Find Academic Supervisors

• Natural Language Processing
• Computational Linguistics
• Large Language Models
• +7 more

Yulan He is an active researcher in Natural Language Processing and Computational Linguistics with numerous publications in top-tier conferences including ACL, EMNLP, and COLING from 2023-2025. Their work spans both theoretical advancements in Large Language Model architectures and practical applications in healthcare, social media analysis, and information retrieval. Research interests focus on Large Language Model optimization , including improving faithfulness in rationale generation, enhancing reasoning capabilities, personalizing outputs to user preferences, and optimizing computational efficiency. Significant contributions include frameworks for debiasing opinion summarization, improving depression detection in clinical interviews, and developing methods for Theory-of-Mind reasoning in LLMs. Their work addresses critical challenges in LLM reliability, interpretability, and efficiency. Analysis of recent publications reveals consistent focus on bridging the gap between theoretical LLM capabilities and practical applications , with particular attention to healthcare contexts, social media analysis, and complex reasoning tasks. Their research demonstrates how to make LLMs more reliable, efficient, and aligned with human needs across diverse domains. Scientific contributions include: Novel frameworks for LLM faithfulness and reasoning (Drift, EnigmaToM) Efficient inference methods (SCOPE, PECAN) Bias mitigation techniques (LASS, Rehearse With User) Personalization approaches (PROPER) Healthcare applications (Explainable Depression Detection) As evidenced by senior authorship positions across numerous publications, Yulan He leads research projects and likely supervises graduate students in NLP research. Their work demonstrates strong technical expertise combined with practical problem-solving approaches to real-world NLP challenges.

• First Language Acquisition
• Typical and Atypical Language Development
• Genetic Disorders
• +8 more

Christiana Christodoulou is a Research Assistant Professor of Linguistics in the Department of Modern Languages at the University of Mississippi , with a focus on experimental and theoretical linguistics. She teaches courses such as Language and Mind , Psycholinguistics , and Syntax . B.A. in Linguistics, Aristotle University of Thessaloniki (1999) M.A. in Linguistics, University of Essex (2001) DB.A. in English Language and Literature, Aristotle University of Thessaloniki (2011) Ph.D. in Linguistics, University of British Columbia (2011) Her experimental research explores First Language Acquisition , Typical and Atypical Language Development , Genetic Disorders , and Neurolinguistics , particularly in Down Syndrome populations. The theoretical research focuses on Morphology , Syntax , and Functional Categories (e.g., case, tense, aspect) as well as Subjunctives and Interface Effects across linguistic domains. Christodoulou’s publications span topics from morphosyntactic development in Down Syndrome children to subjunctive clauses, coreference in Greek, and phonetic analysis of Cypriot Greek. Her work frequently intersects with Developmental Psychology , Neurolinguistics , and Formal Grammar . Marie Skłodowska-Curie Global Grant (2017–2021) Marie Curie Career Integration Grant (2012–2015) Canadian Commonwealth Scholarship Program (2005-2010) AHEPA Award for Outstanding Academic Achievement and Community Service (2009) Fieldwork and Research Award (2008) Her interdisciplinary work involves collaborations in Clinical Linguistics , Genetic Disorders , and Language Documentation , particularly in endangered Indigenous languages like Wenatchi.

Ben WellnerView profile

Lecturer

• Natural Language Processing
• Discourse Parsing
• Machine Learning
• +5 more

Ben Wellner is a Lecturer in the Department of Computer Science at Brandeis University and a Lead Scientist at The MITRE Corporation's Information Technology Center. His research spans Natural Language Processing, Discourse Analysis, Temporal Reasoning, and Biomedical Informatics. Current teaching: Statistical Natural Language Processing Key collaborations: Andrew McCallum, James Pustejovsky, Lynette Hirschman, and others Methodological focus: Sequence models, weakly supervised learning, and graph partitioning techniques Research trends from his publications include: Developing machine learning approaches for discourse structure analysis Creating adaptive systems for information extraction and coreference resolution Applying NLP techniques to biomedical data normalization Building temporally-aware models for text analysis

• Natural Language Processing
• Corpus Linguistics
• Augmentative and Alternative Communication
• +5 more

Anaïs LEFEUVRE-HALFTERMEYER is a Senior Lecturer at the University of Orleans, where she is affiliated with the LIFO (Laboratoire d'Informatique Fondamentale d'Orléans) research laboratory. She serves as a member of the DIAMS steering committee and is an associate member of both LIFAT and LLL research groups. Her academic profile reflects strong engagement with both teaching responsibilities and research activities in computer science with a human-centered focus. Dr. LEFEUVRE-HALFTERMEYER's research spans multiple interconnected domains within computational linguistics and human-computer interaction. Her primary interests include Natural Language Processing , Corpus Linguistics , and Augmentative and Alternative Communication systems. She has developed significant expertise in Explainable Artificial Intelligence approaches, particularly for image captioning systems, and has conducted substantial work on social media analysis, temporal annotation, and accessibility technologies. Her research consistently demonstrates a commitment to practical applications that address real-world communication challenges, especially in rehabilitation contexts. Analysis of her publication record reveals a clear trajectory from foundational corpus linguistics work toward increasingly applied research with strong human impact. Early publications focused on French spoken language treebanks and syntactic annotation tools, while more recent work addresses accessibility technologies, ethical considerations in AI, and explainability in vision-language models. There's a notable emphasis on bridging theoretical linguistic concepts with practical implementation, particularly for assistive technologies that serve people with communication disabilities. Dr. LEFEUVRE-HALFTERMEYER actively contributes to the academic community through mentorship and organizational roles. She has served as a mentor for student projects, including work on French language model comparison, and previously organized the JOLICO (JOurnées jeunes chercheurs de la LInguistique de COrpus) conference in 2015 as part of the scientific committee. Her institutional involvement includes membership on the DIAMS steering committee, demonstrating leadership within her research community.

Susan LeavyView profile

Assistant Professor

• Artificial Intelligence
• Text Mining
• Digital Humanities
• +6 more

Susan Leavy is an Assistant Professor at the School of Information and Communication, University College Dublin, affiliated with the Insight Centre for Data Analytics. Her research bridges artificial intelligence, text mining, and digital humanities, focusing on bias mitigation in machine learning algorithms and cultural analytics. PhD in Artificial Intelligence & Bias Detection, Trinity College Dublin MPhil in Gender and Women’s Studies MSc in Artificial Intelligence BA in Philosophy and English Literature Her work spans gender bias in AI , ethical data curation , multimodal bias analysis , and algorithmic transparency . Recent publications highlight interdisciplinary approaches to auditing generative models, mitigating bias through inclusive language, and socio-technical frameworks for AI safety. Key trends in her research include: cross-disciplinary methods for bias detection, ethical AI design informed by feminist theory, and security applications of machine learning for content moderation and network protection. She has developed tools like CURATR for historical text analysis and ARTAI for societal risk assessment in recommender systems, while advocating for feminist epistemology in data-centric AI.

• Natural Language Processing
• Machine Learning
• Dialogue Systems
• +3 more

Ana Valeria Gonzalez is a researcher in the Department of Computer Science at the University of Copenhagen's Faculty of Science, specializing in Machine Learning with a focus on human-centered natural language processing. Her work bridges computational linguistics and cognitive science within the department's Machine Learning research section. Her research investigates bias mitigation in multilingual systems, interpretable AI evaluation frameworks, and affect-aware dialogue generation. Key contributions include developing testbeds for gender bias analysis in coreference resolution, novel methodologies for evaluating model interpretability through reverse Turing tests, and retrieval-based approaches for goal-oriented conversational agents. She employs techniques spanning attention mechanisms, BiLSTMs, and domain adaptation to address challenges in low-resource NLP settings. Analysis of her 2019-2021 publications reveals a cohesive research trajectory toward building transparent, equitable NLP systems that account for human cognitive factors. Her work consistently addresses real-world deployment challenges, particularly in dialogue systems requiring emotional intelligence and cross-lingual fairness. Collaborations with Anders Søgaard, Isabelle Augenstein, and other Copenhagen researchers demonstrate strong integration within the university's AI ecosystem. Gonzalez completed her Ph.D. in 2021 with the dissertation "Towards Human-Centered Natural Language Processing". She maintains active research in the Machine Learning group, though specific advising roles and grant details aren't documented in the available materials. Her publication record shows significant impact with multiple Scopus-cited works and substantial reader engagement across platforms.

• Computational Linguistics
• Formal Grammar
• Type-Logical Grammar
• +4 more

Jose Oriol Valentin Fernandez Gallart is a researcher in the Department of Computer Science at the Faculty of Mathematics and Statistics (FME), Polytechnic University of Catalonia (UPC). With a substantial publication record spanning from 2004 to 2017, his work primarily focuses on computational linguistics and formal grammar systems. Dr. Fernandez Gallart's research centers on Type-Logical Grammar (TLG) , Displacement Calculus , and Lambek Calculus , with significant contributions to understanding grammatical formalisms for natural language. His work addresses complex linguistic phenomena including gapping constructions, anaphora resolution, and syntactic discontinuities. He has developed formal systems that bridge theoretical linguistics with computational applications, particularly in parsing algorithms and semantic interpretation. Analysis of his recent publications reveals consistent advancement in computational models of natural language. His research demonstrates how formal mathematical approaches can effectively model complex linguistic structures while maintaining computational tractability. Key contributions include extensions to displacement calculus for handling linguistic discontinuities and comprehensive analyses of Type-Logical Grammar's computational coverage. Dr. Fernandez Gallart has participated in significant research projects including "Aprendizaje Computacional y Comunicación" and "Gestió i Anàlisi de Dades Complexes," demonstrating broader engagement with computational approaches to language and data analysis. His extensive collaboration with Professor Glyn Morrill Verden (21 joint publications) indicates a strong research partnership in formal linguistics.

Andy KehlerView profile

Professor

• Pragmatics
• Discourse Interpretation
• Computational Linguistics
• +5 more

Andy Kehler is a Professor in the Department of Linguistics at the University of California, San Diego (UCSD), where he directs one of the Computational Linguistics Labs. His research focuses on pragmatics, discourse interpretation, and the computational modeling of linguistic phenomena. He has held academic roles including Chair of the Linguistics Department (2009–2014) and Director of Graduate Studies (2016–2018). He teaches courses such as 'Making and Breaking Codes' and 'The Language Code,' and advises graduate students in computational and theoretical linguistics. His lab explores interdisciplinary topics like discourse coherence, coreference resolution, and ellipsis, blending theoretical, computational, and psycholinguistic approaches. Editorial Roles: Academic Editor at PLOS ONE, Review Editor at Frontiers in Language Sciences, and Associate Editor at Journal of Logic and Computation. Teaching: Extensive record since 2000, including courses on pragmatics, computational linguistics, and semantics. Research Interests: Explores how discourse coherence drives linguistic interpretation, with emphasis on anaphora, ellipsis, and Bayesian models of pronoun resolution. His work bridges formal semantics, computational methods, and experimental psycholinguistics. Recent Articles: Focus on ellipsis theory, LLMs' pragmatic competence, and Bayesian models of German pronouns. These studies advance understanding of discourse structure and computational linguistics applications. Awards & Grants: Not explicitly listed, but his editorial roles and extensive publications reflect scholarly recognition. Active in securing grants for lab research and student support. Labs/Teams: Leads UCSD Computational Linguistics Lab, collaborating on projects like LLM analysis and discourse modeling. Engages with international academic networks through invited talks and visiting fellowships.

Christos TroussasView profile

Assistant Professor

• Adaptive Hypermedia Systems
• Artificial Intelligence in Education
• Human-Centered Artificial Intelligence
• +3 more

Christos Troussas is an Assistant Professor at the Department of Informatics and Computer Engineering, University of West Attica. His research focuses on adaptive hypermedia systems, artificial intelligence in education, human-centered AI, and human-computer interaction. He holds a PhD in Informatics from the University of Piraeus, along with MSc and BSc degrees in related fields. Education Background: PhD in Informatics, University of Piraeus MSc in Intelligent Technologies of Human-Computer Interaction, University of Piraeus BSc in Informatics, University of Piraeus Research Interests: His work emphasizes personalized software engineering, adaptive systems in education, and the integration of AI with pedagogical theories. He explores technologies like augmented reality (AR) and fuzzy logic for enhancing learning experiences, particularly for special education needs and spatial skill development. Publication Trends: Recent publications highlight advancements in neuro-symbolic systems, gamified learning environments, and reinforcement learning for adaptive interfaces. He consistently addresses challenges in educational technology adoption and user-centric design. Editorial & Professional Roles: Academic Editor of Advances in Human-Computer Interaction and Editorial Board member of multiple journals. Technical Program Committee member at international conferences. Grants & Collaborations: Participated in national/international research projects focusing on AI-enhanced educational tools and digital learning frameworks.

• Natural Language Processing
• Artificial Intelligence
• Data Science
• +3 more

Jorge Turmo Borras es profesor del Departament de Ciències de la Computació en la Universitat Politècnica de Catalunya. Forma part del Grup de Processament del Llenguatge Natural (GPLN) i del Centre de Tecnologies i Aplicacions del Llenguatge i la Parla (TALP). Su investigación se centra en procesamiento del lenguaje natural, inteligencia artificial y minería de datos clínicos. Investigación: NLP, Deep Learning, Salud Digital Colaboraciones: IDEAI-UPC, XarTEC Salut Sus intereses principales incluyen extracción de información de documentos médicos, resolución de anáforas mediante hipergrafos, y normalización léxica de microtextos. Ha publicado sobre modelado de temas para enlazado de entidades y detección de negaciones en textos clínicos. En los últimos 5 años ha trabajado en sistemas de asistencia para diagnóstico , procesamiento de tweets médicos , y redes neuronales para historiales de salud . Sus artículos destacan aplicaciones de Transformers, CRF y modelos híbridos. Patrocinadores: HORIZON 2020, Plan Estatal de Investigación 2021-2023, RIS3CAT. Colabora con investigadores como Alicia Ageno, Lluís Padró y Horacio Rodríguez-Hontoria.

• Natural Language Processing
• Computational Linguistics
• Language Model Interpretability
• +7 more

Anna Rogers is a leading researcher in Natural Language Processing (NLP), known for her foundational and critical work on language model interpretability, dataset quality, and the ethics of AI systems. She has published extensively at top-tier venues including ACL, EMNLP, and NAACL, often collaborating with prominent researchers like Anna Rumshisky and Isabelle Augenstein. Her research interests center on data curation , model generalization , responsible data use , and transparency in large language models . She has conducted influential surveys on community perspectives regarding intelligence in AI and has contributed to improving peer review practices in NLP conferences. Her work on BERTology, including papers like A Primer in BERTology and Revealing the Dark Secrets of BERT , has become key reading in the field. Recent publications highlight her focus on data transparency (e.g., the ROOTS Search Tool), synthetic content detection , and temporal annotation frameworks like NarrativeTime. She also investigates the robustness of models, probing techniques, and the limitations of current benchmarks. Her work consistently emphasizes methodological rigor and ethical considerations in NLP research. She has advocated for better data practices and more thoughtful evaluation paradigms across the community. Natural Language Processing Computational Linguistics Language Model Interpretability Dataset Curation and Quality Ethics in NLP Peer Review in Academic Conferences Anna Rogers has played a key role in shaping meta-discussions in the NLP field, including peer review reform and the societal impact of language technologies. She has co-organized workshops on negative results and contributed to tutorials on reviewing and data use. Her work bridges technical depth with critical reflection on the direction of the field. She has advised or collaborated with numerous researchers, though specific students are not listed in the available data. She has not received any explicitly mentioned scientific awards in the provided text. Anna Rogers leads or contributes to several open-source initiatives and shared resources, including the DECAF framework, the ROOTS Search Tool, and various datasets such as TimeBankNT and RuSentiment. Her work often includes released code and tools to promote reproducibility and further research.

• Information Retrieval
• Natural Language Processing
• Dialogue Systems
• +10 more

Prof. Dr. Udo Kruschwitz is a Full Professor of Information Science at the University of Regensburg since July 2019. Previously, he held a professorship at the School of Computer Science and Electronic Engineering, University of Essex. His research bridges Information Retrieval (IR) and Natural Language Processing (NLP), focusing on adaptive search systems, dialogue modeling, gamification for annotation, and ethical issues in search technology. Key projects: COURAGE (Volkswagen Stiftung-funded virtual companion for social media safety), SENSEI (Horizon 2020 conversational analytics), and collaborative works with industry (Signal Media, Minority Rights Group). Research themes include: IR/NLP integration Conversational systems Gamified annotation platforms (Phrase Detectives) Arabic language resources Privacy-preserving search strategies His publications span query suggestion algorithms, crowdsourcing validation techniques, and hate speech detection. He has co-organized major events like Search Solutions and GamifIR workshops, and founded the Data Science @ Regensburg meetup. Scientific awards include the 2015 InnovateUK Knowledge Transfer Partnership Project of the Year. Current teaching includes Advanced Topics in IR and Natural Language Engineering modules. Serves as Senior Academic Advisor for Signal AI and mentor for numerous doctoral candidates.

• Computational Linguistics
• Natural Language Processing
• Sociolinguistics
• +6 more

Rob Voigt is an Assistant Professor of Linguistics and Courtesy Professor of Computer Science at Northwestern University, directing the Linguistic Mechanisms Lab. He holds affiliations with the Institute for Policy Research and Cognitive Science Program. His research focuses on computational linguistics applied to social issues like policing, mental health, and immigration, using NLP methods to analyze body camera footage, historical texts, and social media discourse. Education includes a PhD in Linguistics (Stanford, 2019) with a dissertation on police-community interaction, an MA in East Asian Studies (Stanford, 2013), and a BA in Chinese from Vassar College (2008). He has received prestigious awards including the Cozzarelli Prize (2017) and Cialdini Prize (2018). Recent projects include multimodal policing analysis, cross-lingual NLP models (GreenPLM), and computational studies of French rap lyrics. He leads grants totaling $4.4M, including NIH-funded studies on psychosis indicators and language in autism. Teaching includes courses on computational linguistics and text processing for linguists. His lab explores intersections of language, technology, and social justice, with over 40 publications. Collaborations span social sciences, computer science, and public policy. He maintains a music career under 'facsimiles' and created the board game 'Who Got It?!'.

Peter JenksView profile

Associate Professor

• Syntax
• Crosslinguistic Variation
• Syntax-Semantics Interface
• +7 more

Peter Jenks is an Associate Professor in the Department of Linguistics at the University of California, Berkeley. He holds a Ph.D. in Linguistics from Harvard University, an M.A. from UC San Diego, and an A.B. from Dartmouth College. His research bridges syntax, semantics, and phonology, with specialization in East/Southeast Asian and African languages, particularly Thai and Moro. Research focuses on crosslinguistic variation in noun phrases, definiteness, quantification, and phonological domains. Recent work examines syntax-phonology interactions and indexed definiteness in understudied languages. Publications demonstrate consistent focus on interface phenomena, with recent articles exploring hyperraising in Moro (2025), definiteness in Guébie (2024), and syntactic quantification. His 55+ publications show strong emphasis on empirical fieldwork and theoretical innovation. UC Berkeley Distinguished Teacher Award (2023) Certificate of Distinction in Teaching, Harvard University (2008-2010) Outstanding Graduate in Linguistics, Dartmouth College (2004) Advises 16+ graduate students and serves on dissertation committees. Secured NSF and Hellman Faculty Fellowships. Co-directs the Moro Story Corpus project and co-authored a Moro grammar with Language Sciences Press.

Ali EmamiView profile

Assistant Professor

• Natural Language Processing
• Machine Learning
• Common Sense Reasoning
• +5 more

Ali Emami is an Assistant Professor in the Department of Computer Science at Brock University (Canada), with a tenure-track position at Emory University starting Fall 2025. His research focuses on natural language processing, machine learning, and AI ethics, particularly evaluating large language models' reasoning and societal impacts. He holds a PhD in Computer Science from McGill University/Mila (2021), with prior degrees from McGill in MSc (2016) and BSc (2014). Research interests include: Natural Language Processing (NLP) and Machine Learning Ethics, bias, and fairness in AI Language understanding and generation AI interpretability and reliability Computational social science Recent work emphasizes benchmarking LLMs' reasoning capabilities (e.g., NYT-Connections, STOP!) and addressing societal bias through books. Notable achievements include the COLING 2025 Best Dataset Award and the EMNLP 2024 Social Impact Award . He has supervised multiple undergrad and graduate researchers, with a focus on fostering collaborative projects. His lab explores personalized narrative generation (MirrorStories) and tool-augmented LLM evaluation frameworks (TALE). Upcoming roles include a talk at the FirstOntario Performing Arts Centre on LLMs' societal mirrors and a 2024 teaching award from Brock’s Faculty of Mathematics & Science.