جست‌وجوی استاد و پژوهشگر

Aditi Lahiriمشاهده پروفایل

استاد پژوهشی

• Phonology
• Phonetics
• Historical Linguistics
• +۳ مورد دیگر

Professor Aditi Lahiri is a Research Professor of Linguistics at the University of Oxford's Faculty of Linguistics, Philology and Phonetics. She holds positions in the Centre for Linguistics and Philology and directs the Language and Brain Laboratory. Her research focuses on phonology, phonetics, historical linguistics, psycholinguistics, and neurolinguistics, with special expertise in metrical theory, feature theory, and morphological complexity. Education : BA (Mathematics, Economics) from University of Calcutta (1971); MA (Comparative Philology) from University of Calcutta (1973); DPhil (Comparative Philology and Linguistics) from University of Calcutta (1979); PhD (Linguistics) from Brown University (1982). Research Interests : Her work spans experimental and theoretical linguistics, including prosodic phrasing, lexical representation, language change, and neural correlates of phonological processing. Key areas include: Metrical phonology and historical sound change Cognitive representation of speech sounds Morphological complexity in the mental lexicon Speech perception and production mechanisms Recent Research Trends : Over the past decade, her publications emphasize cross-disciplinary approaches, integrating experimental psycholinguistics with computational modeling (e.g., ERC-funded projects on morphophonological alternations). Recent work explores language processing in multilingual speakers and the neural basis of phonological features. Awards : Recipient of prestigious awards including the Leibniz Prize (2000), Max Planck Research Prize (1994), and Fellow of the British Academy (2010). She serves as Vice President of the British Academy and President of the Philological Society. Grants & Leadership : Secured over €8 million in research funding, including ERC Advanced Grants (e.g., MORPHON, WORDS). Directed the DFG-funded Sonderforschungsbereich 471 (2006-2008). Established key partnerships in India through endowed scholarships and academic outreach initiatives. Labs & Collaborations : Leads the Language & Brain Laboratory, collaborating internationally on projects combining neurolinguistic methods with historical and experimental linguistics. Supervised numerous PhD students who have become leading academics globally.

Mykel Loren Brinkerhoffمشاهده پروفایل

پژوهشگر

• Phonology
• Phonetics
• Linguistic Fieldwork
• +۳ مورد دیگر

Mykel Loren Brinkerhoff is a Postdoctoral Research Associate and Acting Phonetics Lab Director in the Department of Linguistics at the University of Washington. His research focuses on phonology, phonetics, and linguistic fieldwork, particularly on Mesoamerican languages like Santiago Laxopa Zapotec. He investigates syntactic and prosodic phenomena in Celtic and Germanic languages and collaborates on projects such as the Zapotec Language Project. Brinkerhoff has taught at the University of California, Santa Cruz, and the University of North Carolina at Chapel Hill, leading courses in phonetics, phonology, and syntax. He mentors students in fieldwork and linguistic analysis, with notable projects on Zapotec voice quality and Scandinavian syntax. His work bridges theoretical linguistics with empirical research, contributing to our understanding of phonological interfaces and language structure. His publications explore topics like voice quality in Zapotec, Norwegian object shift, and Welsh morphophonology. He actively contributes to academic discourse through presentations at conferences like LabPhon and SSILA. Brinkerhoff’s research also emphasizes documenting endangered languages and advancing methodologies in acoustic phonetics.

Ellie Pavlickمشاهده پروفایل

استادیار

• Language Acquisition
• Grounded Language Learning
• Neural Language Models
• +۷ مورد دیگر

Ellie Pavlick is an Assistant Professor of Computer Science and Linguistics at Brown University, where she leads the Language Understanding and Representation (LUNAR) Lab . Her work bridges computational linguistics and cognitive science, focusing on grounded language learning and the structural dynamics of neural language models. PhD from University of Pennsylvania (2017), specializing in paraphrasing and lexical semantics Collaborates with Brown's Robotics, Visual Computing labs, and Cognitive, Linguistic, and Psychological Sciences department Research interests center on cognitively-inspired approaches to language acquisition, analyzing how LLMs and humans encode abstract reasoning and compositional structures. Her lab explores: Grounded language learning in multimodal systems Emergence of compositional behavior in neural networks Interpretability frameworks for black-box AI Key publication areas include: Transformer mechanisms and cognitive modeling Formality and complexity in language systems Relational reasoning and multimodal integration Ellie teaches courses on computational linguistics and human-machine language processing, with a focus on synergies between AI and psychological science.

Jeffrey Heinzمشاهده پروفایل

استاد

• Theoretical Linguistics
• Computational Learning Theory
• Phonology
• +۳ مورد دیگر

Jeffrey Heinz is a Professor at Stony Brook University, with a joint appointment in the Department of Linguistics and the Institute for Advanced Computational Science. He holds a Ph.D. from UCLA (2007) and previously served on the faculty at the University of Delaware from 2007–2017. His research bridges theoretical linguistics, computational learning theory, and formal language models, focusing on phonology, linguistic typology, and grammatical inference. He has contributed to influential works on computational phonology and edited volumes on topics like phonological stress and learning theory. Key academic achievements include the 2017 Linguistic Society of America Early Career Award for contributions to computational inference in language. His work emphasizes the intersection of formal models and empirical linguistics, with applications to reduplication, phonological processes, and machine learning benchmarks like MLRegTest. Heinz has co-authored a book on grammatical inference and guest-edited special issues in Machine Learning and Phonology . His research also extends to interdisciplinary applications, such as modeling human-robot interaction and pediatric motor rehabilitation through grammatical inference techniques.

Nicolas Davidenkoمشاهده پروفایل

دانشیار

• Cognitive Psychology
• Perception
• Face Recognition
• +۵ مورد دیگر

Nicolas Davidenko is an Associate Professor in the Department of Psychology at the University of California, Santa Cruz (UCSC). He leads the High Level Perception Lab, focusing on behavioral and computational studies of human perception, particularly face recognition, spatial orientation, and visual ambiguity. His work emphasizes 'top-down' processes like attention and expectations. Davidenko holds a Ph.D. in Psychology from Stanford University (2006), an M.S. in Statistics from Stanford (2004), and an A.B. in Mathematics from Harvard (1998). His research explores how humans perceive and interpret complex visual information, including studies on illusions, virtual reality, and misophonia. He has developed parametric models of faces to study memory encoding and drawing accuracy. Notable achievements include a Top-10 Finalist placement in the 2015 Best Illusion of the Year Contest for his 'Mind-controlled motion' research. He teaches courses such as PSYC 121 (Perception), PSYC 139K (Face Recognition), and advanced cognitive research seminars. Davidenko also runs the CSASS Matlab Workshops, training researchers in statistical tools. His lab includes graduate students and postdocs, with alumni like Jennifer Day (Ph.D. ’19) and Pat Samermit (Ph.D. ’18). Recent projects include investigations into vection in VR environments, cross-sensory modulation of aversive sounds, and time perception in virtual reality. His work bridges cognitive psychology, neuroscience, and computational modeling, contributing to understanding how perception shapes human interaction with the environment.

Cecilia R. Aragonمشاهده پروفایل

استاد

• Human-Centered Data Science
• Human-Centered Artificial Intelligence
• Human-Computer Interaction
• +۵ مورد دیگر

Cecilia R. Aragon is a Professor in the Department of Human Centered Design & Engineering at the University of Washington, where she also serves as an Adjunct Professor in Computer Science & Engineering, Electrical and Computer Engineering, and the Information School. She is additionally a Senior Data Science Fellow at the eScience Institute. Aragon directs the Human-Centered Data Science Lab and has made significant contributions at the intersection of human-computer interaction and data science. Her research interests focus on human-centered data science, human-centered artificial intelligence, human-centered machine learning, human-computer interaction (HCI), computer-supported cooperative work (CSCW), visual analytics, aviation and astronautics sociotechnical systems, and emotion in informal text communication. Aragon's work bridges technical and social aspects of data science, particularly examining how humans interact with and gain insight from large datasets through both quantitative and qualitative methods. Aragon's recent publications demonstrate a strong focus on understanding online communities, sentiment analysis, distributed mentoring systems, and the ethical implications of AI. Her work spans multiple disciplines including social computing, data visualization, and astrophysics data analysis, showing her interdisciplinary approach to human-centered data science. Presidential Early Career Award for Scientists and Engineers (PECASE) 2008 Fulbright Fellowship 2017-18 HCDE Faculty Innovator in Research Award, University of Washington, 2015 Distinguished Alumni Award, Computer Science, University of California, Berkeley, 2013 Top 25 Women of the Year, Hispanic Business Magazine, 2009 Aragon has secured over $28 million in research funding from organizations including the National Science Foundation, National Institute of Standards and Technology, Department of Energy, Gordon and Betty Moore Foundation, Alfred P. Sloan Foundation, Washington Research Foundation, and industry partners like Microsoft and Intel. Her educational background includes a Ph.D. in Computer Science from UC Berkeley (2004), an M.S. in Computer Science from UC Berkeley, and a B.S. with Honors in Mathematics from Caltech. She leads the Human-Centered Data Science Lab and is affiliated with the eScience Institute, the Nearby Supernova Factory, and various research groups focused on data-intensive scientific collaborations. Her work on collaborative visual analytics systems like Sunfall has had significant impact in both academic and applied settings.

Oliver Bondمشاهده پروفایل

دانشیار

• Linguistic Typology
• Morphology
• Syntax
• +۶ مورد دیگر

Oliver Bond is a Reader in Linguistics (Associate Professor) at the University of Surrey, affiliated with the Surrey Morphology Group (SMG) within the School of Literature & Languages. He holds a PhD from the University of Manchester and specializes in linguistic typology, morphology, syntax, and language documentation. His research focuses on the systemic properties of language, particularly in African and Himalayan languages, exploring features like agreement systems, case marking, and morphological complexity. Key roles include Deputy Director of SMG and PhD Coordinator. His research projects include studies on Nuer (South Sudan/Ethiopia), Tibeto-Burman languages of Nepal, and prominent internal possessors. He has received a prestigious British Academy Award for his work on language evolution and analogy in morphological change. Bond supervises PhD students in areas such as morphology, syntax, and language documentation. Notable former students include Dávid Győrfi and Tatiana Reid. His publications span typological studies, language documentation, and theoretical morphology, with recent work on contact effects in Tibeto-Burman languages and negation systems in African languages. Bond’s contributions include collaborative projects like the Nuer Literacy Initiative and the Manang Languages Project. He actively publishes in journals like Journal of Linguistics and Linguistic Typology , and maintains a comprehensive resource, the Nuer Lexicon .

Stefania Degaetano-Ortliebمشاهده پروفایل

دانشیار

• Computational Linguistics
• Corpus Linguistics
• Sociolinguistics
• +۶ مورد دیگر

Stefania Degaetano-Ortlieb is an Associate Professor of English Linguistics and Corpus Linguistics at Saarland University's Department of Language Science and Technology. She serves as Principal Investigator for the Collaborative Research Center (SFB 1102) 'Information Density and Linguistic Encoding,' leading Project B1 on diachronic information density in English scientific writing (17th century-present). Her interdisciplinary work bridges computational methods with sociolinguistics, focusing on register variation, language change, and digital humanities. Research interests center on text mining, data analytics, and probabilistic modeling of language variation. Key areas include: Diachronic evolution of scientific registers and linguistic densification Information-theoretic approaches to language efficiency Computational sociolinguistics and register diversification AI applications in humanities education (e.g., ChatGPT integration) Her publications show a strong trend toward quantitative diachronic analysis, with recent work emphasizing: interpretable AI models for linguistic change detection; propagandistic narrative analysis in conflict zones; and multi-word expression dynamics in scientific discourse. Cross-disciplinary collaborations frequently intersect with history, psychology, and media studies. Awards include the Fellowship Excellence Program for Young Female Scientists (2015-2018). Current grants: EU Horizon MSCA Doctoral Network 'CASCADE' (€521K to UdS, 2024-2027) Data-Pin Project for AI in education (€50K, 2023-2024) SFB 1102 Project B1 (€595K, 2022-2026) Advises PhD candidates in the EU CASCADE project on computational semantic change. Leads a research team exploring Russian media narratives, personality modeling in LLMs, and multi-word expressions. Directs teaching modules integrating AI tools for humanities students.

Max Pellertمشاهده پروفایل

استادیار

• Computational Social Science
• Digital Traces
• Affective Expression
• +۹ مورد دیگر

Max Pellert is a computational social scientist and cognitive scientist with faculty appointments at multiple institutions. Since 2022, he has served as an Assistant Professor at the Chair for Data Science in the Economic and Social Sciences at the University of Mannheim . He previously held an interim Professor position at the University of Konstanz and an Assistant Researcher role at Sony Computer Science Laboratories Rome. His work bridges computational methods with social science theory. Education M.Sc., University of Vienna (2017) in Middle European interdisciplinary Master's program in Cognitive Science (with distinction) Ph.D., Medical University of Vienna (2022) in Medical Informatics, Biostatistics & Complex Systems Research interests center on Computational Social Science , Digital Traces , and Natural Language Processing for emotion and sentiment analysis. He develops Temporal Adapters for tracking longitudinal emotional patterns and FAULTANA pipeline for polarization studies. His AI Psychometrics framework assesses personality-like traits in large language models. Recent publications include: (1) 2025 ACL work on political bias in LLMs; (2) 2025 ICWSM study of temporal emotion analysis; (3) 2024 Perspectives on Psychological Science paper on LLM psychometrics; (4) 2024 PNAS Nexus polarization analysis; (5) 2023 Emotion cross-cultural study of pandemic emotions. Scientific Awards Habilitation candidate status at University of Mannheim Teaching includes IS 616: Large Scale Data Analysis , IS 809: Advanced Text Mining Lab , and IS 723: Data Science Seminar at master’s and PhD levels. His Barcelona Supercomputing Center role focuses on principal investigator duties for computational social science projects.

• Computational Social Science
• Text-as-data methods
• Natural Language Processing
• +۷ مورد دیگر

Kenneth BENOIT is the Dean and Full-time Professor of Computational Social Science at the School of Social Sciences, Singapore Management University (SMU). Previously, he served as Director of the Data Science Institute at the London School of Economics (LSE) from 2020 to 2024. He holds a PhD in Government from Harvard University, specializing in statistical methodology. His research focuses on computational methods for analyzing textual data, particularly political texts and social media. Key areas include text-as-data techniques, natural language processing, and the application of large language models in social sciences. He has pioneered methods combining machine learning with crowd-sourced coding to improve the accuracy of political text analysis. Ken’s work emphasizes the analysis of big data, electoral systems, and comparative party competition, with notable contributions to the European Parliament and policy positioning studies. His expertise extends to software development, including R packages like quanteda and spacyr , which are widely used in text analysis. His articles and publications span methodological innovations, policy analysis, and interdisciplinary applications. Notable projects include scaling political party positions and examining the role of AI in public policy. He is actively involved in academic leadership, having served on editorial boards and organized collaborative research initiatives like the CIVICA research hackathon. Beyond SMU, he maintains professional profiles on LinkedIn and GitHub , reflecting his commitment to open-source tools and scholarly collaboration.

Elise Lavouéمشاهده پروفایل

استاد

• Technology Enhanced Learning
• Human-Computer Interaction
• Gamification
• +۱۲ مورد دیگر

Elise Lavoué is a full Professor in Computer Science at iaelyon School of Management, Jean Moulin Lyon 3 University, and a key researcher at the LIRIS laboratory (CNRS). She leads the SICAL research team and holds leadership roles including Editor-in-Chief of the STICEF journal, member of Labex ASLAN’s management committee, and member of the University of Lyon’s Research Ethics Evaluation Committee (CER-UdL). She is also affiliated with the ATIEF association. Her research focuses on enhancing motivation and engagement in digital learning environments through adaptive gamification, learning analytics, and human-computer interaction. She explores how tailored game elements, emotional awareness tools, and immersive technologies like virtual reality can support self-regulated learning, critical thinking, and skill development in complex digital contexts. Her recent publications span top journals such as IEEE Transactions on Learning Technologies, International Journal of Human-Computer Studies, Computers & Education, and CHI PLAY. These works reflect a strong trend in adaptive and personalized learning technologies, emotion-aware systems, and immersive training environments, particularly in educational and professional settings. Honorable Mention Award at ACM CHI PLAY 2019 (top 4%) Best Industrial Paper award at CSEDU 2020 Elise Lavoué actively supervises PhD students and post-doctoral researchers and leads multiple funded projects including LudiMoodle+, RENFORCE, Lex.gaMe, BODEGA, and Emoviz. These projects involve collaborations with institutions across France and focus on gamification, VR training, emotional dashboards, and vocabulary acquisition. She has secured funding from ANR, Labex ASLAN, CNRS, and other national bodies. Her work emphasizes interdisciplinary collaboration between computer science, education, and social sciences. She is involved in several research teams and labs, primarily the SICAL team within the LIRIS laboratory, a major interdisciplinary research unit in computer science, images, and information systems. Her projects often involve industry partners such as SpeakPlus and Woonoz, and she contributes to both scientific advancement and practical educational innovation.

• Computational Linguistics
• Psycholinguistics
• Language Processing
• +۴ مورد دیگر

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.

Mark Battyمشاهده پروفایل

استاد

• Concurrent Systems
• Formal Verification
• Programming Languages
• +۳ مورد دیگر

Mark Batty is a Professor in the School of Computing at the University of Kent, specializing in formal methods for concurrent systems. His work bridges hardware-software interfaces, focusing on memory models for C/C++, OpenCL, and architectures including x86, ARM, POWER, and GPUs. As a member of the Programming Languages and Systems Research Group, he develops mathematical specifications and verification tools for real-world concurrency challenges. His research centers on empirical testing of hardware/compiler behavior, formal modeling of system components, and verification of fine-grained concurrent algorithms. Key contributions address relaxed memory semantics, transactional memory, and compositional reasoning for concurrent data structures. His work combines theoretical rigor with practical tool development to ensure correctness in complex concurrent environments. Analysis of his 2015-2025 publications reveals consistent focus on memory consistency models, formal verification of weak memory concurrency, and compiler optimizations. Dominant themes include C/C++11 standards, GPU concurrency semantics, and mechanized verification techniques. His research demonstrates strong industry relevance through collaborations with hardware vendors and contributions to language standards. Mark Batty has received significant recognition: John C. Reynolds Doctoral Dissertation Award (2015) from ACM SIGPLAN CPHC and BCS Distinguished Dissertation Award (2015) Lloyds Register Foundation and Royal Academy of Engineering Research Fellowship (2016) He actively leads major research initiatives and mentors next-generation researchers: Current Funding: EPSRC Standard Grant 'Verifiably Correct transactional memory' (2018), VeTTS Grant 'Specification and verification of C++ data structure libraries' (2018), EPSRC First Grant 'Compositional, dependency-aware C++ concurrency' (2018) PhD Recruitment: Actively seeking candidates for UKRI-funded studentship in Verified Trustworthy Software Systems Batty drives community engagement through Kent Concurrency Workshop (2016) and South of England Programming Language Seminars, fostering national collaboration in programming languages research. His leadership in organizing Royal Society discussions underscores his influence in trustworthy systems verification.

François Alexandreمشاهده پروفایل

پژوهشگر ارشد

• Historical Linguistics
• Comparative Linguistics
• Pacific Languages
• +۳ مورد دیگر

François Alexandre is a Senior Research Fellow (Research Fellow) at the CNRS, holding tenured positions in departments LaCiTO (2015–2018) and LaTTiCe (2018–present). He concurrently serves as Honorary Associate Professor in the School of Culture, History & Language at the Australian National University (ANU). He leads major research initiatives such as the ComPLETE project on complex predicates and the HéLiCéO project on Pacific languages preservation. Education: PhD in Linguistics (2001, Université Paris IV Sorbonne), Habilitation à Diriger des Recherches (2014, INALCO). His work focuses on Oceanic languages of Vanuatu and Solomon Islands, emphasizing grammatical description, typology, and language documentation. He conducted extensive fieldwork in Vanuatu (since 1997) and Solomon Islands (since 2005), producing 15+ educational books and bilingual dictionaries for endangered languages. Research interests include linguistic typology, language dynamics, areal linguistics, and semantic change. Recent projects involve semantic databases (Evo Sem) and collaborative archival efforts. Awards include the CNRS Bronze Medal (2004) and election to Academia Europeae (2020). Grants: PI of ANR grant (2004–2007), ELDP Legacy Grant (2017–2018) Service: Convenor of 7 research groups, editor for 3 journals, organizer of major conferences (ICAL11, APLL9) Labs/Teams: Leads CNRS research units and collaborates internationally on language revitalization projects.

Lisa Beinbornمشاهده پروفایل

استاد

• Natural Language Processing (NLP)
• Multilingual Language Models
• Cognitive Plausibility in NLP
• +۵ مورد دیگر

Lisa Beinborn is a Professor for Human-Centered Data Science at the University of Göttingen, leading the Human-Centered Data Science group. Her research bridges natural language processing with cognitive science, focusing on multilingual models and interpretability. PhD in Computer Science (2016), Technische Universität Darmstadt MSc in Computational Linguistics (2010), Saarland University & Bolzano, Italy BSc in Computational Linguistics (2008), Saarland University & Barcelona, Spain Her research explores cognitive plausibility in NLP, analyzing how language models process language differently from humans. Key areas include multilingual model interpretability, semantic drift, eye-tracking, and readability prediction. Recent work examines input representation stability in neural models, cross-lingual transfer of complexity, and aligning language models with human cognitive patterns. Her team has presented findings at EMNLP, CoNLL, ACL, and CoLING. VENI Grant for "Interpretability of Transfer in Multilingual Models" Early Career Partnership by Royal Dutch Academy of Science "Most Interesting Paper" Award at BabyLM Challenge "Best Project Award" by Network Institute She has taught courses like Language as Data and Advanced NLP at University of Göttingen, VU Amsterdam, and TU Darmstadt. Her group collaborates with institutions like Gemeente Amsterdam and NT2 on multilingual text simplification and learner correction.