جستجوی استاد راهنمای دانشگاهی

• Semantics
• Language Technology
• Recommender Systems
• +۵ مورد دیگر

Jon Atle Gulla is a Professor at NTNU and Director of the Norwegian Research Centre for AI Innovation (NorwAI). He holds academic leadership roles, including former Head of the Department of Computer Science and Informatics at NTNU. His expertise spans Semantics, Language Technology, Recommender Systems, and AI-driven innovation. He has nearly 150 international publications and advised over 100 students across MSc, PhD, and postdoctoral levels. Education: MSc in Computer Science (1988), PhD in Computer Science (1993) from Norwegian Institute of Technology (NTH) MSc in Linguistics (1995), University of Trondheim MSc in Management (Sloan fellowship, 2003), London Business School Research interests focus on Semantics and Language Technology applied to Recommender Systems, Information Retrieval, and Text Analysis. He explores AI-based innovations in digitalization and entrepreneurship, advising industry on AI adoption and commercialization. Notable projects include Big Data collaborations with DNB, RecTech for news recommendation, and Trondheim Analytica analyzing political texts/social media. Publications emphasize AI applications in news recommendation, political text analysis, and Scandinavian language models. His work addresses ethical AI, copyright implications, and cross-lingual NLP challenges. Awards: Member of the Royal Norwegian Society of Arts and Sciences. Advising/grants: Supervised 30 PhD students and 70 MSc students. Involved in startups like Fast Search & Transfer (acquired by Microsoft) and Mito.ai/Strise.ai. Active in reviewing for journals like Data & Knowledge Engineering and conferences like ACL. Labs/teams: Leads NorwAI, co-founder of INRA and NOBIDS workshops. Collaborates with industry and academia on AI-driven solutions.

Roman Feimanمشاهده پروفایل

استادیار

• Cognitive Development
• Cognitive Psychology
• Cognitive Science
• +۳ مورد دیگر

Roman Feiman is the Thomas J. and Alice M. Tisch Assistant Professor of Cognitive, Linguistic, and Psychological Sciences and an Assistant Professor of Linguistics at Brown University. He directs the Brown Language and Thought Lab, focusing on how humans combine words into meaningful sentences and develop logical reasoning abilities. His research integrates methods from cognitive developmental psychology, psycholinguistics, and formal semantics. Feiman holds a PhD in Psychology from Harvard University (2015), followed by postdoctoral training at Harvard and UC San Diego. His work explores the cognitive systems underlying language and thought, including negation comprehension, quantifier scope, and the development of exact equality concepts. He teaches courses such as Language Processing in Humans and Machines and Logic in Language and Thought . His research interests span cognitive development, linguistic pragmatics, and the language of thought hypothesis. Notable findings include studies on children’s understanding of negation and how logical principles shape early language acquisition. Feiman has been recognized with the 2023 Henry Merritt Wriston Fellowship. His lab investigates topics like word referencing, semantic development, and the interplay between language and nonverbal reasoning. Recent work examines how neural networks might model human cognitive processes, bridging AI and psychological theory.

David Nelkenمشاهده پروفایل

استاد

• Comparative Law
• Criminology
• Legal Theory
• +۶ مورد دیگر

Professor David Nelken is a distinguished academic in the field of law and legal studies, currently serving as Professor of Comparative and Transnational Law at the Dickson Poon School of Law, King's College London. He previously held positions at prestigious institutions including the University of Cambridge, University College London, and the University of Macerata (Italy) as a Distinguished Professor. His academic career includes roles as Distinguished Research Professor at Cardiff University (1995–2013) and Visiting Professor of Criminology at the University of Oxford (2010–2014). Professor Nelken's research focuses on comparative sociology of law, criminology, and legal/social theory. He has made significant contributions to understanding global social indicators, juvenile justice, white-collar crime, and international criminal justice. His work emphasizes interdisciplinary approaches, combining theoretical inquiry with empirical research. His notable awards include the American Sociological Association Distinguished Scholar Award (1985), Sellin-Glueck International Award (2009), and Fellowships from the British Academy (2023) and the Academy of Social Sciences (2009). He has served on editorial boards of leading journals and contributed to global legal governance initiatives, including the SCOPUS Database evaluation committee. Professor Nelken has advised on criminal justice systems globally, including roles in Scotland’s Children’s Hearings and Italian Regional Crime Committees. He is actively involved in PhD supervision, having been awarded supervisory excellence in multiple years. His teaching spans Jurisprudence, Law & Social Theory, and Sociology of Law at both undergraduate and postgraduate levels.

Jim Smithمشاهده پروفایل

استاد

• Interactive Artificial Intelligence
• Statistical Disclosure Control
• Privacy Leakage from AI Models
• +۷ مورد دیگر

Jim Smith is a Professor in Interactive Artificial Intelligence at the University of the West of England (UWE), Bristol, affiliated with the School of Computing and Creative Technologies and the Department of Computer Science and Creative Technologies. He serves as Director of the Computer Science Research Centre and leads the AI@UWE theme. His research is supported by UKRI, Innovate UK, and partnerships with organizations including Health Data Research UK, Office for National Statistics, NHS Scotland, and DSTL. University: University of the West of England School: School of Computing and Creative Technologies Department: Department of Computer Science and Creative Technologies Role: Professor in Interactive Artificial Intelligence Leadership: Director, Computer Science Research Centre Research Interests : Jim Smith's work focuses on Interactive Artificial Intelligence, particularly at the intersection of AI and privacy preservation when using sensitive data for public good. His research includes statistical disclosure control, privacy leakage from AI models, evolutionary computation, machine learning, and systems that learn through human interaction or self-adaptation. He explores how AI can automate privacy checks in research outputs and assess vulnerabilities in trained models. Recent Publications : His recent work spans AI privacy in trusted research environments (e.g., SACRO, SDC-Reboot), dialogue act classification, human-robot interaction, and visualization of deep learning models. Themes include privacy-preserving AI, automated disclosure control, interactive machine learning, and neuromorphic computing. Machine Learning & Privacy Evolutionary Computation Interactive AI Systems Human-Computer Interaction Statistical Disclosure Control Federated Learning Security Scientific Awards : No specific awards are mentioned in the provided texts. Advising and Grants : He currently supervises PhD students on topics including spatio-temporal air quality modeling, federated learning privacy, and threat detection in mobile networks. He leads Innovate UK and UKRI-funded projects such as SACRO and SDC-Reboot, focusing on AI-driven solutions for data confidentiality in public sector research. Interactive Machine Learning for Claim Settlement (Innovate UK) SDC-Reboot (DARE UK/Health Data Research UK) Threat Identification in Mobile Networks (Ribbon Communications) Labs and Teams : He leads the AI@UWE initiative and the Computer Science Research Centre at UWE. His work involves collaboration through DARE UK and open-source development via the AI-SDC GitHub organization, which hosts tools from SACRO and GRAIMATTER projects.

Thomas Demeesterمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Natural Language Processing
• Deep Learning
• +۷ مورد دیگر

Thomas Demeester is an Associate Professor at the Internet Technology and Data Science Lab (IDLab), Ghent University - imec, Belgium. Appointed as Assistant Professor in 2019, he leads an AI research group focused on health applications and drug design, co-directing the Text-to-Knowledge research cluster with Prof. Chris Develder. His educational background includes: M.Sc. in Electrical Engineering from Ghent University (2005), completed with thesis work at ETH Zurich Ph.D. in Computational Electromagnetics from Ghent University (2009), funded by Research Foundation - Flanders (FWO) Demeester's research spans artificial intelligence with emphasis on deep learning and neuro-symbolic methods. Current tracks include energy-based models (Hopfield Networks, Deep Equilibrium Models), diffusion models for drug design, and clinical reasoning systems. His work bridges NLP, healthcare informatics, and generative AI with strong industry partnerships. Recent publications (2023-2025) reveal strategic expansion from NLP into health-centric AI: BioLORD biomedical encoders (2023), synthetic medical data frameworks (UAI/NeurIPS 2024), and novel diffusion model guidance (ICLR 2025). This evolution demonstrates convergence of generative modeling, clinical data analysis, and protein design. He actively mentors 24 PhD students across diverse AI domains: Current Research: Conversational agents, emotion analysis, clinical reasoning, antibody design, and diffusion model optimization Recent Graduates: Interpretable language models, biomedical semantics, task-oriented dialogue, and social media knowledge extraction Research is supported by imec funding and collaborations with Flemish biotech companies, building on his post-doctoral experience securing media-sector projects. Within IDLab, he co-leads the Text-to-Knowledge cluster driving NLP innovations for healthcare, legal, and economic applications.

Gregory Craneمشاهده پروفایل

استاد

• Greek & Latin Language
• Digital Humanities
• Classical Philology
• +۳ مورد دیگر

Gregory Crane is Professor of Classical Studies and Computer Science at Tufts University, where he holds the Winnick Family Chair in Technology and Entrepreneurship and serves as Chair of the Classical Studies Department. He also maintains a professorship in the School of Engineering's Computer Science department. Previously, he was Alexander von Humboldt Professor of Digital Humanities at Leipzig University in Germany from 2013-2019. PhD in Classical Philology, Harvard University (1985) BA in Classics, Harvard University (1979) Crane's research bridges traditional classical scholarship with digital technology. His work in classical studies focuses on ancient Greek authors, particularly Thucydides, with two major books published on the subject. Simultaneously, he has been a pioneer in digital humanities, beginning work on digital tools for classics as a graduate student in 1982. He is the Editor-in-Chief of the Perseus Project, which he has directed since 1985, developing morphological analysis systems and overseeing the project's evolution through multiple generations of digital library technology. His recent publications demonstrate a strong trend toward integrating artificial intelligence with classical language studies, developing next-generation digital libraries, and exploring new methods for engaging with classical texts in the digital age. Crane's work increasingly focuses on making ancient languages more accessible through technology, with research spanning digital philology, language learning tools, and corpus-based approaches to historical languages. Winnick Family Chair in Technology and Entrepreneurship Alexander von Humboldt Professor of Digital Humanities Crane has secured substantial research funding from major organizations including the National Endowment for the Humanities, the Andrew W. Mellon Foundation, the National Science Foundation, and Google. His current and recent projects include "Reinventing the study of ancient languages" and "Beyond Translation -- new possibilities for reading in a digital age." He has advised numerous students through senior honors theses and directed dissertation research in Classical Studies at Tufts University. Crane leads the Perseus Digital Library research program, which has evolved through multiple generations of technology to become a leading resource for classical studies. His work has established critical infrastructure for digital classics, including named entity identification systems and morphological analysis tools that have shaped the field of digital humanities.

Anett Hoppeمشاهده پروفایل

پژوهشگر

• Search as Learning
• Educational Technology
• Artificial Intelligence in Education
• +۵ مورد دیگر

Dr. Anett Hoppe is a research staff member at the Leibniz Information Centre for Science and Technology (TIB) in Hannover, Germany, where she works in the Visual Analytics research group. Her research focuses on the intersection of artificial intelligence, education technology, and information science, with particular emphasis on how people learn through search processes and educational video consumption. Dr. Hoppe completed her academic journey with: Ph.D. in Semantic Web technologies for online user profiles from the University of Burgundy, Dijon, France Her primary research interests span Search as Learning, software-based support for scientific reproducibility, and ethical considerations in computer-based decision making. She investigates how visual elements, reading sequences, and AI technologies impact knowledge acquisition during web search and educational video consumption. Her work bridges human-computer interaction, educational psychology, and information retrieval to create more effective learning experiences, with recent publications examining the role of large language models, vision-language models, and visual complexity in educational contexts. Analysis of her recent publications (2024-2025) reveals a strong interdisciplinary focus combining computer science, educational psychology, and information science. Her research examines video-based learning effectiveness, knowledge gain prediction, educational resource discovery, and the impact of visual elements on learning outcomes. She consistently explores how AI technologies can be leveraged to enhance educational experiences while maintaining attention to ethical considerations and scientific reproducibility. Dr. Hoppe maintains active collaborations with researchers across multiple institutions, with frequent co-authorship patterns indicating strong research partnerships, particularly with Ralph Ewerth and other members of the Visual Analytics group at TIB. Her work supports TIB's mission to advance knowledge infrastructure and scholarly communication through innovative technological solutions while directly addressing practical challenges in educational technology and information retrieval.

Angela Crowمشاهده پروفایل

دانشیار

• Design
• User Experience (UX)
• Freedom of Movement
• +۷ مورد دیگر

Angela Crow is an Associate Professor at James Madison University (JMU) in the School of Writing, Rhetoric and Technical Communication, where she has served since 2012. Her research bridges literacy studies, design, and urban mobility, focusing on how communities advocate for car-free infrastructure and equitable public spaces. She explores the role of digital communication in fostering feminist interventions, particularly around cycling advocacy and street design. Her work intersects with gender studies, urban studies, and rhetorical theory. Educated at the University of Kansas (Ph.D., 1997) and Point Loma College (B.A., 1987), she has authored books on writing programs and composition studies, including Aging Literacies (2006) and Field of Dreams (2002). Recent publications analyze surveillance, privacy in digital contexts, and transportation equity. Her research often highlights marginalized voices in shaping public discourse. Research Interests: Her current projects examine embodied literacies in mobility advocacy, social media practices of grassroots movements, and the rhetoric of urban infrastructure. She critiques car-centric planning through feminist and critical frameworks, emphasizing accessibility and safety for non-car users. Her work also addresses aging populations’ digital literacies and the intersection of technology with social inequality. Publications: Her articles span rhetorical analysis of social movements, educational assessment frameworks, and the sociotechnical dimensions of writing. Recent trends include collaborations on privacy in big data and participatory design for community mobility.

Nicole Myersمشاهده پروفایل

دانشیار

• Criminology
• Criminal Justice
• Pre-trial Detention
• +۳ مورد دیگر

Nicole Myers is an Associate Professor and Graduate Coordinator in the Department of Sociology at Queen's University, Canada. She holds a PhD and MA from the University of Toronto and a BA from the University of Guelph. Her research focuses on criminology, particularly pre-trial detention, bail processes, and systemic discrimination within the criminal justice system. She critiques current practices such as excessive bail conditions, institutional risk aversion, and the erosion of the presumption of innocence. Her work examines bail court dynamics, including adjournment cultures, systemic overreach in conditions (e.g., banning ordinary locations), and the impact on marginalized groups. Recent studies highlight crises in Canada’s bail system, including deepening detention rates and Manitoba’s discriminatory practices. Myers emphasizes reform needs through policy analysis and empirical studies. Publications span 2009–2024, analyzing bail’s role as punishment, surety supervision roles, and youth justice. Her research bridges legal sociology and criminology, aiming to improve judicial practices and reduce pre-trial detention inequities.

• Neurolinguistics
• Computational Linguistics
• Psycholinguistics
• +۴ مورد دیگر

Jon Brennan is an Assistant Professor in the Department of Linguistics at the University of Michigan, affiliated with the College of Literature, Science, and the Arts (LSA). His research focuses on neurolinguistics, computational linguistics, and psycholinguistics, particularly investigating how the brain processes language structure and meaning. He leads the Computational Neurolinguistics Lab, which develops neurocomputational models to study language comprehension mechanisms. Brennan received an NSF Grant for collaborative research with Christophe Pallier (Paris) on neurocomputational models of natural language processing. His work integrates EEG, fMRI, and MEG techniques to decode linguistic features in neural signals. Key research areas include syntax-semantics interfaces, multilingual processing, and developmental disorders like dyslexia. Notable contributions include studies on hierarchical syntactic structure, minimal pairs in language models, and neural correlates of theory of mind in children. Brennan collaborates internationally, exemplified by the US-French NSF-CRCNS grant. He has published extensively on topics like neural decoding of grammatical features, LLM internal representations, and bilingual processing mechanisms. Scientific awards include the NSF Collaborative Research in Computational Neuroscience (CRCNS) Grant (2016). His research bridges computational modeling and experimental neuroscience, aiming to reveal how language mechanisms are implemented in neural systems.

• Chinese Language Pedagogy
• Chinese Linguistics
• Chinese Cinema
• +۵ مورد دیگر

Zhiqiang Yu serves as an Associate Professor in the Department of Modern Languages and Comparative Literature at Baruch College's Weissman School of Arts and Sciences, City University of New York. With over two decades of teaching experience, he has established himself as a dedicated educator specializing in Chinese language, cinema, and civilization courses. Education: Ph.D. in Chinese, University of Washington M.A. in Asian Civilization, University of Iowa B.A. in Chinese Literature, Fudan University (Shanghai) Professor Yu's research focuses on innovative approaches to Chinese language pedagogy, with particular interest in applying economic principles and artificial intelligence to language teaching. His work bridges traditional linguistic scholarship with modern educational technology, examining how efficiency, resource allocation, and technological advancements can enhance language learning outcomes. His research spans Chinese linguistics, dialectology, cinema studies, and cultural elements in language teaching. His publication record reveals a consistent trajectory toward optimizing language instruction through systematic analysis. Recent work increasingly focuses on AI applications in language education and the economic framework of pedagogical efficiency. His scholarship demonstrates a progression from traditional linguistic analysis toward innovative teaching methodologies that incorporate modern technological and theoretical frameworks. Scientific Awards: Award of Excellent Academic Research Reviewer from Journal of International Chinese Education (2016) Graduate Teaching Fellowship from University of Washington (1993) Graduate Teaching Fellowship from University of Iowa (1989) Graduate Research Fellowship from University of Iowa (1988) Student Excellency Award from Fudan University (1984) Professor Yu has served extensively on departmental committees including as Department Assessment Coordinator and Secretary of the Asian and Asian-American Studies Committee. He has organized numerous academic events featuring prominent Chinese cultural figures and has contributed to developing Chinese language curriculum resources including online placement tests. His professional service extends to editorial work for CUNY publications and Chinese language training for the New York Police Academy. He maintains active involvement with multiple professional organizations including the American Name Society, American Oriental Society, American Society of Geolinguistics, Association for Asian Studies, and Chinese Language Teachers Association, frequently presenting at international conferences on Chinese language pedagogy.

• Neuroscience
• Education
• Cognitive Science
• +۳ مورد دیگر

Kay James is an Associate Professor of Neuroscience and Education at Teachers College, Columbia University, and serves as Director of the Graduate Program in Neuroscience and Education and the Neurocognition of Language Lab. Their work focuses on neural mechanisms underlying language disorders, second language acquisition, and cognitive processes in schizophrenia. Key affiliations include Biobehavioral Sciences, Neuroscience and Education, Human Development, and Cognitive Science in Education. Research interests emphasize the neural basis of language processing in pathological contexts such as developmental speech disorders and schizophrenia, alongside second language acquisition in adults. Their interdisciplinary approach bridges cognitive neuroscience with clinical and educational interventions. Publications span studies on mismatch negativity in speech disorders, syntactic development in Arabic diglossia, and brain-behavior asymmetry in schizophrenia. Ongoing work explores voice-related cortical potentials and emotional face processing through electrophysiological methods. Labs and teams include the Neurocognition of Language Lab, focusing on language neurobiology and clinical applications. Grants and advising roles are not explicitly detailed in the provided materials.

David Hsuمشاهده پروفایل

استاد

• Robotics
• Artificial Intelligence
• Machine Learning
• +۲ مورد دیگر

David Hsu is Provost's Chair Professor in the Department of Computer Science at the National University of Singapore (NUS) School of Computing, where he founded and directs the NUS Artificial Intelligence Laboratory (NUSAIL) and leads the Smart Systems Institute. His academic leadership includes chairing major conferences such as Robotics: Science & Systems (2015) and IEEE ICRA (2016), alongside editorial roles in IEEE Transactions on Robotics and the Journal of Artificial Intelligence Research. He earned a B.Sc. in Computer Science & Mathematics from the University of British Columbia and a Ph.D. in Computer Science from Stanford University. His research spans robotics, AI, and computational biology, with recent focus on robot planning under uncertainty and human-robot collaboration. Current work integrates machine learning with decision-theoretic planning to enable robust human-robot co-existence in unstructured environments. Analysis of his 2023-2025 publications reveals dominant trends in deformable object manipulation (e.g., clothes handling via semantic keypoints), open-world navigation using scene graphs, and LLM-driven multi-agent reasoning for complex tasks. Key innovations include perspective-aware visual grounding for human-centric interaction and functional object arrangement through compositional generative models, reflecting a strong emphasis on real-world applicability. His scientific contributions have earned prestigious recognition: IJCAI-JAIR Best Paper Prize (2022) for foundational AI research Robotics: Science & Systems Test of Time Award (2021) IEEE Fellowship (2018) for contributions to robotic planning RSS Best Systems Paper Award (2017) RoboCup Best Paper Award at IROS (2015) Humanitarian Robotics Award at ICRA (2015) As director of the Adaptive Computing Laboratory, Hsu drives research on fundamental computational frameworks for human-robot interaction. The lab's work on uncertainty-aware decision-making has secured significant research funding through grants from Singapore's National Research Foundation and industry partnerships with robotics firms. While specific student names aren't publicized, his leadership in the NUSAIL indicates extensive mentorship of doctoral candidates in AI and robotics.

John R Andersonمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Cognitive Science
• Computational Psychology
• +۳ مورد دیگر

John R Anderson is the Richard King Mellon University Professor of Psychology and Computer Science at Carnegie Mellon University (CMU), affiliated with the Department of Psychology within the Dietrich College of Humanities and Social Sciences. His research focuses on understanding higher-level cognition, particularly mathematical problem-solving, through the development of the ACT-R cognitive architecture—a computational framework simulating human cognitive processes. This architecture integrates behavioral, neural, and educational data to model learning and decision-making. Anderson’s work bridges cognitive science, neuroscience, and educational technology. He investigates how brain imaging (e.g., fMRI, EEG) can reveal the temporal dynamics of cognitive processes and improve instructional methods. His research emphasizes analyzing brain activity time courses to uncover underlying mechanisms of problem-solving and skill acquisition. Key Research Themes: Cognitive architectures, neural correlates of learning, computational models of memory, and intelligent tutoring systems. Notable Contributions: Development of the ACT-R architecture, integration of neuroimaging with cognitive modeling, and studies on skill transfer and learning strategies. Anderson’s publications include seminal books like Cognitive Psychology and Its Implications and How Can the Human Mind Occur in the Physical Universe? His work has advanced understanding of associative memory, strategic decision-making, and the application of cognitive models in educational technology. His lab, the ACT-R Research Group, collaborates across disciplines to model complex cognitive tasks and their neural foundations. Current projects analyze real-time brain activity to refine educational interventions and improve human-machine interaction.

Patrick Sturtمشاهده پروفایل

دانشیار

• Psycholinguistics
• Syntactic processing
• Language comprehension
• +۵ مورد دیگر

Patrick Sturt is a Reader in Psychology at the University of Edinburgh's School of Philosophy, Psychology and Language Sciences. His research focuses on syntactic processing in language comprehension, computational models of incremental parsing, anaphor resolution, and eye movements in reading. With over 100 publications and more than 3,300 citations, he is a recognized expert in psycholinguistics and language processing. Dr. Sturt's research interests span multiple areas of language processing. He investigates how humans comprehend sentences in real-time, with particular focus on syntactic structures, agreement phenomena, and anaphoric reference. His work often employs eye-tracking methodologies to examine the moment-by-moment processing of linguistic information. He has made significant contributions to understanding how readers handle syntactic ambiguities, garden-path sentences, and the role of prediction in language comprehension. His recent publications demonstrate a strong focus on cross-linguistic studies, particularly examining language processing in Mandarin Chinese and Korean. Many of his studies investigate how syntactic and semantic information interact during comprehension, and how linguistic structures like honorifics, classifiers, and non-canonical word orders are processed. His work bridges theoretical linguistics with experimental psycholinguistics, providing empirical evidence for models of sentence processing. Dr. Sturt actively supervises PhD students including Carine Abraham, Wenjia Cai, Chiuchou Hao, Ruomeng Zhu, and Christy Gu. He teaches Psychology of Language 1 and 2 at the MSc level, as well as Data Analysis for Psychology in R for first-year undergraduates. His teaching reflects his research expertise, providing students with both theoretical knowledge and practical analytical skills. Based in Room G29 of the Psychology Building at 7 George Square, Edinburgh, Dr. Sturt maintains regular office hours on Tuesdays from 3-4pm, providing accessibility to students and colleagues. His email address is patrick.sturt@ed.ac.uk.