Find Academic Supervisors

Lee M. MillerView profile

Professor

• Neuroengineering
• Computational Neuroscience
• Auditory and Speech Processing
• +4 more

Lee M. Miller is a Professor and Vice Chair of Academic Affairs in the Department of Neurobiology, Physiology and Behavior at the University of California, Davis, affiliated with the Center for Mind and Brain. His research focuses on neuroengineering, computational neuroscience, and neural mechanisms underlying attention, speech processing, and multisensory integration. Research interests include the development of neural prosthetics, decoding of neuromuscular signals for prosthetic control, and understanding how auditory and visual systems interact during speech perception and attentional processes. His work bridges clinical applications (e.g., cochlear implants) with fundamental neuroscience, leveraging tools like electrophysiological recordings, EEG/MEG, and advanced signal processing techniques. Recent publications highlight innovations in electromyographic speech neuroprosthetics, the topology of neuromuscular signals, and the neural basis of speech-in-noise processing. Miller’s studies emphasize translational potential, such as improving speech synthesis from brain signals and designing haptic feedback systems for motor coordination. His contributions have advanced understanding of neural mechanisms in sensory integration, auditory attention, and the impact of cognitive factors on perception. Miller maintains a lab dedicated to these interdisciplinary efforts, with a focus on both basic science and clinical applications.

Antoine DoucetView profile

Professor

• Information Retrieval
• Natural Language Processing
• Text Mining
• +7 more

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.

• Radiomics
• Medical Imaging Analysis
• Machine Learning in Healthcare
• +7 more

Adrien Depeursinge is a Professor at HES-SO Valais-Wallis - Haute Ecole de Gestion, affiliated with the School of Economics and Services and the Management Information Systems department. His research focuses on radiomics, personalized medicine via image-based analysis, and clinical workflow optimization. He leads the development of the QuantImage platform, a physician-centered web-based tool for radiomics research, and contributes to radiomics standardization efforts through initiatives like the Image Biomarker Standardization Initiative (IBSI). His work emphasizes machine learning applications in healthcare, including tumor segmentation, biomarker extraction, and improving diagnostic accuracy through computational models. Key research themes include: 1) Radiomics – developing quantitative imaging features for cancer diagnosis/prognosis; 2) Medical Imaging Analysis – advancing texture-based models, multi-modal fusion, and automated lesion detection; 3) Physician-AI Collaboration – designing user-centric tools for clinical integration. His contributions span neuro-oncology (brain metastases), head-and-neck cancer, and multiple sclerosis imaging. Publications emphasize methodological advancements (e.g., kernel optimization in CNNs, steerable detectors) and clinical validation (e.g., reproducibility of radiomics features across imaging protocols). He collaborates with institutions like the University Hospital of Lausanne (CHUV) and international teams on projects like the HECKTOR challenge for PET/CT tumor segmentation. His work bridges technical innovation with clinical impact, aiming to translate radiomics into actionable clinical tools. QuantImage v2, his flagship tool, enables no-code development of machine learning models using clinical imaging data. Research also includes phantom-based validation of radiomics features and addressing challenges in feature stability across imaging modalities. Current projects explore improving contour quality for radiomics studies and optimizing AI explainability in medical decision-making.

Simone Paolo PonzettoView profile

Assistant Professor

• Knowledge acquisition
• Natural Language Processing
• Semantic Web technologies
• +5 more

Simone Paolo Ponzetto is an Assistant Professor (Juniorprofessor) at the University of Mannheim since 2013, affiliated with the Research Group Data and Web Science. His research focuses on Semantic Web technologies, Natural Language Processing (NLP), and knowledge acquisition, particularly leveraging collaboratively built resources like Wikipedia. Prior to Mannheim, he held postdoctoral roles at Sapienza University of Rome and research positions at the University of Heidelberg and Stuttgart. His work includes pioneering projects like BabelNet, a multilingual semantic network. Ponzetto earned his PhD in Computational Linguistics from the University of Stuttgart, with interdisciplinary contributions to coreference resolution, semantic relatedness, and ontology learning. Research Interests: Unsupervised/weakly-supervised knowledge extraction Multilingual ontology learning and semantic networks Lexical semantics (word sense disambiguation, semantic similarity) Discourse semantics (coreference resolution, coherence modeling) Professional Contributions: Guest editor for a Artificial Intelligence Journal special issue on AI and Wikipedia Area chair for EMNLP-CoNLL 2012 and EACL 2014 Program committee member for ACL, AAAI, and other top conferences Lab/Team: Active in the Research Group Data and Web Science at Mannheim, advancing AI and NLP applications in collaborative knowledge systems.

Pablo CallejaView profile

Research Fellow

• Natural Language Processing
• Medical Informatics
• Legal Informatics
• +5 more

Pablo Calleja is a Research Fellow at the Faculty of Computer Science, Polytechnic University of Madrid (UPM), where he has been a member of the Ontology Engineering Group (OEG) since March 2014. His research focuses on Natural Language Processing (NLP), medical terminology mapping, and legal domain applications. He holds a degree in Computer Engineering from San Pablo CEU University (2013) and has prior industry experience as a software developer at IECISA (2008–2011) and a collaboration grant at the Open Access Classroom, San Pablo CEU University (2011–2013). Key contributions include projects like Drugs4covid for pandemic drug discovery, TermitUp for terminological enrichment, and esT5s , a Spanish text summarization model. His work spans legal knowledge graphs, multilingual compliance systems, and NER techniques for academic content analysis. He has also explored accessibility multimedia services and semantic graph applications in tourism ( DBtravel ). Professional roles include collaboration grants at UPM and active participation in interdisciplinary projects such as SNOMED-CT annotation for medical technical sheets. Research trends emphasize cross-domain adaptation (e.g., K-Flares), data augmentation (Widaug), and multilingual NLP solutions. Advising and grants: His current position is supported by a collaboration grant at OEG. Earlier grants include work at San Pablo CEU University. No formal advisees are listed, but he contributes to collaborative research teams. Labs and teams: Core member of the Ontology Engineering Group (OEG), focusing on knowledge representation, NLP, and applied informatics in healthcare and law domains.

Mo El-HajView profile

Associate Professor

• Natural Language Processing
• Financial NLP
• Arabic NLP
• +9 more

Dr. Mo El-Haj is a Reader (Associate Professor) in Natural Language Processing (NLP) at the College of Engineering & Computer Science, VinUniversity, Hanoi, Vietnam, and holds a visiting role at Lancaster University. He specializes in NLP with a focus on Financial NLP, Arabic NLP, and multilingual systems for under-resourced languages. Education: PhD in Computer Science (University of Essex, 2012), MSc in Information Systems (University of Jordan, 2008), BSc in Computer Information Systems (University of Jordan, 2005). Awards include the FHEA Fellowship (2021) and the 2016 BBC NewsHack Best Tool award. Research interests include text summarization, financial narrative processing, biomedical NLP, and corpus linguistics. He leads the VinNLP research group and has supervised/co-supervised over 20 PhD students. Notable projects include the Welsh Automatic Text Summarisation tool (ACC) and the FreeTxt bilingual analysis toolkit, funded by the Welsh Government and AHRC. Publications span 92+ works in top journals/conferences like Computational Linguistics and LREC. Active in organizing workshops (e.g., WACL-4, FinNLP) and has served as external/internal PhD examiner at UK universities.

Viviana CotikView profile

Associate Professor

• Artificial Intelligence
• Natural Language Processing (BioNLP)
• Information Extraction
• +5 more

Dr. Viviana Cotik is an Associate Professor at the Department of Computer Science, Faculty of Exact and Natural Sciences, University of Buenos Aires. She also serves as Professor for the Master's Degree in Data Mining and Knowledge Discovery within the same department. Additionally, she works as an Assistant Researcher at the National Council for Scientific and Technical Research (CONICET) in Argentina. Artificial Intelligence Natural Language Processing (BioNLP) Information Extraction Machine Learning Biomedical Informatics Social Applications of AI Her research focuses on applying natural language processing techniques to biomedical domains, including negation detection in clinical reports, entity recognition in radiology texts, and cross-lingual information extraction. She investigates applications of AI in social inclusion and has developed methodologies for automatic classification of medical documents through machine learning and syntactic analysis. Her work also extends to data quality assessment frameworks and historical analysis of ICT education in Argentina. Recent publications highlight her expertise in Spanish and French language processing for biomedical texts, with applications in radiology report analysis and social implications of AI. She has contributed to multiple conferences including IberLEF, RANLP, ACL BioNLP, and IJCAI workshops, while also publishing in journals like International Journal of Information Quality and Fuzzy Sets and Systems . Scientific recognition: First prize in Estudiantiles Works Contest (undergraduate category), 33rd JAIIO, 2004 She has delivered numerous guest lectures internationally, including at Stanford's Women in Data Science chapter, Universidad Nacional de La Plata, and institutions in Peru, Germany, UK, and Spain. Her outreach activities include coordinating the Computer History Museum and organizing Drunk Talks for PhD students.

Els LefeverView profile

Associate Professor

• Natural Language Processing
• Computational Linguistics
• Machine Learning
• +5 more

Els Lefever is an Associate Professor at Ghent University, where she works with the LT3 (Language and Translation Technology) research team. Her position focuses on computational linguistics and natural language processing research, with strong ties to both theoretical and applied aspects of language technology. Dr. Lefever earned her PhD in Computer Science from Ghent University in 2012 with her dissertation titled "ParaSense: Parallel Corpora for Word Sense Disambiguation." Her academic journey began as a computational linguist at the R&D department of Lernout & Hauspie Speech Products before transitioning to academia. Els Lefever's research spans multiple areas within computational linguistics with particular expertise in multilingual natural language processing. Her work focuses on computational semantics, cross-lingual word sense disambiguation, and multilingual terminology extraction. Recent research directions include automatic detection of irony in online text, argumentation mining in social media, sentiment analysis of financial news, language modeling for low-resourced languages, and computational approaches to Byzantine Greek epigrams. Her research demonstrates a consistent pattern of bridging theoretical computational linguistics with practical applications across diverse language domains and historical periods. Professor Lefever actively supervises PhD research on several cutting-edge topics including terminology extraction from comparable corpora, event extraction and sentiment mining of financial news, language modeling for low-resourced languages, argumentation mining in social media, and the automatic detection of links between Byzantine Greek epigrams. Her supervision portfolio demonstrates her commitment to advancing multiple frontiers of computational linguistics simultaneously. As an educator, Professor Lefever teaches courses in Terminology and Translation Technology, Language Technology, Localisation, Digital Text Analysis, and Digital Humanities. Her teaching reflects her research interests, providing students with both theoretical foundations and practical skills in language technology applications. The LT3 research group, where Professor Lefever is a key member, maintains strong connections with both academic and industry partners. The group has participated in numerous international conferences and shared tasks including SemEval competitions across multiple years, demonstrating consistent contributions to benchmark datasets and evaluation methodologies in natural language processing.

Nicolas BallierView profile

Professor

• Corpus prosody
• Neural machine translation
• Automatic analysis of learner corpora
• +5 more

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.

ZIYA TOKView profile

Associate Professor

• Translation Studies
• French Language Teaching
• Computer-Assisted Translation
• +3 more

ZIYA TOK is an Associate Professor in the Department of French Translation and Interpreting at Kırıkkale University's Faculty of Humanities and Social Sciences. His academic focus lies in translation studies, particularly French-Turkish translation, and the teaching of French as a foreign language. His educational background includes: Undergraduate and Graduate: French Translation and Interpreting, Kırıkkale University Doctorate: French Language Education, Hacettepe University Professor Tok's research spans translation technology, terminology management, and the pedagogy of foreign language teaching. He investigates challenges in translating specialized texts (e.g., forestry, banking, and poetry) and the role of computer-assisted tools in translation. His work also addresses discourse analysis in translation, particularly reported speech, and the integration of translation in language education curricula. The following list highlights his primary research areas: Translation Studies French Language Teaching Computer-Assisted Translation Machine Translation Terminology Discourse Analysis in Translation Analysis of his recent publications (2020-2025) reveals a strong emphasis on practical translation problems between French and Turkish, with a growing interest in technological solutions. His work bridges theoretical translation studies with applied linguistic challenges in the Turkish context, particularly in the development of terminology resources and pedagogical methods for translation education. A comprehensive review of the available information did not reveal any mentions of scientific awards, fellowships, or major honors received by Professor Tok. While Professor Tok's role as a faculty member likely involves student supervision, the provided text does not specify any current or past students, nor does it detail any research grants he may have secured. There is no indication in the source material of any laboratory affiliations, research centers, or collaborative teams led by Professor Tok.

Frank PuppeView profile

Professor

• Artificial Intelligence
• Medical Image Analysis
• Document Analysis
• +5 more

Frank Puppe is a Full Professor of Computer Science at the University of Würzburg, Germany, where he holds the Chair of Computer Science VI (Artificial Intelligence and Applied Computer Science) within the Faculty of Mathematics and Computer Science. He is also affiliated with the Center for Artificial Intelligence and Data Science (CAIDAS) and leads research in artificial intelligence, knowledge systems, and applied computer science. His educational background includes a Diploma in Computer Science from Bonn University (1983), a dissertation on Diagnostic Problem Solving from Kaiserslautern University (1986), and a habilitation on Problem Solving with Expert Systems from Karlsruhe University (1991). Professor Puppe's research spans multiple domains of artificial intelligence and its applications. His primary focus areas include Medical Image Analysis , where he develops AI systems for endoscopic disease detection and medical information extraction; Document Analysis and OCR , with significant contributions to processing historical documents and musical manuscripts; and Information Extraction from diverse domains including medical, legal, and literary texts. His work in E-Learning and E-Assessment has led to innovative systems for automatically evaluating programming assignments and argumentation structures. His recent publications demonstrate a strong interdisciplinary approach, bridging computer science with medicine, digital humanities, and law. A notable trend is the application of deep learning techniques to historical document analysis and medical imaging, while maintaining a strong foundation in knowledge-based systems. His research consistently focuses on practical applications of AI that solve real-world problems across multiple domains. 2015-2017: Senator at University of Würzburg 2011-2013: Dean at University of Würzburg 2008-2011: Dean of Students at University of Würzburg Professor Puppe leads multiple significant research projects including KINERGY (optimization of heating systems), DZ-PTM (order entry optimization in radiology), Corpus Monodicum (edition of medieval Latin music), and projects related to adenoma detection in colonoscopy. His laboratory develops tools such as OCR4all for historical document processing and it4all for programming assessment.

Patricia Martín ChozasView profile

Researcher

• Semantic Web
• Legal Terminology
• Translation Technologies
• +3 more

Patricia Martín Chozas is a predoctoral researcher and PhD student at the Faculty of Computer Science, Polytechnic University of Madrid (UPM) , part of the Ontological Engineering Group. She holds a Master's Degree in Artificial Intelligence from UPM and a degree in translation from Complutense University of Madrid, specializing in technical aspects like audiovisual translation, localization, and translation technologies. Her research focuses on Linked Linguistic Data, multilingual terminology resources in legal domains, and Legal Knowledge Graphs under the European Lynx (H2020) project. She collaborates on initiatives like Open Summer of Code and contributes to projects such as the 3CEL corpus for legal Spanish contract clauses. Her work integrates Semantic Web standards, ontology engineering, and computational linguistics to address challenges in terminology representation and legal content analysis. She has practical experience in video game localization, project management, and translation tools development, alongside academic pursuits in web technologies and AI.

• Natural Language Processing (NLP)
• Artificial Intelligence (AI)
• Translation Technology
• +3 more

Ayla Rigouts Terryn is an Adjunct Professor at Université de Montréal's Faculty of Arts and Sciences, Department of Linguistics and Translation. She holds a Master's in Translation from the University of Antwerp and a PhD in Automatic Terminology Extraction from Ghent University. Her research focuses on improving language models through linguistically grounded approaches, emphasizing multilingual and specialized contexts. She leads the ACTER dataset project and co-leads research on lexical interactions between humans and machines. Research & Education PhD: Ghent University (D-Termine project) MSc: University of Antwerp (Translation) Mila (Quebec AI Institute) affiliation Research Interests : Automatic terminology extraction Computational linguistics Multilingual AI systems Bias analysis in large language models Specialized translation technologies Grants : FRQNT grant for translation bias research (2025-2028) FRQSC grant for lexical research team (2025-2030) Labs & Teams : LT3 Language and Translation Technology Team (Ghent University), Observatoire de linguistique Sens-Texte (OLST).

Ayla Rigouts TerrynView profile

Assistant Professor

• Automatic Terminology Extraction
• Machine Learning
• Language and Translation Technology
• +3 more

Ayla Rigouts Terryn is an Assistant Professor at KU Leuven, with a focus on language and translation technology. She previously served as a postdoctoral researcher at Ghent University's LT3 research group. Her research centers on computational terminology, particularly supervised machine learning approaches for monolingual and multilingual automatic term extraction. She developed the open-source ACTER dataset and organized the TermEval shared task, advancing methodologies in data-driven terminology research. Recent publications highlight her work on sequential labelling approaches (2022), hybrid term extraction frameworks (2019), and cross-lingual embeddings (2022). The ACTER dataset (2020) covers corruption, dressage, heart failure, and wind energy domains across English, French, and Dutch. FWO scholarship recipient for her EXTRACT project (2017) She co-lectures on Advanced Website Management at Ghent University, covering CMS development, web design principles, and team dynamics. Her tools, like D-Terminer, demonstrate practical applications of her research.

Regino CriadoView profile

Professor

• Complex Networks
• Discrete Mathematics
• Cybersecurity
• +4 more

Dr. Regino Criado is Full Professor of Applied Mathematics at Rey Juan Carlos University (URJC), where he has held academic positions since June 2000. He currently serves as Academic Director of the Data, Complex Networks and Cybersecurity Sciences Institute (since March 2017) and was elected to the Academia Europaea in May 2023. His career spans European research projects (ESPRIT II/III) and interdisciplinary collaborations at the intersection of mathematics, computer science, and cybersecurity. His research focuses on Complex Networks , including hyper-networks, multiplex networks, and mesoscale structures, with applications to cybersecurity, intentional risk management, and synchronization phenomena. Key innovations include: A game theory-based intentional risk model integrating accessibility, anonymity, and value metrics Hybrid network mining algorithms for credit card fraud detection PageRank extensions to multiplex networks Framework for discrete resilience analysis in technological systems His work on the 2014 Physics Reports monograph The structure and dynamics of multilayer networks (3,500+ citations) established foundational concepts in multilayer network theory. Current research explores linguistic pattern analysis through multilayer hypergraphs for automatic text summarization. Member of Academia Europaea (2023) Chaos Journal Best Paper Award (2011) Academic Entrepeneurs Prize (2002) EUROPA-1992 Prize (1992) As director of the DCNC Institute (2017-present) and BBVA-URJC Chair (2017-2018), he has led major academic-industry collaborations. His 180+ publications (6,500+ citations) demonstrate sustained impact across network science, applied mathematics, and cybersecurity.