جست‌وجوی استاد و پژوهشگر

• Computational Linguistics
• Cognitive Science
• Semantics
• +۴ مورد دیگر

Suzanne Stevenson is a Professor in the Department of Computer Science at the University of Toronto. Her primary research focuses on computational linguistics and cognitive science, integrating computational theories with insights from linguistics and psycholinguistics. She investigates how people learn and process language, particularly in the domains of semantics, pragmatics, and word-level meaning. Her work bridges machine learning and cognitive modeling, emphasizing probabilistic approaches to language understanding. She is affiliated with the Cognitive Science Research Community (CoRC) at the University of Toronto. Research Interests: Computational models of language acquisition and processing Semantic and syntactic learning from text data Cognitive science of word meaning and pragmatics Probabilistic and machine learning methods in natural language processing Publications: Dr. Stevenson has contributed over 80 papers to conferences and journals, focusing on topics like cross-situational word learning, semantic typology, and cognitive modeling of language production. Her recent work explores probabilistic models of perspective-taking and reference generation in language.

Sina Zarrießمشاهده پروفایل

استاد

• Computational Linguistics
• Natural Language Processing
• Dialogue Systems
• +۵ مورد دیگر

Sina Zarrieß is a Professor of Computational Linguistics at the University of Bielefeld, affiliated with the Faculty for Linguistics and Literature Studies. His research focuses on computational models of language use, with applications in natural language generation, dialogue systems, and language-vision integration. He leads the Computational Linguistics Bielefeld group and collaborates on interdisciplinary projects in ecology, hate speech analysis, and multimodal interaction. Research interests include language model architecture optimization, pragmatic reasoning in generation, and ethical NLP. He actively contributes to workshops such as ACL, EMNLP, and NLP4Ecology, publishing on topics like character-based LMs, gaze-driven hate speech detection, and visualization-oriented dialog systems. His work bridges theoretical linguistics with applied machine learning, emphasizing interpretability and real-world impact. Notable projects include developing BabyLM character-based models, studying gender-inclusive language benchmarks (SlayQA), and creating tools like VIST5 for adaptive visualization dialog. He explores how LMs encode linguistic principles like Maximize Presupposition! and investigates zero-shot learning for novel object categories. Current research trends show a focus on model efficiency (e.g., sentence selection for classification), multimodal grounding (e.g., scene context in visual tasks), and human-AI interaction dynamics (e.g., explanation effects on user perception). Despite prolific publishing, no specific scientific awards are mentioned in the provided materials. Advising and grants are not explicitly detailed, though his extensive co-authorship network indicates active mentoring. The Computational Linguistics Bielefeld group maintains open research directions in visual question answering, poetry generation diversity, and historical hate speech evolution studies.

Felix Golcherمشاهده پروفایل

پژوهشگر

• Stylometry
• Natural Language Processing
• Corpus Linguistics
• +۳ مورد دیگر

Felix Golcher is a researcher at Humboldt-Universität zu Berlin, affiliated with the Institut für deutsche Sprache und Linguistik. He holds a PhD in Linguistics and a background in Physics. His work focuses on statistical methods in linguistics, including stylometry, unsupervised text segmentation, and computational approaches to language analysis. He contributes to the SFB 1412 'Register' project, managing data and providing statistical support for subproject INF. His research spans syntactic processing, bilingualism, and corpus linguistics. Education: PhD in Linguistics (university unspecified), with postgraduate studies at the University of Munich (2005 thesis). Current role involves statistical advising and technical infrastructure support for linguistic projects. Contact: felix.golcher@hu-berlin.de, Room 433. Research highlights include studies on clitic dislocation in Greek, primate habitat analysis using statistical methods, and syntactic processing of split particle verbs. His work bridges computational methods with theoretical linguistics, emphasizing quantitative approaches to language structure and usage.

Giuseppe Varaschinمشاهده پروفایل

مدرس

• Syntactic Theory
• Syntax-Semantics Interface
• Register Variation
• +۵ مورد دیگر

Giuseppe Varaschin is a Lecturer and postdoctoral researcher at Humboldt University of Berlin's Department of German Language and Linguistics, part of the Faculty of Language Sciences. He is affiliated with Project A04 of the SFB 1412 Register, focusing on formal syntax and register variation in HPSG. Previously, he held a Humboldt Research Fellowship at the same institution. His research interests include syntactic theory, the syntax-semantics interface, Romance and Germanic syntax, sociolinguistics, and computational grammar development. His work emphasizes formalizing grammatical constraints and modeling anaphoric relations and intra-individual variation within HPSG frameworks. He has explored register variation in German and Brazilian Portuguese, integrating empirical studies with theoretical linguistics. Key research projects include the parallel architecture of grammar and register-driven syntactic variation. His contributions span formal syntax, computational linguistics, and sociolinguistic perception, with a focus on experimental validation of linguistic hypotheses. Awards include the Humboldt Research Fellowship. He has presented at international conferences like HPSG 2024 and contributed to collaborative projects such as the Integrated Graduate School (MGK). His work bridges theoretical linguistics with computational and empirical methods.

Linnaea Stockallمشاهده پروفایل

استاد

• Morphology
• Lexical Semantics
• Event Semantics
• +۵ مورد دیگر

Professor Linnaea Stockall is a Professor of Linguistics and Cognitive Neuroscience at Queen Mary University of London, affiliated with the School of Languages, Linguistics and Film and the Department of Linguistics. She directs the Morphemes and Meaning Lab, focusing on morphological and semantic processing mechanisms. Her research integrates experimental, neurolinguistic, and cross-linguistic approaches to understand word formation, lexical access, and syntactic-semantic integration. Stockall holds a PhD from MIT and specializes in psycholinguistics, neurolinguistics, and morphology. Her work explores how morphological constituents are stored, decomposed, and recombined during language processing, with particular attention to irregularity, event semantics, and the interaction of roots with functional morphemes. She has conducted studies using MEG neuroimaging and masked priming paradigms in languages like Tagalog, Mandarin, and Arabic. Her research emphasizes understudied languages and developing resources for cross-linguistic research. She supervises PhD/postdoctoral researchers in areas connected to her expertise, requiring clear alignment with her focus on morpho-syntactic and semantic processing. She is also involved in public engagement initiatives, such as the Teach Real English! project. Key contributions include investigations into mass/count distinctions, morphological decomposition in neuroimaging studies, and sociolinguistic effects of taboo language. She collaborates widely, with recent projects addressing lexical semantics, aspectual interpretations, and the impact of grammatical gender on societal perceptions.

Dan Duncanمشاهده پروفایل

مدرس ارشد

• Language Variation
• Sociolinguistics
• Sociophonetics
• +۵ مورد دیگر

Dan Duncan is a Senior Lecturer in Sociolinguistics at the School of English Literature, Language, and Linguistics at Newcastle University. His research focuses on language variation and change, particularly examining relationships between language and place in metropolitan contexts. He holds a graduate degree from New York University and has conducted sociophonetic analysis of St. Louis metropolitan area speakers. Education: Graduate studies completed at New York University. Research Interests: Language variation and change, sociolinguistics, sociophonetics, sound change, morphology, and the interplay of language with urban geography and toponymy. Current studies explore how language reflects and constructs perceptions of place, with emphasis on metropolitan areas and their sociolinguistic dynamics. Publications: Recent work includes analyses of fictional dialogue variation, AI sociolinguistic competence, and computational methods in language analysis. Key themes include verb morphology variation (e.g., preterite-to-participle leveling), toponymy, syntax variation, and urban sociolinguistics. Contact: daniel.duncan@ncl.ac.uk | Website: https://sites.google.com/view/dan-duncan-sociolinguist

Laura Ruppمشاهده پروفایل

دانشیار

• Language Variation and Change
• English as a Lingua Franca
• Global English
• +۳ مورد دیگر

Dr. Laura Rupp is an Associate Professor at the Faculty of Social Sciences and Humanities , Vrije Universiteit Amsterdam, and Director of the Centre for Global English . She holds a PhD in Linguistics from the University of Essex (1999). Her research focuses on language variation, English pronunciation in global contexts, and the sociolinguistic aspects of English as a lingua franca. She has received prestigious awards including the British Academy Visiting Fellowship (2023-2024) and the Hans-Sigrist-Preis (2020). Key grants include a British Academy Fellowship (2023-2024) and a Swiss National Science Foundation grant (2022-2023) supporting research at Universität Bern. She has been a Visiting Professor at the University of Toronto and Australian Catholic University. Her teaching includes courses on Global English, Postcolonial Language, and Pronunciation, with a notable MOOC English Pronunciation in a Global World on FutureLearn. Research interests span grammatical properties of English varieties, discourse pragmatics, and pronunciation's role in mutual understanding. She advocates for linguistic diversity, emphasizing intelligibility over prescriptive norms. The Centre for Global English she leads fosters international collaboration on sociolinguistic challenges of global English usage.

Andrew Cooperمشاهده پروفایل

مدرس ارشد

• Mathematics Education
• Differential Geometry
• Topology
• +۳ مورد دیگر

Andrew Cooper is a Senior Lecturer in the Department of Mathematics at the University of Pennsylvania's School of Arts and Sciences. He is affiliated with the Standing Faculty and Associated Faculty within the university's academic structure. His research spans mathematics education, differential geometry, topology, and geometric analysis. He has contributed to pedagogical innovations in teaching proofs and critical thinking in mathematics, alongside studies on geometric flows, Lagrangian submanifolds, and configuration spaces. Cooper's educational background and specific degrees are not explicitly detailed in the text. His research interests emphasize bridging theoretical mathematics with practical educational methodologies. Notable work includes exploring mastery-based grading systems, analogical reasoning in mathematical induction, and applications of geometric analysis to Lagrangian singularities. He has also engaged in public outreach through publications like the Oberwolfach Snapshots series, focusing on making mathematics accessible to broader audiences. His publications reflect two primary themes: (1) advancing mathematical pedagogy through innovative assessment and instructional techniques; and (2) exploring geometric structures using tools from differential geometry and topology. Recent work (2021-2019) highlights educational research, while earlier contributions (2016-2005) delve into specialized geometric theories. No scientific awards or grants are explicitly mentioned in the provided texts. As a Senior Lecturer, Cooper's role likely combines teaching excellence with scholarly research. No lab affiliations or student advising records are documented in the source material.

Tim Hunterمشاهده پروفایل

استاد

• minimalist grammars
• mild context-sensitivity
• syntax-semantics interface
• +۴ مورد دیگر

Professor Hunter researches formal syntax, computational linguistics, and cognitive modeling of language. Key areas include minimalist grammars, mild context-sensitivity, probabilistic models of language processing and acquisition, and the syntax of ellipsis. Recent work explores computational approaches to syntactic variation, noise-tolerant learning models, and integrating grammatical theories into cognitive architectures. Teaches computational linguistics and syntax at undergraduate and graduate levels. Education includes PhD from University of Maryland (2010) focusing on syntactic effects of conjunctivist semantics.

• Linguistics
• Formal Semantics
• Syntax
• +۳ مورد دیگر

Cynthia Potvin is an Assistant Professor in the Department of Translation and Languages at the University of Moncton's Faculty of Arts and Social Sciences. Her academic expertise spans formal semantics, syntactic theory, language acquisition processes, sociolinguistic variation, and Spanish language pedagogy. Her research examines structural and cognitive aspects of language through theoretical frameworks in linguistics, with applied investigations into second-language teaching methodologies. She maintains an active research program analyzing linguistic interfaces between syntax, semantics, and pedagogical applications.

Takako Aikawaمشاهده پروفایل

مدرس ارشد

• Technology in language education
• Natural Language Processing (NLP)
• AI in language learning
• +۴ مورد دیگر

Takako Aikawa is a Senior Lecturer in Japanese at the Massachusetts Institute of Technology (MIT), where she leads the Japanese language curriculum and teaches across all proficiency levels. Her research focuses on integrating technology into language education, including virtual reality (VR) for immersive learning and AI-driven error correction in written Japanese. Prior to joining MIT in 2013, she held academic positions in Japan and the U.S., and contributed to Microsoft Research's work in machine translation and NLP. Education includes a PhD and MA from Ohio State University (U.S.) and a BA from Tsuda University (Japan). Her pedagogical interests emphasize corpus-based learning, AI applications in language education, and leveraging VR for kinesthetic learning experiences. She frequently presents at conferences on Japanese language pedagogy and has authored chapters in edited volumes such as ICT×日本語教育 and Digital Resources for Learning Japanese . Her technical work spans statistical machine translation systems, terminology consistency validation, and collaborative translation frameworks. She has pioneered projects like Pecha, an LLM-based language learning tool, and VR child avatars to enhance adult language acquisition. Current initiatives explore AI's role in identifying and correcting common learner errors in writing.

• Psycholinguistics
• Language Acquisition
• Language Processing
• +۵ مورد دیگر

Professor Evan Kidd is a prominent academic in psycholinguistics and developmental psychology, currently serving as a Professor at the Australian National University (ANU) within the School of Literature, Languages & Linguistics. He previously held senior roles at the Max Planck Institute for Evolutionary Anthropology and the Max Planck Institute for Psycholinguistics. His research focuses on language acquisition, syntax processing, and the interplay between language and cognitive development. Kidd holds a PhD in Psycholinguistics from La Trobe University (2004) and a BBSc(Hons) in Psychology from the same institution (2000). Key research interests include first language acquisition, bilingualism, adult language processing, and the role of individual differences in language development. His work emphasizes crosslinguistic perspectives, particularly in typologically diverse languages like Murrinhpatha. Kidd has explored how language interfaces with social cognition, symbolic play, and executive functions. He leads a research group investigating language processing mechanisms, neurodevelopmental aspects of grammar learning, and the impact of endangered language documentation on linguistic research. Notable projects include the Evolution of Cultural Diversity - Initiative (ECDI) and collaborations with MPI on language development and typology. His publications span psycholinguistics, cognitive science, and developmental psychology, with a focus on experimental methods and theoretical contributions to language acquisition models.

Alexander Bauerمشاهده پروفایل

پژوهشگر

• Deep Learning
• Computer Vision
• Natural Language Processing
• +۲ مورد دیگر

Alexander Bauer is a Postdoctoral Researcher in the Machine Learning Group at Technical University of Berlin, and a member of BASLEARN—a joint lab between BASF and TU Berlin focusing on machine learning applications. His academic background includes a PhD in Computer Science (2017) and a Diploma degree in Computer Science (2012), both from TU Berlin, alongside a B.Sc. in Mathematics (2011) from the same institution. His research interests span Deep Learning , Computer Vision , and Natural Language Processing . In Computer Vision, he specializes in visual anomaly detection , image classification , and semantic segmentation , with industry applications in automotive quality assurance. In NLP, he focuses on transformer architectures and foundation models for tasks like question answering and textual entailment. His earlier work centered on structured prediction , including optimization techniques for MAP inference in graphical models. His publications emphasize algorithmic efficiency and practical applications, with recent work exploring self-supervised learning and model interpretability. Bauer has contributed to both theoretical advances (e.g., exact inference algorithms) and applied solutions (e.g., anomaly detection in manufacturing). He collaborates with industry partners like BASF through BASLEARN, bridging academic research and industrial challenges. His technical expertise spans neural network design, optimization frameworks, and interdisciplinary problem-solving in vision and language domains.

Sandra Küblerمشاهده پروفایل

استاد

• Machine Learning of Natural Language
• Parsing Morphologically Rich Languages
• Dependency Parsing
• +۵ مورد دیگر

Sandra Kübler is a Professor in the Department of Linguistics at Indiana University, part of the College of Arts and Sciences. Her research focuses on computational linguistics, machine learning applications in natural language processing, and parsing of morphologically rich languages. She has led projects such as the NSF-funded SATC initiative on unsubstantiated information analysis and contributed to initiatives like the TLT workshops and SPMRL conferences. Her work spans dependency parsing, abusive language detection, and cross-lingual NLP challenges. She advises numerous PhD and Master’s students, many of whom have gone on to academic and industry roles. Her contributions include developing tools like the IUCL system for stance detection and collaborating on corpora for languages like Old Occitan and Xibe. Education details are not explicitly stated in the provided texts, but her extensive academic career and publications indicate advanced training in computational linguistics. Her research interests emphasize leveraging machine learning for linguistic analysis, particularly in under-resourced languages and social media text processing. Projects include the development of the TüBa-D/Z treebank and contributions to parser evaluation frameworks. She has organized major workshops such as the SIGMORPHON and TLT conferences, reflecting her leadership in the field. In advising, she has guided over 20 students to completion, many securing academic positions (e.g., University of British Columbia, Rose-Hulman Institute) or industry roles (e.g., JP Morgan Chase, Microsoft). Her lab activities involve collaborations with institutions like Bosch and IntraFind. Current research includes multilingual coreference resolution and fusion of hard/soft data for information reliability assessment.

Christian Hänigمشاهده پروفایل

استاد

• Machine Learning
• Deep Learning
• Natural Language Processing
• +۷ مورد دیگر

Prof. Dr. Christian Hänig is a Professor at the Department of Computer Science and Languages and a Temporary Lecturer at the Department of Electrical Engineering, Mechanical Engineering and Industrial Engineering at Anhalt University of Applied Sciences. He advises the Data Science (Full-Time Program) Master of Science degree and teaches courses such as Artificial Intelligence, Data Mining, and Deep Learning. His research focuses on Machine Learning, Deep Learning, Natural Language Processing (NLP), Computer Vision, Medical Imaging, Multimodal Document Processing, and Data Science. Recent work emphasizes applications in financial domains (e.g., German financial language models and corpus development) and agricultural sector benchmarking. Earlier research includes VR education analytics, unsupervised NLP techniques, and knowledge extraction from unstructured data. Key publications (2024) include developing benchmarks for Ukrainian language models, evaluating agricultural LLMs, and creating financial domain corpora. His contributions span over 20 years, addressing challenges in domain-specific NLP, clinical text mining, and industrial quality analysis. Prof. Hänig’s academic service includes roles as a degree program advisor and committee member. Office hours are Thursdays 4:30–6:00 PM (by appointment) at the Ratke Building, Room 23-114, Köthen campus.