جستجوی استاد راهنمای دانشگاهی

• Computational Linguistics
• Natural Language Processing
• Phonology
• +۶ مورد دیگر

Professor Janet B. Pierrehumbert is a leading academic in computational linguistics and natural language processing, holding the position of Professor of Language Modelling at the Oxford e-Research Centre, University of Oxford. She is also a Senior Research Fellow at Trinity College and affiliated with the Faculty of Linguistics, Philology and Phonetics. Her work bridges interdisciplinary research in phonology, sociolinguistics, and computational models of language dynamics. Education: PhD in Linguistics from MIT (1980), A.B. in Linguistics from Harvard University (1975). Research Interests: Focuses on computational linguistics, dialect variation, language dynamics, and the societal impacts of NLP. Her group develops algorithms for analyzing social media discourse, forecasting trends, and modeling language evolution. Recent work includes studies on dialect fairness in LLMs and semantic shifts in political discourse. Key Projects: EPSRC-funded research on online forum dynamics, the Wordovators project on lexical innovation, and collaborations with institutions like the Oxford Man Institute. Her work emphasizes robust NLP systems and theoretical linguistics. Awards: ISCA Medal (2020), National Academy of Sciences membership (2019), Fellowships from the American Academy of Arts and Sciences and Cognitive Science Society. Grants & Advising: Over £6M in research funding, including EPSRC and Templeton grants. Supervised over 30 PhD students and postdocs, many now leading academics and industry researchers in NLP and linguistics. Labs/Teams: Leads the Pierrehumbert Language Modelling Group, collaborating with the Oxford e-Research Centre and international partners like Stanford and the University of Canterbury.

• Software Engineering
• Graph Transformation Systems
• Model-Based Development
• +۵ مورد دیگر

Reiko Heckel is a Professor of Software Engineering at the University of Leicester, serving as Director of Postgraduate Teaching for Computing degrees and Data Analytics Lead at the Leicester Innovation Hub. She previously held academic roles at the Technical Universities of Dresden and Berlin before joining Leicester in 2004. Her research focuses on graph transformation systems, model-based development, stochastic modeling, and formal methods in software engineering. She earned her PhD (Dr.-Ing.) in Computer Science from TU Berlin in 1998. Her research interests span software engineering pedagogy, formal specification techniques, and applications of graph grammars in system modeling. Recent work explores stochastic graph transformations for social networks, transparency engineering in AI systems, and blockchain-based smart contract frameworks. Her contributions bridge theoretical foundations with practical applications in cybersecurity, data integration, and human-centric systems design. Key contributions include advancements in automated test case generation via graph transformations, visual contracts for software reverse engineering, and formal methods for complex system analysis. Her work frequently intersects with industry through collaborations via the Leicester Innovation Hub, emphasizing data analytics and technology transfer. Education: MSc Computer Science, Technical University of Dresden PhD (Dr.-Ing.), Computer Science, TU Berlin (1998) Leadership Roles: Head of Department (2014-2018) Director of Postgraduate Teaching (Ongoing) Research Themes: Model-Based Development Stochastic Systems Analysis Graph Neural Networks Trustworthy AI Her publications reflect a focus on formal methods, with recent trends in applying graph transformation techniques to social network modeling, blockchain smart contracts, and educational pedagogy.

• Bilingualism
• Cognitive Aging
• Executive Functioning
• +۷ مورد دیگر

Ellen Bialystok is a prominent academic in the fields of psycholinguistics and cognitive neuroscience, focusing on bilingualism and its effects on aging and executive functioning. She has contributed extensively to interdisciplinary research through publications, editorships, and theoretical analyses. Her research explores how bilingualism modifies cognitive control, working memory, and neuroplasticity, particularly in aging populations. Key themes include cognitive reserve, language representation, and neural mechanisms underlying bilingual processing. The articles highlight a consistent focus on bilingualism's impact on cognitive aging, executive function, and lexical access, with methodologies spanning behavioral studies, ERP analysis, and theoretical frameworks. Keywords include psycholinguistics, neuroscience, and cognitive psychology.

Devyani Sharmaمشاهده پروفایل

استاد

• Sociolinguistics
• Language Variation
• Diaspora Studies
• +۴ مورد دیگر

Professor Devyani Sharma is a Professor of Linguistics at Queen Mary University of London, affiliated with the Department of Linguistics within the School of Languages, Linguistics and Film. She holds a PhD from Stanford University. Her research focuses on sociolinguistics, style variation, migration, bilingualism, new varieties of English, syntax, typology, and accent bias. She has conducted extensive studies on diasporic communities, particularly Punjabi Londoners, examining dialect development and social change through projects like 'Generations of London English' and 'Accent Bias in Britain.' Her work integrates quantitative and qualitative methods, including sociolinguistic interviews, acoustic analysis, and discourse analysis. Notable contributions include studies on the role of social networks in language variation, the concept of 'lectal focusing,' and the impact of accent biases in professional contexts. She has authored/co-authored books such as From Deficit to Dialect: The Evolution of English in India and Singapore (2023) and edited volumes including English in the Indian Diaspora (2014). Professor Sharma collaborates on public engagement initiatives like Teach Real English! and Multilingual Capital , aiming to improve linguistic education and address accent bias in society. Her research has been funded by grants from the ESRC and other UK organizations, totaling over £412,000 for major projects. She serves as Associate Editor for the Journal of Sociolinguistics and contributes to international conferences and workshops.

Danfeng Wuمشاهده پروفایل

پژوهشگر ارشد

• syntax-semantics interface
• syntax-prosody mapping
• ellipsis
• +۸ مورد دیگر

Dr. Danfeng Wu is a Research Fellow at Magdalen College, University of Oxford, conducting interdisciplinary research in syntax-semantics and syntax-prosody mappings. Her work focuses on ellipsis, focus in coordination, and the empirical interplay between syntactic structure and prosody, employing experimental phonetic methods. She investigates languages like English and Mandarin Chinese to explore the cognitive and computational aspects of linguistic structure. Her research themes include phonetics, prosody, semantics, and syntax, with a particular emphasis on how syntactic configurations interact with prosodic phrasing and stress patterns. She has contributed to studies on corrective constructions, clitic climbing in Wolof, and vowel lengthening in Zulu, demonstrating a broad methodological approach combining theoretical linguistics with experimental and computational methods. Dr. Wu is affiliated with the Phonetics Lab and Language & Brain Lab within the Faculty of Linguistics, Philology & Phonetics. She has organized interdisciplinary events such as the Oxford workshop on AI language models and developed linguistics courses for computer scientists and cognitive scientists at MIT. Her work bridges formal linguistics with cognitive science and computational linguistics, emphasizing realistic models of language acquisition and evolution.

• Artificial Intelligence
• Multimodal Interaction
• Natural Language Processing
• +۴ مورد دیگر

Arash Eshghi is an Assistant Professor in the School of Mathematical & Computer Sciences at Heriot-Watt University, specializing in the Department of Computer Science. His research focuses on multimodal interaction, embodied AI, and dialogue systems, with applications in human-AI collaboration, vision-language models, and incremental processing. He leads projects like the EMMA and AlanaVLM frameworks, which explore embodied agents in 3D environments and egocentric video understanding. His work emphasizes ethical considerations in conversational AI, including dementia-friendly voice assistants and faithfulness in large language models. He collaborates internationally, with contributions to benchmarks like the BURCHAK corpus and the Block World repair framework. Eshghi’s research bridges computational linguistics, cognitive science, and robotics, addressing challenges in ambiguity resolution, spatial reasoning, and incremental dialogue processing. Key collaborations involve institutions like the University of Edinburgh and MIT, focusing on multimodal learning, dynamic syntax, and interactional semantics. His lab develops tools for grounded language learning and real-time interaction, with a focus on systems that adapt to human feedback and contextual dynamics.

• Formal Verification
• Software Testing
• Programming Languages
• +۶ مورد دیگر

Alastair F. Donaldson is a Professor and Director of Research in the Department of Computing at Imperial College London, where he leads the FastPL research group. His academic career spans over a decade at Imperial, progressing from Lecturer (2011-2014) to Senior Lecturer (2014-2017), Reader (2017-2020), and Professor (2020-present). He has also held significant industry positions, including Founder and Director of GraphicsFuzz Ltd. (acquired by Google in 2018), Senior Software Engineer at Google (2018-2021), and Visiting Researcher at both Google and Microsoft Research Redmond. Donaldson earned his PhD from the University of Glasgow under Alice Miller, following a BSc (hons, First Class) in Computing Science and Mathematics. His postdoctoral work included an EPSRC Postdoctoral Research Fellowship at the University of Oxford and a Research Fellowship at Wolfson College Oxford. His research focuses on formal analysis, software testing and programming languages techniques for improving software reliability, with special emphasis on high-performance systems. Donaldson's work bridges theoretical foundations with practical applications, particularly in compiler testing, GPU programming verification, and metamorphic testing. His research has significantly influenced both academia and industry, as evidenced by the acquisition of his startup GraphicsFuzz by Google. Analysis of his recent publications reveals a strong focus on fuzz testing techniques applied across diverse domains including compilers, GPUs, cryptographic protocols, and large language models. His work consistently combines formal methods with practical testing approaches, addressing challenges in compiler correctness, memory models, and API verification across multiple platforms. 2017 BCS Roger Needham Award EPSRC Early Career Fellowship Best Paper Award, EuroSys 2024 Best Paper Award, MET 2021 Best Paper Award, IWOCL 2019 Best Paper Award, IISWC 2019 Best Paper Award, ICST 2016 ACM SIGSOFT Distinguished Paper Award, ISSTA 2023 ACM SIGSOFT Distinguished Paper Award, FSE 2017 ACM SIGPLAN Most Influential OOPSLA Paper Award, 2022 (for GPUVerify) As Director of Research in the Department of Computing, Donaldson oversees research strategy and development. His FastPL research group investigates novel techniques for programming, testing and reasoning about high performance systems. He has served on numerous program committees and held leadership roles including PLDI Steering Committee Chair (2022-2025) and PACM-PL Advisory Board member. His industry engagement includes testifying as an Expert Witness in the IBM UK Ltd v LzLabs GmbH & Ors case. The FastPL research group, which Donaldson leads, focuses on formal analysis, software testing and programming languages. The group has made significant contributions to compiler testing, GPU verification, and metamorphic testing techniques, with practical impact demonstrated by the acquisition of GraphicsFuzz. Current research directions include fuzzing for zero-knowledge proof circuits, randomized testing of decompilers, and systematic testing of large language models for code generation.

Li Nguyenمشاهده پروفایل

استادیار

• Language variation and change
• Contact linguistics
• Computational sociolinguistics
• +۴ مورد دیگر

Li Nguyen is an Assistant Professor of Linguistics and Multilingual Studies at Nanyang Technological University (NTU), Singapore . Their work bridges linguistics with computational approaches, focusing on language variation, contact phenomena, and multilingual NLP. Education: PhD in Linguistics (University of Cambridge), Master’s in General and Applied Linguistics (Australian National University) Research interests include: Language variation and change in multilingual/diasporic communities Computational sociolinguistics and NLP for low-resource varieties Syntax-pragmatic interface in bicultural contexts Code-switching and heritage language documentation Recent publications highlight collaborations on Vietnamese-English and other code-switched language pairs, with a focus on NLP applications and corpus-based analysis. Their work has gained recognition through grants like the NTU Start-up Grant and Cambridge Language Sciences funding . Scientific awards: Cambridge International Scholarship, Philological Society Fieldwork Grant Li Nguyen actively collaborates on projects involving sociolinguistically informed NLP and community-driven language documentation. They have contributed to the development of the CanVEC corpus for Vietnamese-English speech research.

• Natural Language Processing
• Machine Learning
• Data Mining

Danushka Bollegala is a Professor in the Department of Computer Science at the University of Liverpool, where he leads both the Machine Learning and Natural Language Processing research groups. He previously held a lectureship at the University of Tokyo (2010-2013) and currently serves as an Amazon Scholar for Amazon Search. His research bridges fundamental AI with applications in healthcare, law, and social sciences. Research Focus: Professor Bollegala specializes in developing core NLP methodologies including word embedding techniques, semantic similarity measurement, and domain adaptation. His machine learning research explores privacy-preserving AI, unsupervised parsing, and bias mitigation. Recent applications include clinical decision support for polypharmacy management and legal document analysis. His publications demonstrate strong emphasis on: 1) Advancing evaluation methodologies for generative NLP systems, 2) Developing privacy-aware embedding techniques, and 3) Creating cross-domain NLP applications for healthcare and social good. Research consistently addresses real-world implementation challenges. Research Leadership: Principal Investigator for £6M+ grants including DynAIRx (NIHR: £4.2M) for AI in multi-morbidity management KTP grant with Fletchers Solicitors for legal AI systems EU-funded WEB-RADR project for pharmacovigilance Leads 30+ member research group spanning NLP, machine learning, and healthcare AI. Teaches graduate course COMP 527: Data Mining and Visualisation.

• Computational Linguistics
• Natural Language Processing
• Artificial Intelligence
• +۵ مورد دیگر

Massimo Poesio is a Professor of Computational Linguistics at Queen Mary University of London and a full Professor of Natural Language Understanding at Utrecht University. He leads the ARCIDUCA project (EPSRC-funded) on conversational agents and the Dealing with Meaning Variation project (NWO-funded) exploring NLP applications. His research focuses on anaphora resolution, games-with-a-purpose, and applying NLP to combat deception and misinformation. He is a Fellow of the Alan Turing Institute and supervises students in PhD programs like IGGI and Health Data in Practice. Education: Previous affiliations include University of Essex and University of Trento (founded CLIC Lab). Research Projects: DALI (ERC), SENSEI (EU), AnaWiki (EPSRC), and LiveMemories (Provincia di Trento). His work combines formal semantics with empirical methods, including brain data and corpus analysis. He has developed tools like Phrase Detectives and BART for anaphora resolution, and co-founded the Lingotowns platform for language learning.

• Architecture
• Urban and regional planning
• Design
• +۵ مورد دیگر

Professor Alan Penn is a leading academic at University College London's The Bartlett School of Architecture , where he holds the title of Professor in Architectural and Urban Computing. He previously served as Dean of the Bartlett Faculty of the Built Environment from 2009 to 2019 and has been instrumental in establishing Space Syntax Ltd , a UCL knowledge transfer spin-out company. His affiliations include membership in the Space Syntax Laboratory, board membership of UCL Consultants Ltd, and trustee status at Shakespeare North Trust. Education: BSc (1978), Dip Arch (1980), MSc (1983) - all from University College London Alan Penn’s research investigates how spatial design influences social and economic behaviors through innovative space syntax methodologies . Key areas include: Agent-based simulations of human behavior Spatio-temporal representations of built environments Urban spatial network analysis Urban sustainability across multiple dimensions Cognitive markers in architectural design Historical urban growth modeling His recent publications demonstrate a strong focus on computational urbanism, evolutionary city patterns, and behavioral architecture. Research trends show interdisciplinary approaches combining architectural theory with: Machine learning applications Network science analysis Behavioral psychology insights Historical GIS techniques Complex systems modeling Public health considerations Scientific recognition includes: HEFCE Business Fellowship (2001-2005) KTP SE Region Award (2010) Multiple UCL Enterprise awards ‘Spirit of Enterprise’ Award (2008) As Principal Investigator he leads the £5m EPSRC-funded Urban Dynamics Lab , demonstrating sustained research excellence. His work extends to public engagement through: Shakespeare North Trust educational theatre development Media appearances (New Scientist, Slashdot) Public policy contributions

• Design Computing
• Spatial Modeling
• Machine Learning
• +۷ مورد دیگر

Sean Hanna is a Professor of Design Computing at The Bartlett School of Architecture , University College London , and a member of the UCL Space Syntax Laboratory . His interdisciplinary work bridges architecture, computational modeling, and machine learning.

Glyn Hicksمشاهده پروفایل

دانشیار

• Syntactic theory
• Language acquisition
• Bilingual syntax attrition
• +۳ مورد دیگر

Glyn Hicks is an Associate Professor and Head of the Department of Modern Languages and Linguistics at the University of Southampton. He holds a PhD in Linguistics from the University of York, with research focusing on syntactic theory, language acquisition, and bilingual syntax attrition. His work explores Minimalist approaches to syntactic phenomena like 'tough'-movement and binding theory, alongside applications to second language acquisition and attrition in bilingual speakers. Research highlights include co-investigating the AHRC-funded 'Vulnerable Native Grammars' project (2020-2023), examining attrition in native grammars of bilinguals exposed to second languages post-childhood. He teaches undergraduate modules such as Elements of Linguistics, Syntax, and Advanced Syntax, and has contributed to postgraduate language analysis courses. Education: BA French & Linguistics (York), MA & PhD Linguistics (York) Active Roles: Chair of AHRC Peer Review College (2017-2020), Chair of QAA Subject Benchmark Group (2021-2022) His research bridges formal syntactic theory with applied linguistics, emphasizing cross-linguistic comparative analysis across Germanic and Romance languages.

Ajitha Rajanمشاهده پروفایل

استاد

• Software Testing
• Software Verification
• Automated Testing
• +۱۲ مورد دیگر

Ajitha Rajan is a Professor (Personal Chair of Software Testing and Verification) at the School of Informatics, University of Edinburgh. Previously, she was a post-doctoral researcher at Oxford University's Computer Science Department and Laboratoire d'Informatique de Grenoble (LIG) in France. She earned her PhD in Computer Science from the University of Minnesota in August 2009 under the supervision of Prof. Mats Heimdahl. Her research spans two main directions: Automated Software Testing Techniques covering test input generation, test oracles, and coverage metrics; and Biomedical Artificial Intelligence focusing on cancer survival models, interpretability for biological sequences, and medical images. Her work bridges software engineering and biomedical applications, particularly in the development of trustworthy AI systems for healthcare. Professor Rajan leads several significant research projects including a Royal Society Industry Fellowship (2022-2025) on AutoTest for autonomous vehicle perception safety, the H2020 European Project KATY (2021-2025) on AI for genomics and personalized medicine where she serves as Edinburgh Lead PI, and an EPSRC Trustworthy Autonomous Systems Node project (2020-2024). Her recent publications demonstrate strong activity across software testing, explainable AI, and biomedical applications, with numerous papers accepted to top conferences in 2025 including ML for Healthcare, IJCAI, and ESEM. Among her scientific recognitions, she received the Best Reviewer Award at ISSTA'25. Her work has been consistently published in leading venues including ICSE, ICASSP, and Communications Biology. Professor Rajan actively mentors PhD students working on diverse topics from automated testing of speech recognition systems to explainable AI for medical image analysis and cancer immunotherapy. She teaches undergraduate courses in Software Testing, Computer Programming, and Embedded Systems, and has been instrumental in establishing several fully funded PhD positions through Centres for Doctoral Training at the University of Edinburgh.

Ross Horneمشاهده پروفایل

مدرس ارشد

• Security protocols
• Privacy-preserving technologies
• Concurrency theory
• +۷ مورد دیگر

Ross Horne is a Senior Lecturer in the Department of Computer & Information Sciences at the University of Strathclyde, Glasgow, United Kingdom. He is a member of the StrathCyber and Mathematically Structured Programming research groups. Education: PhD (University of Southampton, 2012), BA (Oxford University, 2005) Prior Appointments: Research Fellow at University of Luxembourg (2018-2023), Senior Research Fellow at Nanyang Technological University (2015-2018), Associate Professor at Kazakh-British Technical University (2012-2015) Research Interests: Dr. Horne's work focuses on security and privacy protocols for digital systems, particularly addressing threats in payment technologies, ePassports, and decentralized identity management (e.g., Solid protocol). His theoretical contributions bridge concurrency theory, proof theory, and logic through applications to security verification and process calculi. Developed formal models for unlinkability in EMV payment protocols Created intuitionistic logical frameworks for process equivalence Explored graphical proof systems beyond formulaic representations Investigated legal-compliant AI for space systems (CubeSat anomaly detection) Scientific Contributions: He has published extensively in top venues including ACM CCS, IEEE CSF, LICS, and CONCUR. His 2017 CONCUR best paper introduced intuitionistic characterizations of bisimilarity. Principal Investigator for EU COST Action on Distributed Knowledge Graphs Co-developed privacy models adopted in Luxembourg parliamentary responses Advising: Currently accepting PhD students with strong mathematical and computer science skills for research in security/privacy of emerging systems. Former student Semen Yurkov completed a thesis on privacy-preserving smart card payments. Interdisciplinary Work: Collaborates with space lawyers through the Interdisciplinary Master Program in Space Resources. Projects include AI for CubeSat reliability and legal-compliant software certification frameworks.