مورد دیگر

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.

François Jacquenetمشاهده پروفایل

استاد

• Machine Learning
• Data Mining
• Natural Language Processing
• +۵ مورد دیگر

François Jacquenet is a Professor of Computer Science at the University of Saint-Etienne, where he is a member of the Machine Learning Team at the Hubert-Curien Laboratory. His research focuses on machine learning and data mining applications for natural language processing, with significant contributions to privacy-preserving systems including Hippocratic Multi-Agent Systems and Automata-Based Sequence Mining. His research interests span Machine Learning , Data Mining , Natural Language Processing , and Privacy-Preserving Systems . Jacquenet has led multiple research projects including the PASCAL II Network of Excellence (2008-2012), the Bingo2 project (2008-2010), and the Web Intelligence project (2006-2008), where he focused on ethical web design and privacy protection techniques. His work bridges theoretical foundations with practical applications in areas like fraud detection, meeting summarization, and video tag correction. Analysis of his recent publications reveals a consistent research trajectory in deep learning applications , privacy-preserving techniques , and cross-modal learning . His work shows a progression from foundational research in grammatical inference and automata theory to contemporary applications in neural networks and self-organizing systems. The publications demonstrate strong interdisciplinary connections between computer science, physics, and security applications. Best AI Paper Award at Conference (2006) Professor Jacquenet has supervised numerous PhD students including Maria Galvan, Hoang-Tung Tran, Ludivine Crépin, and Stéphanie Jacquemont. His research has been supported by significant grants including the French Research Agency (ANR), the Rhône-Alpes region, and international networks like PASCAL. He has organized multiple conferences including Privacy on the Web at the ACM Symposium on Applied Computing and the PASCAL Workshop on Teaching Machine Learning. He is actively involved with the Machine Learning Team at Hubert-Curien Laboratory , contributing to the PASCAL Network of Excellence and the REWERSE Network. His research group focuses on developing practical applications of machine learning while addressing fundamental theoretical questions in pattern mining and language learning.

Sonia Mandinمشاهده پروفایل

پژوهشگر

• Educational Technologies
• Learning Sciences
• Computer-Assisted Learning
• +۵ مورد دیگر

Sonia Mandin is a Postdoctoral researcher in educational sciences specializing in educational technologies at the French Institute of Education (EducTice) at École Normale Supérieure de Lyon. She has been working as a Post-Doc researcher with the Eductice team since October 2015. Her professional background includes positions as a teaching assistant at DILIPEM, Grenoble-3 since 2014, and previous postdoctoral research with the LIRIS - CNRS SILEX team from 2013-2015. Her educational background is impressive and interdisciplinary. She earned her doctorate in educational sciences from LSE, Grenoble 2 in 2009 with 'Very honorable mention with congratulations from the jury.' Prior to this, she completed a DEA in educational sciences (2003), a Master's in Educational Sciences (2002), and a degree in educational sciences (2001), all from SEAD, Lille 3 with honors. Her technical foundation was established with a DUT in computer science engineering from IUT A, Lyon 1 in 1998. Dr. Mandin's research focuses on the complex process of learning from an interdisciplinary perspective, integrating insights from psychology, didactics, and computer science. Her work centers on assisting learners through appropriate digital activities by developing computational models that can be implemented in educational technology tools. A significant portion of her research has focused on summarization skills, exploring how to help students better understand texts through effective summarization techniques. She has developed expertise in Latent Semantic Analysis (LSA) and its application to educational contexts, particularly in the development of the Résum'Web system for improving students' summarization abilities. Analysis of Dr. Mandin's recent publications reveals a strong focus on adaptive learning systems, competency-based education, and the application of natural language processing to educational contexts. Her work demonstrates a consistent trajectory from foundational research on text summarization to broader applications in personalized learning environments. Key themes include learner modeling, knowledge representation through ontologies, and the development of feedback mechanisms that support student learning. Her research bridges cognitive science with practical educational technology applications, particularly in mathematics education and writing instruction. Dr. Mandin has been actively involved in several significant research projects including the e-education project 'OCINAEE' (2015-2016), the 'Cartographie des savoirs' project (2013-2015), the European 'Language Technologies for Lifelong Learning' project (2008-2011), and the ACI Ecole et Sciences Cognitives project (2003-2005). She has also served as a speaker for the Canopé Network (formerly CNDP), the National Agency for the Use of ICT in education. Her work spans multiple research teams and institutions, including collaborations with the Knowledge Media Institute at the Open University of Milton Keynes, and research positions at LIRIS - CNRS and LSE, Grenoble. This diverse institutional engagement has allowed her to develop a rich perspective on educational technology applications across different educational contexts.

• Reinforcement Learning
• Artificial Intelligence
• Natural Language Processing
• +۴ مورد دیگر

Sylvain Lamprier is an Adjunct Professor affiliated with the Institute for Intelligent Systems and Robotics (ISIR) at Sorbonne University, working closely with the Machine Learning and Artificial Intelligence (MLIA) team. His research spans reinforcement learning, adversarial robustness, fairness in AI, and natural language processing. Specializes in robustness of deep RL agents against adversarial attacks Investigates fairness mechanisms without sensitive attributes Develops cooperative learning frameworks for language models Contributes to symbolic regression and query decomposition techniques Recent work includes ensemble methods for adversarial robustness (CAp 2025), distributionally robust auto-encoding (2025), and grounding LLMs in interactive environments (ICML 2023). Publications in top venues like NeurIPS, IJCAI, and ACL reflect his interdisciplinary focus. No scientific awards or part-time status are explicitly mentioned.

• Natural Language Processing
• Deep Learning
• Text Summarization
• +۳ مورد دیگر

Valentin Nyzam is a Researcher at the University of Tours , affiliated with the Polytechnic School and Department of Networks and Telecommunications (RT) . He works at the Fundamental and Applied Computer Science Laboratory of Tours (LIFAT, UR 6300) and is associated with the University Institute of Technology of Blois (IUT Blois) . Research Focus: Specializes in Natural Language Processing with emphasis on automatic summarization and comparative summarization Develops modular open-source tools (MOTS) for multi-document summarization Active in deep learning applications for text analysis and word embeddings Conducts cross-lingual research and short text language identification Focus on French language processing and implementation of NLP tools Contact: valentin.nyzam@univ-tours.fr

Chloé Clavelمشاهده پروفایل

استاد

• Affective Computing
• Artificial Intelligence
• Natural Language Processing
• +۵ مورد دیگر

Chloé Clavel is a Professor of Affective Computing at Télécom Paris (Institut Polytechnique de Paris) and Senior Researcher at INRIA Paris . She coordinates the Social Computing theme at Télécom Paris and leads research at the intersection of Affective Computing , Artificial Intelligence , and Human-Agent Interaction . Her work spans multiple disciplines including speech processing, natural language understanding, and social robotics. Research Focus: Socio-emotional behavior modeling Applications: Health, Education, Social Robotics Funding: H2020 ITN ANIMATAS, ANR SINNet Her recent publications demonstrate expertise in NLP and AI with topics including: Language model evaluation Contextual word representations Multimodal attention networks Stance detection Emotion recognition Awarded the AAAI-22 Outstanding Student Paper award for her work on the InfoLM metric, she has developed significant resources like the 3MT_French dataset and SILICONE benchmark . Her teaching includes: Master's Degree in Artificial Intelligence Courses on affective computing and NLP Industry training at Allianz and Sagemcom

• Machine Learning
• Graph Analysis
• Natural Language Processing
• +۷ مورد دیگر

Michalis Vazirgiannis is a Professor at the Department of Computer Science, École Polytechnique, France, leading the Data Science and Mining (DaSciM) group. He holds degrees in Physics (Athens University), Informatics (PhD, Athens University), and AI (Heriot-Watt University). His research focuses on machine learning for graphs, NLP, combinatorial optimization, and applications in fraud detection, biomedical tasks, and social networks. He has supervised 29 PhD theses and published over 250 papers. Awards include the ERCIM Fellowship, Marie Curie EU Fellowship, and Tencent's Rhino-Bird Award. Educations Bachelor's in Physics, Athens University Master's in AI, Heriot-Watt University PhD in Informatics, Athens University Research Interests His work spans graph neural networks (GNNs), community detection, text mining, and biomedical applications. He emphasizes explainability in GNNs and has developed models like RW-GNN. Current projects include the ANR-HELAS Chair on heterogeneous data and the X/AXA Data Science Chair. Industrial collaborations include Airbus, Google, and Tencent. Grants & Chairs ANR-HELAS Chair (2020–25): Deep learning for graphs and NLP AXA Data Science Chair (2015–18) ANR-XCOVIF (2020–21): Social impact analysis of COVID-19 via social media Labs & Teams The DaSciM group has 15 completed PhD theses and collaborates with industry on projects like predictive maintenance and recommendation systems. Key projects include graph generative models for biomedical data and privacy-preserving synthetic medical records.

Benoit Favreمشاهده پروفایل

استاد

• Natural Language Processing
• Machine Learning
• Multimodal Systems
• +۵ مورد دیگر

Benoit Favre is a Full Professor (PR, Section 27) at Aix-Marseille University and its engineering school Polytech Marseille since 2021. He leads the Data Science axis at the Laboratoire d'Informatique et Systèmes (LIS, CNRS UMR7020), encompassing research teams in NLP, machine learning, and multimodal processing. He completed his HDR (habilitation) in 2019 and serves as co-head of the multimodality group in the CNRS GdR on NLP. His research focuses on Natural Language Processing with machine learning, including semantic content analysis, multimodal system fusion, and technology evaluation in realistic applications. He teaches advanced machine learning for NLP at the Master IAAA program and organizes the ILCB Summer School. The 15 most recent publications highlight trends in Vision-Language Transformers , biomedical classification, historical domain adaptation, and cross-modal analysis. These works span from 2020 to 2024, with particular emphasis on multimodal representations, semantic parsing, and robust NLP systems. Scientific Awards : Best paper at TALN 2011 Ranked 1st in PERCOL consortium (REPERE 2013-2014) Ranked 1st in TAC 2008 and 2009 Benoit is also deeply engaged in community service, having organized major conferences like IEEE SLT 2010, SLAM 2013, and TALN 2014. He serves on scientific committees for selection of PhD grants and faculty positions. Office location: University library building (Luminy campus), second floor, office C207