جست‌وجوی استاد و پژوهشگر

• Natural Language Processing
• Computational Linguistics
• Dependency Parsing
• +۳ مورد دیگر

Prof. Dr. Gülşen Eryiğit is a Professor at Istanbul Technical University within the Faculty of Computer and Informatics , Department of Artificial Intelligence and Data Engineering . She founded and directs the ITU Natural Language Processing Group , Turkey's leading team in Turkish-language NLP, and serves as Senior Action Editor for ACL RR , Director of ITU TÖMER (Turkish Language Teaching Center), and Co-Chair of the EU UniDive Cost Action WG3. Education: PhD in Computer Engineering from ITU (2007), MSc and BSc from ITU and Marmara University Research: Focuses on Natural Language Processing for Turkish, including dependency parsing , coreference resolution , multiword expressions , and language education technology Her recent work involves multilingual transfer learning , LLM applications for Turkish text simplification, and gamification for morphology education. She has received prestigious awards like the Siemens Excellence Award and TÜBİTAK's Above Threshold Award . Her research has produced 65+ publications and 29+ projects funded by EU, TÜBİTAK, and industry partners. Scientific Awards: Siemens Excellence Award (2007) Above Threshold Award (TÜBİTAK, 2015) Certificate of Appreciation (EU 7th Framework, 2012) Thank You Plaque (ITU, 2017) The ITU NLP Group under her leadership has developed Turkey's first licensed NLP software exported internationally. She collaborates with European institutions through COST actions and participates in ACL, CoNLL, and LREC conferences. Her lab focuses on language technology for Turkish , including sign language processing and social media normalization.

Brendan O'Connorمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Natural Language Processing
• Computational Social Science
• +۵ مورد دیگر

Brendan O'Connor is an Associate Professor in the Manning College of Information and Computer Sciences (CICS) at the University of Massachusetts Amherst. His research focuses on computational social science and natural language processing (NLP), particularly exploring how social factors influence language technologies and using text analysis to understand societal trends. His work includes studies on racial bias in NLP, political event analysis, and social media linguistics. He holds a PhD in Machine Learning from Carnegie Mellon University (2014) and dual MS/BS in Symbolic Systems from Stanford University (2006). Education: PhD in Machine Learning, Carnegie Mellon University (2014) MS in Symbolic Systems, Stanford University (2006) BS in Symbolic Systems, Stanford University (2006) Research interests span AI ethics, social media analysis, and computational methods for studying language and society. Notably, he investigates racial disparities in NLP systems, linguistic variation in African American English, and event detection in news and social media. His work has been recognized with NSF CAREER and Google Faculty awards, and his research has been cited thousands of times. His lab, the Statistical Social Language Analysis Lab, develops tools for analyzing large-scale text data. He is affiliated with the Center for Data Science, Center for Intelligent Information Retrieval, and Computational Social Science Institute. Recent projects include analyzing global news coverage of critical events and developing frameworks for zero-shot argument explication. Awards and Honors: NSF CAREER Award Google Faculty Research Award Best Paper Award Advising and Grants: O'Connor has advised projects on social media polling representativeness and demographic analysis. His grants include collaborative research on sociopolitical event extraction and bias mitigation in AI systems. He has also contributed to platforms like Rookie for news archive exploration and ezCoref for coreference resolution. Labs/Teams: Leads the Statistical Social Language Analysis Lab and collaborates with the UMass NLP Group and Harvard Institute for Quantitative Social Science. His work bridges NLP with social science methodologies, emphasizing transparency in algorithms and causal inference using text data.

Brendan T. O'Connorمشاهده پروفایل

دانشیار

• Natural Language Processing
• Computational Social Science
• Statistical Text Analysis
• +۲ مورد دیگر

Brendan T. O'Connor is an Associate Professor at the College of Information and Computer Sciences, University of Massachusetts Amherst, where he directs the SLANG Lab and serves as Associate Director of the Computational Social Science Institute. His research bridges statistical machine learning and natural language processing with social science applications, particularly using text data from news and social media to understand societal patterns. His work focuses on developing text analysis methods to answer social science questions in domains like political science and sociolinguistics. Current collaborative projects include combating misinformation, analyzing bias in news coverage, and developing tools for clinical discourse assessment using large language models. O'Connor's publications demonstrate a consistent focus on computational social science, with recent work exploring multilingual analysis, legal discourse patterns, and sociolinguistic variation. His methodological contributions span coreference resolution, event extraction, and argument mining. At UMass, he contributes to multiple research centers including the Computational Social Science Institute, UMass NLP group, and Centers for Data Science and Intelligent Information Retrieval. He teaches graduate seminars in natural language processing and maintains active collaborations across disciplines.

Martin Volkمشاهده پروفایل

استاد

• Computational Linguistics
• Machine Translation
• Natural Language Processing
• +۵ مورد دیگر

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).

• Computational Linguistics
• Natural Language Processing (NLP)
• Dependency Parsing
• +۵ مورد دیگر

Joakim Nivre is a Professor at Uppsala University's Department of Linguistics and Philology. He is a leading researcher in computational linguistics, with a focus on dependency parsing, Universal Dependencies (UD) framework development, and multilingual NLP applications. His recent work explores LLMs in climate change discourse analysis, pharmacovigilance explainability, and historical text processing. Key research areas: Dependency parsing theory, Universal Dependencies standardization, LLM evaluation Collaborations: SweSAT-1.0 benchmark development, ClimateEval project, PARSEME integration His 2025-2023 publications demonstrate expertise in explainable AI for healthcare, synthetic data generation for idioms, and multilingual benchmark design. Notably, he co-developed SweSAT-1.0 to evaluate Swedish LLMs and contributed to typology-informed UD revisions. Despite extensive work in NLP, no scientific awards are mentioned in available texts.

• 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.

Nianwen Xueمشاهده پروفایل

استاد

• Machine Learning
• Natural Language Processing
• Chinese language processing
• +۴ مورد دیگر

Nianwen Xue is a Professor in the Computer Science Department and Language & Linguistics Program at Brandeis University, leading the Chinese Language Processing Group. He holds affiliations with the Michtom School of Computer Science, Benjamin and Mae Volen National Center for Complex Systems, and serves on editorial boards of Computational Linguistics and Lingua Sinica. His research focuses on computational linguistics, machine learning, and cross-linguistic meaning representations. He previously held roles at the University of Colorado and University of Pennsylvania. Education: Ph.D. in Linguistics from University of Delaware, M.A. and B.A. in Linguistics from Nankai University. Research projects include the Chinese Treebank, OntoNotes, and initiatives funded by NSF, DARPA, and IARPA. Teaching includes courses on Natural Language Systems and Computational Corpus Linguistics. He has organized major NLP conferences like CoNLL Shared Tasks and DMR workshops. Research interests emphasize semantic parsing, discourse analysis, and computational social science, with over 100 publications in top venues like ACL, EMNLP, and Computational Linguistics. His work bridges theoretical linguistics and applied NLP, advancing cross-lingual resources and formal meaning representations.

Marieke Meelenمشاهده پروفایل

دانشیار

• Historical Linguistics
• Comparative Syntax
• Information Structure
• +۵ مورد دیگر

Dr Marieke Meelen is an Associate Professor in Historical Linguistics at the University of Cambridge, affiliated with the Faculty of Modern and Medieval Languages and Linguistics. She serves as a Fellow, Tutor, and Director of Studies at Trinity Hall. Research Interests: Historical Linguistics, Comparative Syntax, Information Structure, Grammaticalisation & Pragmaticalisation, NLP for low-resource languages, Celtic & Tibeto-Burman languages Projects: PI for ELDP-funded endangered language documentation in Nepal; collaborator on ERC-funded 'PaganTibet' and AHRC-funded 'Emergence of Egophoricity' Key Contributions: Development of ASR and HTR models for Tibeto-Burman languages; historical treebank of Welsh; computational approaches to Celtic and Tibeto-Burman syntax Publications & Grants focus on syntactic reconstruction, corpus creation, and NLP for endangered languages. She mentors PhD students working on Celtic or Tibeto-Burman languages and consults for computational linguistics projects.

• Computational Linguistics
• Natural Language Processing
• Formal Language Theory
• +۲ مورد دیگر

Giorgio Satta is a Full Professor at the Department of Information Engineering , University of Padua, Italy. He received his Ph.D. in Computer Science from the University of Padua in 1990. His career includes research positions at Fondazione Bruno Kessler (Trento) and the University of Pennsylvania (IRCS). Research Focus : His work centers on computational linguistics and formal language theory , with emphasis on: Parsing algorithms (CCG, TAG, LCFRS) Computational complexity of grammar formalisms Probabilistic language modeling Dependency parsing and synchronization techniques Professional Service : He chaired the European Chapter of the ACL (2009-10), served on editorial boards for Computational Linguistics , Transactions of the ACL , and co-chaired ACL-2001/IWPT-2001. Teaching : Current courses include Automata, Languages, and Computation and Natural Language Processing (2024-25).

Rolando Coto Solanoمشاهده پروفایل

استادیار

• Natural Language Processing for Indigenous and Under-Resourced Languages
• Speech Recognition
• Tonal Phonetics and Phonology
• +۶ مورد دیگر

Rolando Coto Solano is an Assistant Professor of Linguistics at Dartmouth College , with an Adjunct Assistant Professor appointment in Computer Science and an Affiliate Professor role in the Quantitative Social Science Program (QSS) . He focuses on creating computational tools to document and revitalize Indigenous languages like Cook Islands Māori and Bribri. Education : PhD and MA in Linguistics from the University of Arizona; BA in Computer Science from the University of Costa Rica. Research Interests include: Natural Language Processing for Indigenous and Under-Resourced Languages Tonal Phonetics and Phonology, with a focus on tonal reduction Sociophonetics, particularly interisland variation in Cook Islands Māori Publication Trends show expertise in automatic speech recognition (ASR) for Indigenous languages, computational sociophonetics, tonal priming, and metadata standards in academic publishing. He collaborates on tools like Universal Dependencies treebanks and the ELPIS pipeline . Scientific Awards : Fulbright Foreign Student Program (Master’s Degree) National Science Foundation (NSF) Consultant Royal Society of New Zealand Marsden Fund Ship for World Youth Program (Office of the Prime Minister of Japan)

• Computational Linguistics
• Natural Language Processing
• Grammar Engineering
• +۳ مورد دیگر

PD Dr. phil. Evangelia Kordoni is a research assistant at Humboldt University of Berlin's Faculty of Linguistics and Literary Studies, specifically within the Institute for English and American Studies. Her office is located at Dorotheenstraße 28, Room 3.04, and she can be contacted via email for appointments. She is an active researcher in computational linguistics with a focus on grammar engineering and natural language processing. Kordoni's research primarily explores: Computational linguistics frameworks including HPSG grammar implementation Multiword expression processing and machine translation systems Treebank development for languages including English, German and Bulgarian Lexical acquisition methods for large-scale grammars Semantic parsing and disambiguation techniques Her work bridges theoretical linguistics with practical NLP applications. Kordoni's publication record shows consistent focus on deep linguistic processing, with recent emphasis on: Multiword expression analysis in machine translation systems Parallel treebank development for multilingual applications Verb subcategorization and compound noun disambiguation Dynamic annotation methodologies for Wall Street Journal texts Cross-linguistic studies of Germanic syntax

• Natural Language Processing
• Text Normalization
• Named Entity Recognition
• +۵ مورد دیگر

Dilara Torunoğlu Selamet serves as a Lecturer in the Department of Computer Engineering within the Faculty of Computer and Informatics at Istanbul Technical University. Holding a PhD, she specializes in Natural Language Processing for Turkish, with research emphases on social media text normalization, named entity recognition, and sentiment analysis. Her academic credentials feature: PhD in Computer Engineering, Istanbul Technical University (awarded circa 2013) Master of Science in Computer and Information Sciences (Non-thesis), Doğuş University (2009-2013) Bachelor of Science in Computer Engineering, Doğuş University (2004-2009) Dilara's scholarship tackles the complexities of Turkish NLP, a language with rich morphology. She has made notable contributions to text normalization for social media platforms, named entity recognition in authentic datasets, and semantic smoothing techniques for sentiment classification. Her work often bridges theoretical NLP with practical applications, as seen in resource-building projects like the ITU Web Treebank and Turkish sign language corpora. Her publication record (2011-2021) demonstrates methodical growth: initial work on text classification (2011) evolved into named entity recognition (2013) and social media normalization (2014, 2017), then expanded to data augmentation (2020-2021) and sign language processing (2020). This trajectory reflects her commitment to advancing Turkish NLP through both foundational research and innovative resource development. While no specific awards are documented, her research impact is evidenced by an h-index of 4 and over 127 citations in Scopus. Available information does not indicate any students supervised or research grants obtained. She is affiliated with Istanbul Technical University's Department of Computer Engineering, but no laboratory or research team memberships are specified in public profiles.

Thomas Rainsfordمشاهده پروفایل

مدرس

• Historical Romance Linguistics
• Phonology
• Corpus Linguistics
• +۲ مورد دیگر

Thomas Rainsford is a Lecturer at the University of Stuttgart's Institute of Linguistics, Division of Romance Linguistics. His research focuses on historical Romance linguistics, particularly phonological change, morpho-syntax, and corpus development. He holds a PhD from the University of Cambridge and has held positions at ENS de Lyon and as a British Academy Post-Doctoral Fellow at the University of Oxford. Research interests center on: Diachronic evolution of French, Occitan, and Italian Prosodic changes and phonological annotation Lexical and morpho-syntactic aspects of motion events Historical corpus development with multi-layer annotation Publications demonstrate consistent focus on: Historical phonology and orthographic systems Syntactic change in medieval Gallo-Romance languages Corpus linguistics methodologies Computational approaches to historical texts Awards include the British Academy Post-Doctoral Fellowship. Current research involves leading a DFG-funded project examining motion events in French and Italian through lexical and syntactic change analysis. Developed the Old Gallo-Romance Corpus (OGR) with specialized phonological and metrical annotation layers.

Guillaume Thomasمشاهده پروفایل

دانشیار

• Linguistics
• Corpus Linguistics
• Semantics
• +۴ مورد دیگر

Guillaume Thomas is an Associate Professor in the Department of Linguistics at the University of Toronto. His research focuses on the study of meaning (semantics and pragmatics) in relation to morphosyntactic structures, particularly in Mbyá Guaraní, a Tupí-Guaraní language spoken in Argentina, Brazil, and Paraguay. He combines corpus linguistics and digital methods with fieldwork, developing resources like dependency treebanks and morphological analyzers. His work includes language documentation projects, such as the National Inventory of the Cultural Heritage of the Guaranis in Brazil, which involved community-based documentation of oral traditions. His research interests also encompass usage-based approaches, probabilistic models in language analysis, and the interface between semantics and syntax. Education: PhD in Linguistics from the Massachusetts Institute of Technology (MIT). Research Interests: Cross-linguistic semantics and pragmatics Morphosyntax and its interface with meaning Language documentation and digital linguistics Corpus-based methods and computational tools for endangered languages Funding: Supported by grants from the Social Sciences and Humanities Research Council of Canada and the Connaught Fund. His work integrates theoretical linguistics with practical applications in language preservation and computational modeling. Labs/Teams: He collaborates with the Indigenous Museum of Rio de Janeiro on documentation projects and contributes to the Universal Dependencies project for syntactic annotation.

Miriam Buttمشاهده پروفایل

استاد

• Morphology
• Lexical semantics
• Digital humanities
• +۳ مورد دیگر

Miriam Butt is a Professor (W3) for General and Computational Linguistics at the Department of Linguistics, University of Konstanz since 2019. Previously, she held a Professor (C3) position at the same department from 2003 to 2019. Earlier roles include a Lecturer at the Centre for Computational Linguistics, UMIST (2002-2003), and Research Scientist positions at the University of Konstanz, Universität Stuttgart, and Universität Tübingen. Education: PhD and MA in Linguistics from Stanford University (1988-1993), BA in Language Studies and Computer Science from Wellesley College (1984-1987). Her research focuses span Morphology, Lexical Semantics, Digital Humanities, Historical Linguistics, Computational Linguistics, and Syntax. She has contributed to projects such as SFB471 (Variation and Change in the Lexicon), ParGram (grammar development for German), and Verbmobil (tense analysis in German-English translation). She has served on advisory boards and consulted for projects including NSF's Hindi/Urdu treebank initiative and CRULP's Urdu machine translation system.