Mark Liberman is a Trustee Professor at the University of Pennsylvania , holding appointments in the Department of Linguistics and Department of Computer and Information Science . He serves as Director of the Linguistic Data Consortium and Faculty Director of Ware College House . His career spans linguistics, speech technology, and computational methods. Education: Harvard University (1965-1969), MIT (M.S. 1972, Ph.D. 1975) Professional Experience: AT&T Bell Laboratories (1975-1990), University of Pennsylvania (1990-present) His research interests include: Corpus-based Phonetics : Analyzing speech patterns via large-scale datasets. Clinical Applications : Developing speech biomarkers for neurodegenerative diseases. Tonal Phonology : Studying lexical tone and intonation in languages like Yoruba and Mandarin. Formal Annotation Models : Creating frameworks for linguistic data standardization. Recent publications highlight automated speech analysis, cross-linguistic prosody, and digital biomarkers for conditions like ALS-FTD and Alzheimer’s. His collaborations span computational linguistics , neurology , and cognitive science . Scientific awards include the IEEE James L. Flanagan Award (2017), Antonio Zampolli Prize (2010), and fellowships from the AAAS and Linguistic Society of America . He advises PhD students May Chan and Jonathan Him Nok Lee and contributes to editorial boards for journals like Cognition and Annual Review of Linguistics . His work bridges speech science , language technology , and neurocognitive research .
Mark Y. Liberman is the Christopher H. Browne Distinguished Professor of Linguistics and Trustee Professor at the University of Pennsylvania. He holds a joint appointment in the Department of Linguistics and the Department of Computer and Information Science. His roles include Director of the Linguistic Data Consortium (LDC), Faculty Director of Ware College House, and former Director of the Institute for Research in Cognitive Science. Education: A.B. in Linguistics and Applied Mathematics from Harvard University (1965–1969), M.S. (1972) and Ph.D. (1975) in Linguistics from MIT. Research focuses on corpus-based phonetics, clinical linguistics applications, tonal phonology, formal models for linguistic annotation, and computational linguistics. He explores speech production, prosody, and interdisciplinary topics like language evolution and neurobiology of speech. Recent articles highlight advancements in speech biomarkers for neurodegenerative diseases, autism analysis, and computational linguistics. Awards include Fellowships from the AAAS and Linguistic Society of America. He advises graduate students and leads large-scale language resource initiatives like LDC, contributing to open-access linguistic datasets. Labs/Teams: Linguistic Data Consortium (LDC), Institute for Research in Cognitive Science (IRCS), and collaborations in computational linguistics and neuroscience.
Dawn Song is a Professor in the Department of Electrical Engineering and Computer Science at the University of California, Berkeley, affiliated with multiple research centers including the Berkeley Artificial Intelligence Research Lab (BAIR) and the Berkeley Center for Responsible, Decentralized Intelligence (RDI). She holds leadership roles in AI safety, cybersecurity, and blockchain research. Her work bridges machine learning, security, and distributed systems, with notable contributions to formal verification, privacy-preserving technologies, and AI governance. Education: Ph.D. (2002) and M.S. (1999) in Computer Science from UC Berkeley and Carnegie Mellon University, respectively. She previously served as an Assistant Professor at Carnegie Mellon University before joining UC Berkeley in 2007. Research Interests: Dawn's work focuses on AI safety, cybersecurity, and the ethical implications of frontier AI. She explores topics such as large language model vulnerabilities, zero-knowledge proofs, blockchain security, and policy frameworks for AI governance. Her research combines theoretical rigor with practical applications, addressing challenges in secure systems, adversarial machine learning, and privacy-preserving computation. Publications: Her recent work includes groundbreaking studies on LLM memorization, smart contract decompilation, and AI agent cybersecurity evaluation. She also leads initiatives like the Singapore Consensus and California Report on AI safety priorities, emphasizing global collaboration in risk mitigation. Notable Awards: MacArthur Fellowship (2010), ACM Fellow (2019), IEEE Fellow (2019) Advising & Grants: She advises projects on AI policy and cybersecurity, securing grants from NSF, DARPA, and industry collaborations. Her lab develops tools like CyberGym for evaluating AI agents and zkPyTorch for secure machine learning. Labs & Teams: Her research groups at UC Berkeley focus on cutting-edge projects in AI safety, blockchain, and cybersecurity, collaborating with industry leaders and policymakers to advance both technical and ethical standards.
Kenji Kawaguchi is the Presidential Young Professor in the Department of Computer Science at the National University of Singapore (NUS), where he leads the Deep Learning Lab and is a faculty affiliate at the NUS Institute of Data Science. His research bridges theoretical and applied machine learning, focusing on deep learning, large language models, and physics-informed neural networks. His educational background includes a Ph.D. and S.M. in Computer Science and Electrical Engineering from the Massachusetts Institute of Technology (MIT), advised by Leslie Pack Kaelbling, and a postdoctoral fellowship at Harvard University’s Center of Mathematical Sciences and Applications. Dr. Kawaguchi’s research interests center on the theoretical foundations of deep learning, optimization, generalization, and applications in areas such as molecular modeling, AI safety, and efficient training of large models. He has made significant contributions to understanding in-context learning, diffusion models, and neural operators for partial differential equations. His recent publications (2023–2025) reflect a strong trend toward improving the efficiency, robustness, and interpretability of large-scale models, particularly in language and scientific domains. Key themes include LLM alignment and safety, diffusion model optimization, and physics-informed learning for high-dimensional problems. Presidential Young Professor He has served as Area Chair and PC Member for top-tier conferences including NeurIPS, ICML, ICLR, AAAI, and UAI, and as reviewer for journals such as JMLR and Annals of Statistics. He has delivered invited talks at Harvard, MIT, Stanford, CMU, Brown, and Google Research, reflecting his international recognition. He actively mentors students and welcomes PhD candidates and postdocs to join his research group.
Mark Steedman is a Professor in the School of Informatics at the University of Edinburgh, where he conducts research in Artificial Intelligence, Computational Cognitive and Social Science, and Natural Language and Speech Processing. He is affiliated with the Institute for Language, Cognition and Computation (ILCC), the Centre for Speech Technology Research (CSTR), and the Human Communications Research Center (HCRC). He also holds an adjunct professorship in Computer and Information Science at the University of Pennsylvania. His research focuses on Combinatory Categorial Grammar (CCG) , computational linguistics , prosody and intonation , temporal semantics , gesture in communication , and computational music analysis . He has authored foundational books including Surface Structure and Interpretation , The Syntactic Process , and Taking Scope . The recent publications reflect a strong trend toward integrating formal grammatical frameworks like CCG with modern neural and distributional models, particularly in semantic parsing, entailment reasoning, and cognitive modeling. His work bridges symbolic and statistical approaches in NLP, often focusing on robust, wide-coverage parsing and semantic interpretation. Best Paper Award at AACL/IJCNLP 2023 for 'Smoothing Entailment Graphs with Language Models' Best Paper Award at ACL 2023 for 'Extrinsic Evaluation of Machine Translation Metrics' Influential Paper Award 2017 from IFAAMAS for 'Animated Conversation' Mark Steedman has supervised numerous PhD students and collaborated widely across institutions. He leads research in formal grammar applications to cognitive modeling, dialogue, and multimodal communication. His lab contributes to CCG software and semantic parsing tools, and he continues to be actively involved in advancing the integration of symbolic and neural AI.
Elaine Francis is a Professor of English and Linguistics at Purdue University's College of Liberal Arts, where she serves as Associate Head of the Department of English and directs the Experimental Linguistics Lab. She holds additional affiliations as an Affiliate Faculty Member in the Department of Linguistics and a Courtesy Faculty Member in the Department of Speech, Language, and Hearing Sciences. Ph.D. in Linguistics, University of Chicago (1999) B.A. in Linguistics, College of William and Mary (1993) MA in Linguistics, University of Chicago (1995) Former Assistant Professor at the University of Hong Kong (1999-2002) Professor Francis's research focuses on syntax and its interfaces with semantics, discourse information structure, and language processing in production and comprehension. She employs experimental methods to investigate syntactic, semantic, discourse-pragmatic, and cognitive factors underlying complex sentence structures. Her primary research areas include word order alternations, filler-gap dependencies, resumptive pronouns, and grammatical acceptability. She examines how various factors contribute to grammatical alternations in language use and explores how processing pressures in production and comprehension contribute to grammatical conventions. Her recent publication record shows consistent output across multiple linguistic subfields, with a strong emphasis on experimental syntax and psycholinguistics. Her 2022 book, Gradient Acceptability and Linguistic Theory , represents a significant contribution to understanding acceptability judgment tasks in relation to syntactic theory. Her work spans theoretical syntax, experimental linguistics, second language acquisition, and cross-linguistic comparison, often bridging the gap between theoretical frameworks and empirical evidence. Regularly teaches short courses at Linguistic Society of America Linguistic Institutes Member of Linguistic Society of America Ethics Committee Editorial board member of Glossa Psycholinguistics Co-editor of Polymorphous Linguistics: Jim McCawley's Legacy (2005) Co-editor of Mismatch: Form-Function Incongruity and the Architecture of Grammar (2003) Professor Francis actively supervises graduate students in linguistics, though she has indicated she will be unable to take on new graduate students for the 2025-2026 academic year. She has received research support for her experimental work, particularly for investigating syntactic phenomena through controlled experiments and corpus analysis. Her collaborative work extends across multiple institutions and disciplines, including collaborations with researchers in computational linguistics, cognitive science, and clinical linguistics. She directs the Experimental Linguistics Lab at Purdue University, which conducts research on syntactic processing using various experimental methodologies. The lab investigates how speakers produce and comprehend complex sentence structures, with particular attention to how grammatical knowledge interacts with processing constraints. Current projects include research on relative clauses, syntactic islands, and acceptability gradient phenomena across multiple languages.
Paulina Łęska-Bayraktar is an Assistant Professor in the Department of English-Polish Comparative Linguistics at the Faculty of English, Adam Mickiewicz University in Poznań, where she conducts research and teaches in formal syntax and comparative linguistics. Her academic foundation is deeply rooted in the same institution, reflecting a sustained commitment to linguistic scholarship in Poland. Her educational background includes: B.A. in English Linguistics, Adam Mickiewicz University in Poznań (2012) M.A. in English Linguistics, Adam Mickiewicz University in Poznań (2014) Ph.D. in English Linguistics, Adam Mickiewicz University in Poznań (2019) Her research interests lie at the intersection of syntax, semantics, and cognitive grammar, with a strong focus on generative approaches to Slavic languages—particularly Polish. She investigates complex syntactic phenomena such as binding theory, pronoun distribution, quantifier scope, agreement, and the structure of relative and nominal clauses. Her work combines formal theoretical analysis with empirical data, often drawing on acceptability judgments and psycholinguistic methodologies. The trends in her recent publications reveal a sustained engagement with the syntax of Polish, especially in non-canonical constructions involving dative arguments, experiencers, and pronominal clusters. Her work contributes significantly to the understanding of how universal syntactic principles manifest in Slavic morphosyntax, and she frequently collaborates with leading scholars like Prof. Jacek Witkoś. She has received research funding from the Polish National Science Center through multiple grants, including OPUS, Beethoven, and Miniatura projects, which have supported her investigations into nominal expressions, pronouns, and anaphora in Polish. These grants underscore the national recognition of her research contributions. Paulina Łęska-Bayraktar actively participates in the international linguistics community, presenting her work at major conferences such as Formal Approaches to Slavic Linguistics (FASL), Formal Description of Slavic Languages (FDSL), and the Poznań Linguistic Meeting. She is also involved in collaborative research teams and has co-authored works with scholars from Humboldt-Universität zu Berlin and other institutions. Her academic presence is further strengthened by her profiles on ORCID and ResearchGate.
Jiayi Lu is a PostDoc Researcher at the University of Pennsylvania School of Arts & Sciences, working under the supervision of Dr. Julie Anne Legate. Her research focuses on syntax, psycholinguistics, and Chinese linguistics, with a particular emphasis on grammaticality judgments, satiation effects, and island phenomena. She has contributed to understanding how sentence processing and discourse factors influence syntactic structures. Her research interests encompass syntax, psycholinguistics, and formal semantics, with a focus on exploring grammaticality illusions, the role of discourse in syntactic constraints, and cross-linguistic variations in Chinese. Key areas include the study of extraction islands, coordination effects, and the cognitive mechanisms underlying sentence processing. Her recent work (2020-2024) demonstrates a strong focus on syntactic satiation, island effects, and experimental methods in syntax. Publications analyze both English and Chinese data, investigating how linguistic structures are processed and judged by speakers. Trends include exploring the generalizability of satiation across island types and the interplay between discourse and syntactic constraints. Dr. Lu has not listed any scientific awards or grants in the provided information. Dr. Lu has not listed any advisees or grants in the provided information.
Prof. Stefan Müller is a Professor at the Institute for German Language and Linguistics , part of the Faculty of Languages and Literature at Humboldt University. His research focuses on syntax, formal grammar theories (especially Head-Driven Phrase Structure Grammar), and computational linguistics. He leads the CoreGram Project , developing cross-linguistic grammars using HPSG formalisms. His work includes analyses of German syntax, constituent order, anaphoric binding, and register phenomena. He is also involved in open-access publishing initiatives through Language Science Press . Contact: St.Mueller@hu-berlin.de . Education and academic background details are not explicitly stated in the provided text, but his professional trajectory indicates deep expertise in theoretical linguistics. His research spans multiple languages including German, Mandarin, and Persian, with a focus on grammar implementation and syntax-semantics interfaces. Key contributions include the Head-Driven Phrase Structure Grammar Handbook (2024), analyses of headless nominal structures in German (2022), and exploration of large language models' theoretical implications (2024). He actively engages in interdisciplinary projects bridging formal grammar and computational methods.
Marcin Wągiel is an Assistant Professor in the Department of Czech Language at the Faculty of Arts, Masaryk University, Brno, Czech Republic. His office is located in building D, room D.413 at Arna Nováka 1, with contact details including phone 549 49 8884 and email marcin.wagiel@phil.muni.cz. His research centers on theoretical and descriptive linguistics with emphasis on Czech language semantics and syntax. Key interests include degree/number constructions, part-whole structures, classifier systems, and temporal-modal interactions in natural language. He employs formal linguistic frameworks to analyze comparative and typological phenomena across languages, particularly within Slavic linguistics. Wągiel actively supervises doctoral research, currently guiding a thesis on temporal-modal semantics. He has secured significant research funding including Czech Science Foundation projects like Classification of classifiers (GA24-10073S, 2024-2026) and Part-whole structures across languages (GA20-16107S, 2020-2023). Additionally, he contributes to Masaryk University's student research programs supporting work in general linguistics, Indo-European studies, narratology, and Baltic studies.
Christopher Potts is Professor and Chair of Linguistics at Stanford University, with a courtesy appointment as Professor of Computer Science. He serves as Director Emeritus of the Stanford Center for the Study of Language and Information (CSLI) and leads the Pragmatic Enrichment & Contextual Interface Lab. His work bridges theoretical linguistics and computational approaches to language understanding. Education: B.A. in Linguistics from New York University (1999) Ph.D. in Linguistics from University of California, Santa Cruz (2003) Potts' research focuses on how computational methods can illuminate linguistic phenomena, particularly in the areas of semantics, pragmatics, and sentiment analysis. His work explores how emotion is expressed in language and how linguistic production and interpretation are influenced by context. He has made significant contributions to understanding conventional implicatures, sentiment analysis frameworks, and the application of neural networks to linguistic problems. His recent work has increasingly focused on the interpretability of large language models and the development of frameworks like DSPy for building reliable AI systems. An analysis of Potts' recent publications reveals a strong trend toward the intersection of linguistic theory and practical AI applications. His work spans theoretical linguistics (e.g., compositionality, preposing constructions), neural network interpretability, and practical NLP systems (e.g., ColBERT, DSPy). The research demonstrates consistent focus on making language models more transparent, controllable, and linguistically informed, with particular attention to how context shapes meaning. Scientific Awards: Best Paper Award at 2024 ACL for 'Mission: Impossible Language Models' Outstanding Paper Award at 2024 ACL for 'CausalGym' ACL Test of Time Award 2023 Dean's Award for Distinguished Teaching (2015-2016) Best New Data Set or Resource Award at 2015 EMNLP Potts has secured numerous research grants as PI or Co-PI from major organizations including Google, Amazon, NSF, Office of Naval Research, and Stanford's HAI institute. His current projects focus on evaluation of retrieval-augmented generation systems, LLM-mediated communication in organizations, interpretability techniques for language models, and frameworks like DSPy for building next-generation AI systems. He has mentored numerous researchers who have gone on to make significant contributions in NLP and computational linguistics. As Director of CSLI (2013-2020) and current Chair of Linguistics at Stanford, Potts has played a key leadership role in shaping interdisciplinary research at the intersection of language, computation, and cognition. His Pragmatic Enrichment & Contextual Interface Lab continues to be a hub for innovative research combining formal linguistic theory with cutting-edge computational methods.
Oleksandr Kapranov is an Associate Professor of English at NLA University College's Teacher Education program. His work intersects discourse analysis, climate change communication, and English language teaching (ELT), with a focus on sustainable development education and intercultural communication. Research areas include political speeches (e.g., Keir Starmer, Rishi Sunak), corporate disclosures (Bank of England, Vedanta Resources), and media framing (Greenpeace branches, King Charles III). Key pedagogical interests: digital competence, beginner EFL training, and discourse markers in academic writing. His recent publications analyze climate change discourse through syntactic structures, metonymy, modality, and evidentiality, emphasizing institutional and political narratives. While no formal awards are listed, his work spans interdisciplinary collaborations with NGOs, governments, and universities.
Nathan Martin is an Associate Professor of Music Theory at the University of Michigan, School of Music, Theatre & Dance. He joined in 2015 after postdoctoral fellowships at Columbia, Harvard, Katholieke Universiteit Leuven, Hochschule für Musik Freiburg, and Yale. He holds a PhD from McGill University’s Schulich School of Music (2009). His research focuses on the history of music theory and musical form analysis, particularly the works of Jean-Philippe Rameau and their reception among Enlightenment thinkers like Jean-Jacques Rousseau. He integrates intellectual history with practical analytical methods, emphasizing both contextual and emic perspectives. Recent interests include adapting empirical social science and linguistics methods to study musical form. Key publications include articles on Rameau’s harmonic concepts, Rousseau’s musical writings, and global music theory history. His 2014 article on Rameau’s supposition/suspension theories earned the Society for Music Theory’s Outstanding Publication Award. He co-edited Formal Functions in Perspective (2015) and served as co-editor of Music Theory & Analysis until 2019. Professional highlights include the Edward T. Cone Membership at the Institute for Advanced Study (2018–2019) and a 2023 visiting researcher role at the Max Planck Institute for Empirical Aesthetics. His work bridges historical analysis with contemporary empirical approaches, fostering interdisciplinary dialogue in music theory.
Pranav Anand is a Professor in the Department of Linguistics at the University of California, Santa Cruz (UCSC). He currently serves as the Faculty Director of the Humanities Institute at UCSC since July 2023. His research focuses on the interplay between context, interpretation, and grammatical perspective, particularly in areas like de re/de se contrasts, evaluative predication, and indexical shift. He has contributed to studies on narrative structures, evidential restrictions, and the syntax-semantics interface in sluicing. Dr. Anand has taught a variety of courses including Ling 119: Narratives , Ling 231: Semantics A , and special topics like Invented Languages: From Elvish to Esperanto . His work bridges theoretical linguistics with computational methods, evidenced by collaborations in projects such as the Santa Cruz sluicing dataset and analyses of political discourse in online commentary. His research has been published in journals like Linguistics and Philosophy , Language , and Discourse and Society , with a focus on semantics, pragmatics, and narrative linguistics. He has also contributed to computational linguistics initiatives, including the development of annotated corpora for sentiment analysis and argumentation studies. Dr. Anand's academic contributions span both theoretical exploration and applied computational linguistics, reflecting his interdisciplinary approach to understanding language structure and usage.
Jiwon Yun is an Associate Professor in the Department of Linguistics at Stony Brook University. She holds a Ph.D. in Linguistics from Cornell University (2013) and a B.S.E. in Computer Science & Engineering from Seoul National University (cum laude with honors). Her research focuses on speech prosody, syntax-semantics interfaces, and computational modeling of sentence processing, with special attention to East Asian languages like Korean, Mandarin, and Japanese. Dr. Yun teaches undergraduate and graduate courses in computational linguistics, semantics, pragmatics, and experimental phonetics. Her work bridges theoretical linguistics and experimental methods, examining how prosody interacts with syntactic and semantic structures. Recent publications investigate prosodic disambiguation of syntactic ambiguities, computational models of relative clause processing, and intonation patterns in Korean and Mandarin. She has developed tools for automated speech corpus analysis and maintains a Hangul-Yale Romanization Converter for linguistic research. Her research has been published in journals like Humanities and Social Sciences Communications , Linguistic Inquiry , and Journal of East Asian Linguistics . Teaching responsibilities include courses such as LIN 335 (Computational Linguistics) and LIN 627 (Computational Semantics).
