جست‌وجوی استاد و پژوهشگر

MARCOS GARCIA GONZALEZمشاهده پروفایل

پژوهشگر ارشد

• Computational Linguistics
• Natural Language Processing
• Multilingual Language Technologies
• +۳ مورد دیگر

Marcos Garcia Gonzalez is a Ramón y Cajal Research Fellow at the University of Santiago de Compostela (USC), affiliated with the Department of Spanish Language and Literature and the Center for Research in Intelligent Technologies (CITIUS). His research focuses on computational linguistics, particularly in semantic analysis, multilingual systems, and language technologies for Galician and Portuguese. He leads projects like the Nós Project, advancing Galician's integration into AI and NLP tools. His work includes developing resources like the Parallel Universal Dependencies Treebank and tools such as Bertinho (Galician BERT models). Key areas include idiomaticity detection in word representations, vector models for semantic analysis, and syntactic parsing. Education: PhD in Computational Linguistics from USC (2014), Master in Linguistics (University of Lisbon), and Degree in Portuguese Philology (USC). Postdoctoral research under the Juan de la Cierva fellowship (2016-2020). Awards include Ramón y Cajal and Juan de la Cierva fellowships. Research interests span vector models, multilingual NLP, and semantic compositionality. Projects include LINNA (linguistic-based neural models) and DeepR3 (green language tech). His publications explore topics like homonymy/synonymy representation and Galician language preservation through open-source tools. Key contributions include annotated corpora, coreference resolution systems, and cross-lingual parsing methods. He collaborates on hybrid intelligence systems for education (iRead4Skills) and Responsible AI (DeepR3.gal). Current efforts emphasize leveraging linguistic knowledge to enhance NLP models' interpretability and multilingual support.

Stephen Nealeمشاهده پروفایل

استاد

• Philosophy of Language
• Philosophical Logic
• Philosophy of Law
• +۶ مورد دیگر

Stephen Neale is a Professor of Philosophy and Linguistics at the Graduate Center, City University of New York (CUNY) . His research bridges Philosophy of Language, Philosophical Logic, and their intersections with Linguistics, Metaphysics, and Cognitive Science. He holds the John H. Kornblith Family Chair in the Philosophy of Science and Values and has been affiliated with CUNY since at least 2012. Ph.D., Stanford University (1988) Neale’s work explores intention, context, semantic composition, pragmatic inference , and the indeterminacy of meaning. His research extends to interdisciplinary applications in legal interpretation, archaeological theory, and cognitive science. He is a proponent of rigorous analysis of semantic and pragmatic boundaries in language and logic. The 15 most recent articles (2001–2016) reflect his focus on Philosophy of Language , with recurring themes of anaphora , contextual parameters , definite descriptions , logical form , and pragmatic enrichment . His scholarship engages deeply with Gricean pragmatics, Davidsonian semantics, and the theoretical underpinnings of linguistic interpretation. Scientific Awards : University of California President’s Fellow (1994) Rockefeller Fellow (Bellagio, Italy, 1995) National Endowment for the Humanities Fellow (1998) Guggenheim Fellow (2002) Neale has taught graduate and undergraduate courses in Philosophy of Language, Linguistic Pragmatism, Metaphysics, and Interpretive Practices at CUNY and Rutgers University. His editorial contributions include co-edited volumes such as Mind (Special Issue) and Descriptions and Beyond .

• Natural Language Processing (NLP)
• Interpretability of NLP Models
• Explainable AI
• +۴ مورد دیگر

Jenny Kunz is a Research Fellow at Linköping University's Department of Computer and Information Science (IDA), within the Artificial Intelligence and Integrated Computer Systems (AIICS) division. She holds a PhD in Computer Science from LiU (2024) and previously completed a Master’s in Language Technology from Uppsala University and a Bachelor’s in Computer Science from Humboldt University of Berlin. Her research focuses on interpretable and explainable NLP, including parameter-efficient language adaptation, self-rationalizing models, and understanding linguistic information storage in neural networks. She has contributed to studies on LLM-generated explanations, cross-lingual transfer learning, and the challenges of under-resourced languages. Kunz has taught courses such as Language and Computers and has held roles including Chair of the IDA PhD Council and co-representative on the IDA Board. Her work spans over 15 peer-reviewed publications in venues like ACL and COLING, addressing topics from model interpretability to multilingual NLP challenges.

• Natural Language Processing
• Machine Learning
• End-to-End Reasoning
• +۷ مورد دیگر

Dr. Nafise Sadat Moosavi is a Lecturer in Natural Language Processing at the University of Sheffield's School of Computer Science, and a Deputy School Head of ED&I. She holds a PhD from Heidelberg University, with prior postdoctoral research at the Technical University of Darmstadt's UKP Lab. Her research focuses on NLP and machine learning, including end-to-end reasoning, robustness, coreference resolution, text generation, sustainability, and evaluation metrics. Her academic journey includes bachelor's and master's degrees in computer science from Alzahra University and Sharif University of Technology, Iran. She leads projects like the Royal Society-funded 'Geometric Representations of Uncertainty for Foundation Models' (2025–2028). Her work emphasizes ethical AI, bias mitigation, and improving model generalization. Grants: £193,560 Royal Society Grant (PI) for foundational model uncertainty research Research Groups: Member of the University of Sheffield's NLP research group Key Themes: Debiasing NLU models, sustainable NLP practices, and advancing coreference resolution techniques Her publications span 2020–2025, addressing topics like hate speech detection, LLM limitations, and evaluation metric design. She co-organized workshops including SustaiNLP and contributed to datasets like PeerQA and SciGen.

• Computational Linguistics
• Corpus Linguistics
• Discourse Analysis
• +۶ مورد دیگر

Amir Zeldes is an Associate Professor in the Department of Linguistics at Georgetown University, where he leads the Corpling@GU Corpus Linguistics lab. He serves as President of the ACL Special Interest Group on Annotation (SIGANN). His primary research focuses on computational models of discourse, including referentiality and discourse relations, leveraging multilayer corpus studies to advance NLP and linguistic theory. Zeldes holds a Ph.D. from Humboldt Universität zu Berlin, complemented by an M.A. and B.A. in linguistics from Humboldt and the Hebrew University of Jerusalem. His work emphasizes discourse analysis, coreference resolution, and annotation frameworks, with contributions to Universal Dependencies treebanks and discourse parsing benchmarks like DISRPT. Zeldes has authored influential texts such as Multilayer Corpus Studies (2018/2020), exploring methodologies for parallel linguistic analyses. His research bridges theoretical linguistics and computational tools, addressing challenges in discourse signaling, entity salience, and cross-linguistic NLP applications. Zeldes' lab develops open-source tools for corpus creation and annotation, fostering interdisciplinary collaboration in computational linguistics. His recent projects include advancing discourse relation parsing, LLM evaluation, and historical language restoration through RNN models. Despite no listed awards, his extensive grants and publications reflect significant academic impact in NLP and corpus linguistics.

• Psycholinguistics
• Neurolinguistics
• Language Production
• +۵ مورد دیگر

Prof. Dr. Katharina Spalek serves as Professor of Psycho- and Neurolinguistics at Heinrich Heine University Düsseldorf's Faculty of Arts and Humanities within the Institute of Linguistics since her appointment in August 2021. Her research examines human language processing across multiple linguistic levels—from phonetics to narrative discourse—with particular emphasis on focus alternatives and memory mechanisms. Current affiliations include leadership of ERC-funded projects and active participation in international research collaborations. Her educational background spans German linguistics and psychology studies at Heidelberg University, University of Oxford, and Humboldt University Berlin, culminating in a doctoral degree from Radboud University Nijmegen (2005). Postdoctoral research followed in the USA and UK before her 2007 appointment as junior professor at Humboldt University Berlin. Spalek's research trajectory evolved from language production in monolingual/bilingual speakers toward language comprehension, investigating how humans process sounds, words, phrases, and narrative discourse. Recent work integrates electrophysiological (ERP), behavioral, and computational methods to explore focus alternatives, cross-linguistic variation (including Vietnamese tonal systems), and the interplay between linguistic and visual information. Her experimental paradigms frequently employ picture-word interference, recall tasks, and discourse analysis to uncover cognitive mechanisms underlying alternative set representation. Analysis of her 15 most recent publications (2019-2024) reveals three dominant trends: (1) neurocognitive investigation of focus alternatives using ERP methodology, (2) cross-linguistic studies of intonation and tonal processing, and (3) computational modeling of human performance in language tasks. These works consistently bridge theoretical linguistics with experimental validation, emphasizing memory encoding for contextual alternatives and individual differences in processing. ERC Starter Grant for 'focus alternatives in the human mind' (2016) Posterpreis at 17th Herbsttreffen Patholinguistik (2023) Her ERC-funded research program examines how focus particles and pitch accents modulate alternative set representation in production and comprehension. Current projects investigate neural correlates of discourse memory, Vietnamese intonation patterns, and computational models of human language processing limitations. Collaborative work spans institutions in Germany, Netherlands, and Vietnam, with methodological emphasis on controlled experiments and cross-linguistic comparison. Spalek leads the Psycho- and Neurolinguistics research group within the Institute of Linguistics, utilizing facilities for ERP recording, eye-tracking, and behavioral experimentation. Her team conducts interdisciplinary research at the intersection of linguistics, cognitive science, and neuroscience, with particular focus on how information structure shapes language processing and memory.

James Martinمشاهده پروفایل

استاد

• Artificial Intelligence
• Cognitive Science
• Natural Language Processing
• +۵ مورد دیگر

James Martin is a Professor of Computer Science at the University of Colorado at Boulder and a Fellow in the Institute of Cognitive Science. He holds a B.S. in Computer Science from Columbia University and a Ph.D. in Computer Science from the University of California at Berkeley. His research focuses on computational semantics, particularly how languages convey meaning to humans and computers, with a specific emphasis on metaphor processing and non-literal language analysis. He co-authored the widely used textbook Speech and Language Processing (3rd edition in progress), and his work extends to applications in healthcare and education through projects like the TalkMoves dataset analyzing classroom discourse. Current research includes cross-document event coreference resolution, AMR parsing tools (e.g., X-AMR), and AI-driven educational systems via the Institute for Student-AI Teaming (iSAT). Education History: Bachelor of Science in Computer Science, Columbia University Doctor of Philosophy (Ph.D.) in Computer Science, University of California, Berkeley Research Interests: Natural Language Processing (NLP) and Computational Linguistics Metaphor Analysis in Language and AI Semantic Parsing and Knowledge Representation AI Applications in Healthcare and Education Dialogue Systems and Classroom Discourse Analysis Recent Work Trends: His 2023-2024 publications emphasize multimodal NLP, cross-document semantic analysis (e.g., event coreference resolution), and AI tools for education (e.g., TalkMoves application for teacher feedback). NSF-funded National AI Institutes collaborations highlight strategic technology development. No scientific awards explicitly listed, though his textbook and research contributions are widely recognized in the field. Currently not actively recruiting PhD students. Labs/Teams: Core contributor to NLP initiatives at University of Colorado, particularly in semantic parsing and educational AI through iSAT. Involved with projects like the TalkMoves dataset and AMR annotation tools (CAMRA, X-AMR).

• Natural Language Processing
• Computational Linguistics
• Machine Learning
• +۳ مورد دیگر

Dr. Don Tuggener is a Researcher at the ZHAW Zurich University of Applied Sciences' School of Engineering, affiliated with the Centre for Artificial Intelligence. His work focuses on Natural Language Processing (NLP), Computational Linguistics, and Machine Learning applications in professional training and AI evaluation. He leads or collaborates on projects such as Meaning@Work (stress management for healthcare professionals), Virtual Kids (child interrogation training), and Favi-Score (bias detection in AI evaluation). His research emphasizes dialogue systems, generative AI ethics, and legal text analysis. Key projects include developing frameworks for conversational AI evaluation (Spot The Bot), large-scale legal text classification (LEDGAR corpus), and innovative training tools using LLMs. He has contributed to over 30 peer-reviewed publications since 2011, spanning topics like compound splitting in German, coreference resolution, and generative AI applications in professional contexts. As an editor for SwissText conferences and reviewer for ACL/EMNLP, he actively participates in the NLP academic community. Project Leadership: Virtual Kids, Interscriber Deputy Leadership: AutoNews, PRISM, SCAI Core Research Themes: AI ethics, dialogue systems, legal NLP Recent work highlights AI's role in professional education (e.g., investigative interviews with children) and societal challenges (hate speech mitigation via social influencers).

• Georgian Language
• Computational Linguistics
• Natural Language Processing
• +۳ مورد دیگر

Aleksandre Maskharashvili serves as Assistant Professor in the Department of Linguistics at the University of Illinois Urbana-Champaign, specializing in computational approaches to linguistic theory with particular expertise in Georgian language processing. His research profile reveals deep engagement with: Formal grammatical frameworks (Abstract Categorial Grammar, Tree Adjoining Grammar) Probabilistic semantics and Bayesian inference models Discourse relation analysis and connective generation Computational treatment of anaphora and coreference Neural language model applications for linguistic tasks Georgian language-specific computational challenges Analysis of recent publications (2021-2023) shows a pronounced shift toward integrating probabilistic reasoning with neural architectures in linguistic theory, particularly in natural language semantics and discourse generation. His work bridges theoretical linguistics with practical computational implementations, emphasizing how discourse relations enhance pre-trained language model performance.

Elizabeth Pankratzمشاهده پروفایل

مدرس

• Psycholinguistics
• Statistical Learning
• Cognitive Modeling
• +۳ مورد دیگر

Elizabeth Pankratz is a Lecturer in Psychology (Statistics) at the University of Edinburgh's Department of Psychology within the College of Humanities and Social Science. She specializes in teaching statistical methods for psychological research and maintains active contributions to computational research tools through GitHub repositories. Her research focuses on psycholinguistics and statistical learning mechanisms in language acquisition, with particular emphasis on rule formation, segmentation, and generalization processes. Current work investigates how frequency distributions facilitate linguistic rule generalization and the role of production in morphosyntactic learning. Her methodological approach combines computational modeling experimental paradigms like serial reaction time tasks corpus analysis simulation-based hypothesis testing Analysis of her 15 most recent publications reveals strong interdisciplinary connections between cognitive science, linguistics, and statistical methodology. Key trends include the investigation of scalar inferences under cognitive load, cross-linguistic register analysis, and computational approaches to coreference resolution in indigenous languages. Her work frequently employs simulation methods to formalize null hypotheses in cognitive science research. Pankratz has developed technical resources including a jsPsych 7 plugin for gathering serial reaction times to audio stimuli, demonstrating her integration of programming skills with experimental psychology. Her GitHub activity shows consistent contributions through 2025, including development of lecture materials and data playgrounds for statistical courses.

• Deep Learning for NLP
• Information Extraction
• Coreference Resolution
• +۵ مورد دیگر

Juntao Yu is a Lecturer in Computer Science at Queen Mary University of London's School of Electronic Engineering and Computer Science. Previously, he held a Lecturer position at the University of Essex and worked as a post-doctoral researcher at Queen Mary University on the ERC-funded DALI project under Professor Massimo Poesio. His PhD from the University of Birmingham focused on out-of-domain dependency parsing under Dr. Bernd Bohnet. Research Interests: Deep Learning for NLP, Coreference Resolution, Conversational AI, Dependency Parsing, Domain Adaptation, and Multi-task Learning. His work emphasizes scalable anaphora resolution systems, hybrid crowdsourcing approaches for corpus development, and cross-linguistic NLP challenges. He has contributed to major frameworks like the Universal Anaphora Scorer and the ARRAU corpus family. Yu's recent research explores large language model capabilities in coreference tasks and dialogue system evaluation. He maintains active collaboration with industry through projects like the CODI-CRAC shared tasks. Labs/Teams: Active member of the School's Natural Language Processing group and collaborator with the DALI project team.

Veronique Hosteمشاهده پروفایل

استاد

• Computational Linguistics
• Natural Language Processing
• Machine Learning
• +۷ مورد دیگر

Veronique Hoste is a Full Professor of Computational Linguistics at Ghent University's Faculty of Arts and Philosophy , where she serves as Department Head of the Department of Translation, Interpreting and Communication and Director of the LT3 Language and Translation Technology Team . Her work bridges machine learning with natural language processing, focusing on semantics, discourse modeling, and practical applications in emotion detection, irony recognition, and customer service dialogue analysis. PhD in Computational Linguistics from University of Antwerp (2005) 2023-2024: Francqui Chair at Université Libre de Bruxelles 2024: Elected to Royal Flemish Academy of Belgium (KVAB) Research Interests: Specializes in machine learning approaches to coreference resolution, sentiment analysis, and multimodal emotion detection. Leads projects like FlandersAI (empathy in conversational agents), METRICS (emotion trajectories in service dialogues), and SENTiVENT (financial event extraction). Develops high-quality datasets (e.g., EmotioNL , ENCORE ) for broader NLP community use. Recent Publications span Dutch social media irony detection, Classical Chinese poetry sentiment analysis, and multimodal emotion datasets. Collaborates on interdisciplinary initiatives like NewsDNA (news recommendation) and SentEMO (commercial sentiment analysis). Scientific Awards Francqui Chair (2023-2024) KVAB Membership (2024) Outreach includes co-founding AlfaSent (LT3 spin-off for customer feedback analysis) and authoring the first Dutch-language NLP book Taaltechnologie Ontrafeld (2024). Coordinates AI education initiatives like the AI at School project.

Shalom Lappinمشاهده پروفایل

استاد

• Natural Language Processing
• Machine Learning
• Deep Learning
• +۴ مورد دیگر

Shalom Lappin is a Professor of Natural Language Processing at the School of Electronic Engineering and Computer Science, Queen Mary University of London. He holds a dual affiliation as Chief Scientific Advisor at the Centre for Linguistic Theory and Studies in Probability (CLASP) at the University of Gothenburg. His research focuses on computational linguistics, deep learning, and probabilistic models applied to syntax, semantics, and grammar induction. He leads research in areas such as neural network architectures for compositional semantics, Bayesian inference semantics, and the application of machine learning to natural language understanding. His work bridges theoretical linguistics and computational models, emphasizing the cognitive plausibility of AI systems. His contributions include foundational texts like Deep Learning and Linguistic Representation and Foundations of Intensional Semantics . He has collaborated extensively on projects exploring gradient acceptability judgments, context effects in language processing, and the evaluation of large language models. Lappin's affiliations include roles in both academic and collaborative research centers, reflecting his commitment to advancing interdisciplinary research at the intersection of computer science, linguistics, and artificial intelligence.

Edoardo Barbaمشاهده پروفایل

پژوهشگر

• Natural Language Processing (NLP)
• Lexical Semantics
• Entity Linking
• +۵ مورد دیگر

Edoardo Barba is a full-time Researcher (RTDA) in the Department of Computer, Control and Management Engineering (DIAG) at Sapienza University of Rome. He is a core member of the Sapienza NLP group led by Professor Roberto Navigli, focusing on Lexical Semantics, Entity Linking, and Word Sense Disambiguation. His recent work explores descriptive modeling applications in Language Modeling, Semantic Role Labeling, and Machine Translation. He co-founded Litus AI, an NLP-focused startup in Rome. Barba holds a Ph.D. in Computer Science from Sapienza University (2023), with a thesis on 'Descriptive Modeling: Capturing Semantics in Neural Models via Natural Language Descriptions'. His research emphasizes innovative architectures like ReLiK (entity linking/relation extraction) and ExtEnD (extractive entity disambiguation), achieving state-of-the-art results. He has published extensively in top conferences like ACL, EMNLP, and IJCAI, focusing on semantic grounding, metric evaluation, and efficient NLP systems. His work on ConSeC (continuous sense comprehension) and DMLM (descriptive masked language modeling) highlights contributions to semantic understanding and knowledge-enhanced models. Selected Awards: None explicitly mentioned, though his publications reflect significant academic recognition. Grants/Advising: Not detailed in the provided text. Barba collaborates on multilingual resources like MOSAICo and explores Italian-specific LLM optimizations. His research bridges theoretical advancements with practical applications in startups and open-source tools.

Vered Shwartzمشاهده پروفایل

استادیار

• Natural Language Processing
• Computational Semantics
• Pragmatics
• +۴ مورد دیگر

Dr. Vered Shwartz is an Assistant Professor of Computer Science at the University of British Columbia (UBC) and a CIFAR AI Chair at the Vector Institute. Her research focuses on advancing natural language processing (NLP) with an emphasis on common sense reasoning, culturally-inclusive AI, and vision-language models. She holds a PhD from Bar-Ilan University and completed postdoctoral research at the Allen Institute for AI and the University of Washington. Her work addresses challenges in NLP such as cultural bias in AI systems, commonsense knowledge integration, and multimodal reasoning. Notable contributions include the WikiGap initiative to bridge knowledge gaps in multilingual Wikipedia editions and the CulturalBench benchmark for evaluating cultural competence in models. She teaches courses like CPSC 436N (Natural Language Processing) and CPSC 532V (Commonsense Reasoning in NLP) at UBC. Dr. Shwartz has received the Canada CIFAR AI Chair award (2022) and actively contributes to conferences and workshops on NLP fairness, commonsense reasoning, and ethical AI. Her research emphasizes the societal impact of AI, advocating for culturally aware and equitable systems.