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Roberto NavigliView profile

Professor

• Natural Language Processing
• Multilingual Natural Language Understanding
• Large Language Models
• +5 more

Roberto Navigli is a Full Professor in the Department of Computer, Control and Management Engineering at Sapienza University of Rome, where he leads the Sapienza NLP Group. He has held academic positions at Sapienza since 2007, progressing from Researcher to Associate Professor, and now Full Professor. Navigli is internationally recognized for his groundbreaking work in multilingual natural language processing and computational semantics. His research spans multiple areas within Natural Language Processing, with a particular focus on multilinguality , lexical semantics (Word Sense Disambiguation and induction), sentence-level semantics (Semantic Role Labeling and Semantic Parsing), and Large Language Models . As the leader of the Minerva LLM project, he pioneered the development of the first pretrained LLM in Italian. His creation of BabelNet, the largest multilingual encyclopedic computational dictionary covering 271 languages and about 14 million concepts, represents a landmark achievement in computational linguistics. Professor Navigli's recent publications demonstrate a strong focus on advancing multilingual capabilities of language models, addressing challenges in semantic understanding across languages, and developing robust evaluation frameworks. His work on Italian LLM optimization, lexical ambiguity in machine translation, and cross-lingual safety gaps reflects his commitment to building more accurate and reliable language technologies that work effectively across diverse linguistic contexts. AAAI Fellow (2025) EurAI Fellow (2024) ELLIS Fellow (2024) ACL Fellow (2023) Outstanding Paper Awards at ACL 2024, ACL 2023, and NAACL 2021 Best Resource Paper Award at ACL 2022 Prominent Paper Awards from the Artificial Intelligence Journal (2023, 2017) META Prize 2015 for BabelNet Professor Navigli has successfully secured substantial research funding, including two prestigious ERC Grants (MultiJEDI ERC Starting Grant 2010-2016 and MOUSSE ERC Consolidator Grant 2017-2023, totaling around 3 million euros), PI of PRIN 2017 and PRIN 2020 projects (overall 1.4 million euros), and a Google Focused Research Award (around 300k$). He has mentored over 30 PhD students, many of whom have gone on to successful careers in academia and industry. His leadership extends to major international conferences, serving as General Chair of ACL 2025 and Program Co-Chair of ACL-IJCNLP 2021. As the director of the Sapienza NLP Group and co-leader of the Transversal Project on Large Language/Multimodal Models in the FAIR (Future Artificial Intelligence Research) project, Professor Navigli oversees a vibrant research ecosystem focused on advancing the state-of-the-art in natural language understanding across languages. His spinoff company, Babelscape, translates academic research into practical applications for industry.

Naoki YoshinagaView profile

Associate Professor

• Natural Language Processing
• Computational Linguistics
• Multilingual and Multimodal NLP
• +4 more

Naoki Yoshinaga is a tenured Associate Professor at the Institute of Industrial Science, The University of Tokyo, with extensive experience in natural language processing and computational linguistics. He has held academic positions since 2008 and currently leads research on pragmatic NLP models and multilingual systems. PhD in Computer Science, The University of Tokyo (2005-2008) MSc in Information Science (2000-2002) BSc in Information Science (1996-2000) His research focuses on mechanistic interpretability in NLP models, multilingual/multimodal NLP , and efficient model design using trie structures and conjunctive features. He also investigates knowledge acquisition from social data and evaluation metrics for language generation . Recent publications include work on neuron empirical gradient analysis (ACL-25), multilingual knowledge representation (EACL-24), and compact embedding methods (CoNLL-24). His research has been funded by multiple grants, including the University of Tokyo Excellent Young Researcher program and JSPS fellowships. Committee Special Award, Association for NLP (2023) JSAI SIG Research Award (2022) Best Interactive Award, DEIM Forum (2019, 2016) He developed widely-adopted NLP tools like pecco (fast classification library), RenTAL (LTAG-to-HPSG grammar converter), and J.DepP (Japanese dependency parser). His lab emphasizes strong equivalence in formalism comparisons and pragmatic model design .

Martin VolkView profile

Professor

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

Martin Volk is a Full Professor of Computational Linguistics at the University of Zurich, with a dual affiliation to the Department of Informatics since 2019. He holds a PhD from the University of Koblenz and has held academic positions at institutions including Stockholm University (part-time from 2008-2011), Zurich University of Applied Sciences, and the University of Georgia. His research focuses on grammar engineering, machine translation evaluation, multilingual text analysis, and cross-language information retrieval. Education : Born in Cochem, Germany Studied Computer Science and Computational Linguistics at EWH University, Koblenz Master's in Artificial Intelligence at the University of Georgia (Fulbright Scholar) PhD in Computational Linguistics from the University of Koblenz Research Interests : His work emphasizes data-driven NLP methods, including corpus-based approaches, parsing technologies, and the application of machine learning to historical and multilingual texts. Key focuses include: Machine translation systems and evaluation frameworks Grammar testing environments (e.g., GTU) OCR and digitization of historical documents (e.g., Gothic script) Development of parallel corpora for linguistic research Projects : SMULTRON: Multilingual parallel treebank project Bullinger Digital: Historical document digitization initiative Text+Berg: Digital Humanities project for alpine textual heritage EU-funded MuchMore (cross-language medical IR) Grants & Collaborations : Recipient of grants from the Swiss National Science Foundation, EU projects, and industry partnerships (e.g., Siemens, Xerox). His work integrates academic and industrial perspectives in NLP tool development. Labs & Teams : Leads research teams in the Institute of Computational Linguistics at UZH, focusing on projects like the Zurich Parallel Corpus Collection and MODERN (modeling discourse for MT).

Erik VelldalView profile

Professor

• Natural Language Processing
• Machine Learning
• Sentiment Analysis
• +5 more

Erik Velldal is a Professor in the Language Technology Group (LTG) at the Section for Machine Learning , Department of Informatics, University of Oslo . With over 25 years of experience in machine learning and natural language processing (NLP), he leads the SANT project focused on sentiment analysis and contributes to major research initiatives including MediaFutures , NorwAI , and Integreat (Norwegian Center for AI Research). His work bridges linguistic theory and computational methods, emphasizing semantic modeling and uncertainty detection. Research interests include sentiment analysis , language modeling , event extraction , and machine learning applications to NLP. Recent publications address cross-domain sentiment classification , generative event analysis , and multilingual model adaptation . He co-developed the Norwegian Review Corpus (NoReC) and Norwegian Anaphora Resolution Corpus (NARC) , foundational resources for Norwegian NLP. His projects often involve collaboration with international institutions, reflected in publications at venues like ACL, COLING, and EMNLP. Current efforts focus on entity-level sentiment analysis , diagnostic datasets for Norwegian , and evaluating compositional generalization in language models. No public record of scientific awards or part-time appointments exists.

Sarah EblingView profile

Professor

• Computational Linguistics
• Assistive Technologies
• Sign Language Technologies
• +7 more

Sarah Ebling is a Full Professor of Language, Technology and Accessibility at the University of Zurich's Faculty of Arts and Social Sciences. She leads the Language, Technology and Accessibility research group within the Institute for Computational Linguistics. Her work focuses on computational linguistics applications for assistive technologies targeting disabilities such as hearing impairments, visual impairments, and cognitive disorders. Key areas include sign language technologies, automatic text simplification, and audio description systems. She directs the large-scale Swiss innovation project 'Inclusive Information and Communication Technologies' (2022-2026, CHF12 million budget) and collaborates on EU H2020 and SNSF Sinergia projects. Education: Holds a doctoral degree (summa cum laude, 2016) from the University of Zurich with research on automatic translation to Swiss German Sign Language. Completed studies in German Linguistics, Computational Linguistics, and English Linguistics at Universities of Zurich and Heidelberg, with research stays in Dublin, Chicago, and Rochester. Research emphasizes multimodal accessibility solutions, including sign language fluency assessment, gesture-based interaction, and AI-driven text adaptation. Current projects explore audio description translation systems (SwissADT), sign language corpus development (SwissSLi), and digital tools for comprehensibility assessment in simplified texts. Her work bridges computational linguistics with ethical considerations in assistive technology deployment. Grants and Leadership: Principal Investigator on major accessibility-focused grants, including the CHF12M Swiss innovation project. Supervises PhD candidates in areas like sign language assessment tools and text simplification algorithms. Active in international collaborations, publishing extensively in computational linguistics and accessibility journals/conferences. Technology Development: Created the 'DigiSpon' benchmark for language sample analysis and developed open-source tools for sign language translation baselines. Her team's innovations include the SignCLIP model connecting text and sign language via contrastive learning, and pose estimation frameworks for sign language recognition.

Ian QuinnView profile

Professor

• Music Theory
• Harmonic Analysis
• Music Cognition
• +4 more

Ian Quinn is the Allen Forte Professor of Music Theory and Director of Graduate Studies (DGS) at Yale University, within the Department of Music in the College of Arts and Science. He holds a B.A. from Columbia University (1993), M.A. and Ph.D. from the Eastman School of Music (1998, 2004). Prior to Yale, he taught at the University of Chicago and University of Oregon, and was a CASBS Residential Fellow at Stanford (2008-09). His research focuses on tonal harmony, corpus studies, music cognition, and the intersections of mathematics and computation in music theory. He edited the Journal of Music Theory (2004–2011) and co-organized the 2009 Society for Mathematics and Computation in Music conference. He leads the Yale-New Haven Regular Singing (YNHRS) shape-note singing group and serves on editorial boards for Journal of Mathematics and Music and the Northeast Music Cognition Group (NEMCOG). Quinn’s work has earned awards from the Society for Music Theory, including the Emerging Scholar Award (2004) and Outstanding Publication Award (2006/2007). His research spans analytical frameworks for harmonic function, corpus-based studies of tonal systems, and empirical investigations of music perception. He has advised over 15 doctoral students, many now in academic and industry roles. Key collaborations include co-authoring the Oxford Handbook of Corpus Studies in Music (2023) and developing the Yale-Classical Archives Corpus. His work bridges theoretical, computational, and historical approaches to music analysis, with contributions to Science , Music Theory Spectrum , and Perspectives of New Music .

• Computational Linguistics
• Psycholinguistics
• Language Processing
• +4 more

Richard Futrell is an Associate Professor at the University of California, Irvine (UCI), affiliated with the Department of Language Science. He leads the Language Processing Group, focusing on computational models of human and machine language processing. His work bridges information theory, Bayesian cognitive modeling, and natural language processing (NLP) interpretability. University of California, Irvine Department of Language Science Language Processing Group leader His research examines how linguistic structures emerge from cognitive and communicative pressures. Key areas include dependency locality, surprisal theory in sentence processing, and efficiency-driven language evolution. He investigates how memory constraints, predictability, and information density shape syntactic and morphological patterns across languages. Recent publications analyze code-switching efficiency, syntactic priming, ERP component modeling, and agent-based language contact simulations. His work frequently employs Bayesian modeling, neural network analysis, and cross-linguistic corpora to uncover universal principles in language processing. ACL Best Paper Award (2024) Best Paper Award for Computational Modeling of Language (2023) Marr Prize for Best Student Paper (2017) He has developed datasets like SPACER for error repair analysis and contributed to phonotactic learning frameworks. His collaborations span cognitive scientists, computational linguists, and neuroscientists, advancing understanding of language production, comprehension, and structural optimization.

Patrick T. BrandtView profile

Professor

• Political Dynamics
• Time Series Analysis
• Machine Learning
• +8 more

Patrick T. Brandt is a Professor of Political Science, Public Policy, and Political Economy at the University of Texas at Dallas , affiliated with the School of Economic, Political and Policy Sciences . His work integrates advanced statistical methods with political science, focusing on time series analysis, machine learning, and Bayesian modeling to study political dynamics. His research spans international relations , political economy , terrorist targeting , and conflict forecasting . He specializes in developing novel models for event count time series, including the Bayesian Poisson Vector Autoregression and MS-BVAR packages for R. His NSF-funded projects focus on event data generation and real-time conflict forecasting. Recent publications emphasize domain-specific language models (ConfliBERT variants), graph neural networks for conflict prediction, and machine translation challenges in political text analysis. He maintains the OpenEvent Data Repository and develops software like MSBVAR and PESTS for academic use. Scientific Awards : Robert H. Durr Award for Best Methodology Paper, Midwest Political Science Association (2006)

Frances YungView profile

Research Fellow

• Discourse Relations
• Computational Linguistics
• Natural Language Processing
• +4 more

Dr. Frances Yung is a Postdoctoral Researcher at Saarland University's Department of Language Science and Technology within the Department of Computer Science. She has been affiliated with Prof. Vera Demberg's research group since April 2017 and is currently working on the DFG-funded SFB-1102 project "Information Density and Linguistic Encoding," specifically on project B2 "Cognitive modelling of information density for discourse relations." She is pursuing her habilitation, indicating career progression toward a higher academic position in the German university system. Dr. Yung's research focuses on discourse relations at the intersection of NLP, corpus linguistics, and experimental psycholinguistics. Her work explores how information density affects discourse relation marking through cognitive modeling approaches. She has developed expertise in discourse parsing, resource construction, annotation aggregation, and experimental pragmatics, with particular attention to multilingual aspects of discourse phenomena. Her research combines computational modeling with experimental methods to understand how speakers produce and comprehend discourse relations. Analysis of Dr. Yung's recent publications reveals a strong focus on discourse relation resources, particularly multilingual corpora like DiscoGeM 2.0 covering English, German, French, and Czech. Her work increasingly incorporates crowdsourcing methodologies and examines how large language models can be leveraged for discourse annotation tasks. She has made significant contributions to understanding the challenges of implicit discourse relation annotation and the biases introduced by different task designs in crowdsourcing environments. Active reviewer for major computational linguistics conferences (ACL, EMNLP, NAACL, EACL, COLING, IJCNLP) and workshops since 2016 Served as area chair for Sigdial 2024 Regular service on program committees for discourse-related workshops Dr. Yung has supervised multiple Master's theses on topics related to discourse relations, implicit relation identification, and domain adaptation. Her teaching portfolio includes courses on crowdsourcing linguistic annotations, discourse relations from cognitive and NLP perspectives, and recent advances in discourse processing. She has also served as a teaching assistant for data science and AI courses, demonstrating her commitment to interdisciplinary education at the intersection of computer science and linguistics.

• Lexicology
• English for Specific Purposes
• Language of Color
• +3 more

Isabel Espinosa Zaragoza is an Assistant Professor in the Department of English Philology at the University of Alicante, Faculty of Philosophy and Letters I. She holds a PhD in Linguistic Studies (cum laude, 2022) and is renowned for her work in lexicology and English for Specific Purposes, particularly the language of color. PhD in Linguistic Studies (cum laude, University of Alicante, 2022) Master’s in English and Spanish for Specific Purposes (University of Alicante, 2016, extraordinary award) B.A. in English Philology (University of Alicante, 2014, extraordinary award) Her research focuses on lexical creativity, color terminology, and natural language processing applications for accessibility. She contributes to projects like CLEARTEXT (CENID) and leads in text simplification for cognitive disabilities. Published in journals: Procesamiento del lenguaje natural , Feminismo/s , Color Culture and Science Journal Book chapters with Cambridge Scholars Publishing and Universidad de Alicante She participated in 15 conferences (PICS 2022, BICLCE 2024) and contributed to 8 public research projects (2019-2025), including EU-funded initiatives. Teaching spans 10 years across 12 courses in English for International Relations, Cultural Management, and Computational Linguistics.

• Computational Linguistics
• Machine Translation
• Text Simplification
• +8 more

Sergiu Nisioi is an Associate Professor at the Faculty of Mathematics and Computer Science, University of Bucharest, with expertise in computational linguistics, machine translation, and text simplification. He bridges cognitive science with NLP through eye-tracking and EEG research, while also exploring sound art and digital autonomy via initiatives like HYPHA.ro. Current projects include PN-IV-P2-2.1-TE-2023-2007 (text complexity/readability), Legal Document Processing , and Europarl Dialectal Corpora Research spans computational psycholinguistics , LSTM-based translation models , and algorithmic composition for sound art His work integrates interdisciplinary methodologies, combining EEG signal processing for architecture data with the University of Architecture, and DSP for ecological projects at chlorophylla.live.

Philipp KoehnView profile

Professor

• Machine Translation
• Natural Language Processing
• Artificial Intelligence
• +2 more

Philipp Koehn is a Professor in the Department of Computer Science at Johns Hopkins University, with additional affiliation at the University of Edinburgh. His primary research focuses on statistical and neural machine translation, specifically developing methods to leverage large-scale digital information for cross-lingual communication. He leads the Machine Translation Research Group and maintains key resources like the Moses toolkit and Europarl corpus. His research interests span: Core machine translation techniques (statistical/neural approaches) Low-resource and unsupervised translation methods Cross-lingual representation learning Speech-to-speech translation systems Large-scale parallel data mining and alignment Evaluation methodologies for generated text Koehn's recent publications demonstrate strong focus on improving translation efficiency (dynamic compression, streaming models), robustness (noise handling, error correction), and accessibility (low-resource languages, radio speech processing). Key trends include multilingual generalization, document-level coherence, and human-centered evaluation. Significant scientific recognition includes: ACL Fellow (2024) IAMT Award of Honor (2015) European Inventor Award Finalist (2013) He currently advises PhD students Rachel Wicks, Elina Baral, Bismarck Odoom, and Weiting Tan. His Machine Translation Group develops widely-used open-source tools and organizes major conferences including WMT and MT Marathon.

Ondřej BojarView profile

Associate Professor

• Machine Translation
• Computational Linguistics
• Computer Science
• +9 more

Ondřej Bojar is an Associate Professor at the Institute of Formal and Applied Linguistics (UFAL), part of the Faculty of Mathematics and Physics at Charles University in Prague . He actively engages in research and teaching, with a focus on machine translation and computational linguistics. His work spans both theoretical and applied domains, involving collaborations with industry and academia.

Martina WernerView profile

Research Fellow

• Morphology
• Grammar Theory and Language Change
• Historical Linguistics
• +7 more

Martina Werner is a Senior Postdoc and Research Fellow at the Austrian Centre for Digital Humanities (ÖAW), affiliated with the Institute of German Studies at the University of Vienna's Faculty of Philology and Cultural Studies. She holds a habilitation in German Linguistics from the University of Vienna (2019) and a PhD from LMU Munich (2009). Her academic appointments include visiting professorships at Universität Würzburg (2024–2025) and LMU Munich (2019–2020), along with a guest professorship at the University of Vienna (2017/2018). Research Focus: Werner specializes in morphology, historical linguistics, and corpus-based approaches. Her work explores grammar theory, language change, syntax-morphology interfaces, and digital humanities methodologies. Current projects include FWF-funded research on relational adjectives in historical German (RAHiG) and the diachrony of nominalized infinitives. Publication Trends: Her recent articles (2016–2025) predominantly analyze diachronic morphology in German, focusing on nominalization patterns, compound structures, and suffix evolution. Corpus linguistics methodologies underpin her investigations into grammaticalization, language variation, and comparative Germanic linguistics. A strong interdisciplinary thread connects linguistic theory with empirical data analysis. Awards & Grants: FWF Project Funding: RAHiG – Relational Adjectives in the History of German (2019–2026) Elise Richter Project Grant: Diachrony of the Nominalized Infinitive in German (2014–2019) LMUMentoring Excellence Program (2008–2011) HWP Doctoral Scholarship (2005–2006) Academic Service: Werner co-leads research teams at ÖAW's Digital Humanities Centre, collaborates internationally on Germanic linguistics projects, and supervises academic initiatives through the Vienna Linguistic Society. Her teaching covers historical linguistics, morphology, and language development at undergraduate and graduate levels.

Maria MoruzView profile

Researcher

• Romanian linguistics
• Philology
• Phraseology
• +3 more

Maria Moruz serves as a Researcher at the Department of Social Sciences and Humanities, Alexandru Ioan Cuza University of Iasi, a position she has held since February 2009. Her academic profile centers on Romanian linguistic research with strong interdisciplinary connections to biblical studies and computational methods. She earned her PhD from Alexandru Ioan Cuza University of Iasi in December 2009 with a dissertation analyzing phraseological units in parallel bilingual corpora, establishing her foundational expertise in comparative linguistics. Maria Moruz's research program integrates traditional philological scholarship with modern computational techniques . Her primary domains include Romanian linguistics , phraseology , and computational linguistics , with significant contributions to Biblical philology through critical editions of historical texts. She examines national specificity in phraseological units while developing linguistic resources for Romanian language processing , bridging historical textual analysis with contemporary NLP applications. Her publication trajectory reveals distinct thematic phases: early computational linguistics work (2004-2012) on Romanian lexical resources and question-answering systems evolved into specialized biblical philology research (2014-present) within the Monumenta linguae Dacoromanorum project. Recent publications focus on Romanian lexicography and biblical marginalia, demonstrating sustained engagement with both digital humanities methodologies and historical textual criticism. Maria Moruz has secured significant research funding as Project Director for a CNCSIS TD grant and served as a POSDRU postdoctoral researcher. Her collaborative work includes membership in the international "Widespread Idioms in Europe and Beyond" project and leadership in multiple Romanian linguistics initiatives. Project Director: CNCSIS TD grant POSDRU Postdoctoral Researcher Collaborator: "Widespread Idioms in Europe and Beyond" project Co-organizer: International Symposium "Explorations in the Romanian and European Biblical Tradition" Founding Member: Romanian Association of Biblical Philology and Hermeneutics She maintains active scholarly infrastructure through editorial work on the Monumenta linguae Dacoromanorum series and organization of specialized symposia, fostering interdisciplinary dialogue between computational linguists, philologists, and biblical scholars.