جست‌وجوی استاد و پژوهشگر

Caroline Lehrمشاهده پروفایل

استاد

• Translation Studies
• Psychology of Language
• Emotion in Translation
• +۵ مورد دیگر

Caroline Lehr is Professor of Translation Studies at the Zurich University of Applied Sciences (ZHAW) School of Applied Linguistics, where she works in the Institute of Multilingual Communication. She is also a member of the University Ethics Committee. Her academic career spans multiple institutions including the University of Geneva, University College London, and Copenhagen Business School. PhD in Psychology of Language & Translation Studies from University of Geneva (2014) Master of Arts in Specialized Translation from University of Geneva CAS in Higher and Professional Education from ZHAW Professor Lehr's research focuses on the intersection of translation studies, cognitive psychology, and emerging technologies. Her work examines translation processes and multilingual text production, multilingualism in organizations, the use of artificial intelligence in multilingual communication, and the role of cognition, emotion and motivation in language professions. She has pioneered research on 'MT literacy' - the responsible and competent use of machine translation - particularly in educational contexts. Her recent publications reveal a strong trend toward examining the impact of artificial intelligence on translation and language professions, with particular attention to emotional intelligence, cognitive load, and professional adaptation in the face of technological change. She has co-edited significant works like 'The psychology of translation: an interdisciplinary approach' and published extensively on neural machine translation in language teaching. Co-project leader of 'Language learning in the age of Artificial Intelligence' Project leader of 'Use of machine translation in healthcare' Co-project leader of 'AI Literacy and Post-Editing Training for Language Services in Multilingual Companies' Professor Lehr actively contributes to bridging academic research with practical applications in the language industry. She has developed training interventions to improve emotional intelligence for translators and has been instrumental in establishing machine translation literacy as a critical competence for language professionals. Her work demonstrates how emotional factors influence translation performance and how professionals can develop resilience in rapidly changing technological landscapes.

Andrew Hardieمشاهده پروفایل

دانشیار

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

Dr. Andrew Hardie is a Reader in Linguistics at Lancaster University, holding a position equivalent to Associate Professor. He is affiliated with the Faculty of Humanities, Arts and Social Sciences and the Department of Linguistics and English Language within the School of Social Sciences. His primary research specialism focuses on corpus-based methodology and its applications across various disciplines: Corpus design and construction methodologies Development of corpus analysis software tools Applications in grammar of English and other languages Extensions to discourse analysis, language teaching, and other humanities and social sciences fields Dr. Hardie's work spans both theoretical and applied linguistics, with particular emphasis on adapting corpus methods for social scientists and humanists in fields including Psychology, Geography, History, and English Literature. His expertise extends to multiple languages, with special focus on South Asian languages such as Nepali, Urdu, and Hindi. He has developed several significant software tools for corpus linguistics, including Corpus Workbench (as a lead developer), CQPweb (as creator), Unicodify, and Unitag, which have substantially advanced the field of corpus linguistics methodology. His research portfolio includes major projects like the ESRC Centre for Corpus Approaches to Social Science (where he serves as Deputy Director) and UCREL (where he is Chair), demonstrating his leadership in the field. His work bridges theoretical linguistics, computational methods, and practical applications across multiple disciplines. Dr. Hardie actively supervises PhD students working on diverse topics from collocational errors in language learning to sociolinguistics of swearing in Arabic, reflecting the breadth of his research interests and influence across linguistic subfields.

• Computer Vision
• Scene Understanding
• 3D/4D Vision
• +۷ مورد دیگر

Dr. Armin Mustafa is an Associate Professor in Computer Vision and AI at the University of Surrey, where he holds a prestigious Royal Academy of Engineering Research Fellow position. He is affiliated with the Centre for Vision, Speech and Signal Processing (CVSSP), the School of Computer Science and Electronic Engineering, and the Surrey Institute for People-Centred Artificial Intelligence (PAI). His research focuses on developing AI systems for visual understanding of complex dynamic scenes, with applications in entertainment, autonomous systems, and augmented/virtual reality. Dr. Mustafa completed his PhD in general dynamic scene reconstruction from multi-view videos in 2016 from the University of Surrey under the supervision of Prof. Adrian Hilton. Prior to his doctoral studies, he worked for three years (2010-2013) at Samsung Research Institute in Bangalore, India, in the field of Computer Vision. His research expertise spans Computer Vision, Scene Understanding, 3D/4D Vision, Virtual Reality, Light Fields, Machine Learning, Video Captioning, Augmented Reality, Artificial Intelligence, and Audio-visual Video Understanding. Dr. Mustafa has pioneered advances in 4D vision, NLP, and Scene Understanding over the past decade, with a particular focus on enabling machines to model and interpret real-world environments for socially beneficial applications. His work bridges theoretical advances in computer vision with practical applications in media production, virtual reality, and autonomous systems. Analysis of Dr. Mustafa's recent publications reveals a strong focus on multimodal learning, particularly the integration of audio and visual information for scene understanding. His work spans diverse areas including shadow detection and removal, audio event classification, video captioning, person image generation, and dynamic scene reconstruction. A notable trend is his exploration of transformer architectures for both vision and audio tasks, as well as the application of self-supervised learning techniques to reduce dependency on labeled data. Dr. Mustafa has received numerous prestigious awards: 2018 - Research Fellowship, The Royal Academy of Engineering, UK 2017 - Young Researcher award, CVPR 2016 - Doctoral Consortium grant, CVPR 2015 - BMVA travel grant for ICCV 2014 - Set-Squared Research to Innovator grant 2013 - Overseas Research Scholarship, FEPS, The University of Surrey 2010 - Cadence Silver Medal, Indian Institute of Technology, Kanpur As a dedicated mentor, Dr. Mustafa supervises several PhD students working on cutting-edge topics including multi-person reconstruction, audio-visual scene understanding, and automatic storyboard generation. His research is supported by significant grants including a £15 million UKRI Prosperity Partnership with the BBC (AI4ME), a 5-year Royal Academy of Engineering fellowship (4D Vision for Perceptive Machines), and multiple projects with industry partners such as Figment Productions and Foundry. Dr. Mustafa is an active member of the Centre for Vision, Speech and Signal Processing (CVSSP), one of the world's leading research centers in vision, speech, and signal processing. He also contributes to the Surrey Institute for People-Centred Artificial Intelligence (PAI), where he serves as a Surrey AI Fellow. His work often involves collaboration with industry partners and other academic institutions across Europe.

• Linguistics
• Dialogue Semantics
• Pragmatics
• +۴ مورد دیگر

Jonathan Ginzburg is a Researcher in the Department of Linguistics at Université Paris Diderot, affiliated with the CLILLAC-ARP research group. His work bridges linguistics, cognitive science, and computational models, focusing on dialogue semantics, pragmatic functions, and developmental language acquisition. Education details are not explicitly provided in the text, but his research spans formal semantics, syntax, and multimodal interaction. His studies on laughter dynamics and infant communicative behaviors have advanced understanding of pragmatic functions in early development. Key research interests include dialogue structure, question-response systems, and the integration of cognitive science with linguistic theory. Recent work explores neural correlates of language processing through type-theoretical semantics and corpus-based methodologies. He has pioneered the analysis of non-sentential utterances and their role in social interaction. His contributions to dialogue systems design for low-resource languages and the DUEL corpus (analyzing disfluencies, exclamations, and laughter) reflect his interdisciplinary approach. Current projects investigate laughter's pragmatic functions across developmental stages and cross-linguistic variations in exclamatory constructions. Laboratory affiliations include the CLILLAC-ARP laboratory, where he develops computational tools for analyzing dialogue semantics and cognitive interactions. His work on 'response spaces' for questions integrates machine learning and formal pragmatics to model conversational coherence.

Wei Shaoمشاهده پروفایل

استادیار

• Medical Imaging
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Dr. Wei Shao is an Assistant Professor in the College of Medicine at the University of Florida, specializing in artificial intelligence applications in medical imaging. His work focuses on developing machine learning algorithms for medical image registration, segmentation, and diagnosis, with a particular emphasis on integrating these tools into clinical workflows. Dr. Shao holds a Ph.D. in Electrical and Computer Engineering from Stanford University (2022), preceded by M.S. degrees in Mathematics and Electrical and Computer Engineering from the University of Iowa (2019-2018). His postdoctoral training focused on deep learning and medical imaging. His research projects include: Machine learning algorithms for multimodal image registration and segmentation AI-driven disease diagnosis on medical images Integrating image processing into clinical practices Notable contributions include advancements in 3D medical image segmentation, text-guided models for radiology, and AI-enhanced micro-ultrasound for prostate cancer screening. His work bridges computational methods with clinical needs, aiming to improve diagnostic accuracy and patient care. Recent publications highlight innovations in diffusion models, vision-language integration for medical imaging, and robust artifact detection in 4DCT scans. These studies underscore his commitment to advancing AI-driven solutions in healthcare.

Toby Daviesمشاهده پروفایل

دانشیار

• Crime Science
• Urban Analytics
• Spatial Analysis
• +۶ مورد دیگر

Toby Davies is an Associate Professor in Criminal Justice Data Analytics at the University of Leeds, School of Law. His work focuses on quantitative criminology, spatial analysis, and computational methods to inform crime prevention. He holds a Mathematics degree from the University of Oxford (2008) and a PhD from University College London (UCL), followed by postdoctoral research on the EPSRC-funded Crime, Policing and Citizenship project. Before joining Leeds in 2023, he was at UCL’s Department of Security & Crime Science. His research spans interdisciplinary topics including urban form and crime, crime modeling, social networks, and cybercrime. He has collaborated with police agencies (West Yorkshire, Thames Valley, West Midlands Police) and governmental bodies (UK Home Office, London Mayor’s Office). A strong advocate for Open Science, he co-founded JDI Open to promote open practices in crime science. His recent work emphasizes policy interventions like phasing out pointed kitchen knives to reduce knife crime, leveraging data-driven approaches. He publishes widely in criminology, physics, network science, and general science journals, and has guest-edited special issues. His applied research aims to bridge theory and practice, developing tools deployed operationally in policing. Current interests include financial crime dynamics, social contagion of crime, and street network configurations’ impact on crime patterns.

• Psychometrics
• Network Theory
• Psychopathology
• +۲ مورد دیگر

Denny Borsboom is Professor in the Psychological Methods Group at the University of Amsterdam, where he directs the Social and Behavioural Data Science Centre. His research program develops network theories of psychopathology, novel psychometric methods, and formalized psychological theory through initiatives like the Psychosystems Project and Theory Methods Lab. Research focuses on conceptual foundations of measurement, complex systems approaches to mental disorders, and computational modeling of psychological phenomena. Recent publications advance network psychometrics, validity theory, and integration of intra/interindividual dynamics. Articles demonstrate strong methodological innovation through computational psychiatry applications, network theory development, and philosophical engagement with psychological foundations. Recurring themes include psychopathological networks, measurement realism, system transitions, and collaborative theory-building frameworks.

• Childhood Media Studies
• Developmental Psychology
• Media Psychology
• +۵ مورد دیگر

James Bonus is an Associate Professor at The Ohio State University in the School of Communication . His work explores childhood media experiences and the cognitive obstacles that impede learning from socioemotional and science-themed media, such as developing story schema and inaccurate reality judgments. He also investigates the effects of nostalgic media on adult audiences, focusing on temporal comparisons between past and present selves and their implications for psychological well-being. Education: PhD in Communication Science from the University of Wisconsin-Madison MA in Communication Science from the University of Wisconsin-Madison BA in Sociology and Journalism from Flagler College James Bonus’s research bridges media psychology and developmental communication , with a dual focus on children’s educational media challenges and adults’ nostalgia-driven experiences. His work addresses how media shapes STEM engagement , language acquisition , and family dynamics , emphasizing interactive and temporal dimensions . Publication Trends: His 2025–2022 work spans educational television , YouTube , and nostalgic entertainment , analyzing their roles in science learning , parent-child interactions , humor mechanisms , and temporal identity . Themes include media literacy , psychological well-being , and developmental communication , often integrating machine learning and bio-sensing methodologies.

• Cartography
• Geomatic Engineering
• Historical Map Analysis
• +۴ مورد دیگر

Dr. Yizi Chen is a Researcher affiliated with the Professorship for Cartography at ETH Zurich's Department of Civil, Environmental and Geomatic Engineering. Their work focuses on advancing cartographic techniques through AI-driven methods, historical map analysis, and geospatial technologies. Key contributions include automated map vectorization, semantic segmentation of historical maps, and integrating multimodal data for robotic systems. They have published extensively in top-tier journals and conferences, addressing challenges in deep learning applications for geomatic engineering. Education details are not explicitly provided in the text. Research interests include semantic segmentation, generative AI for cartography, and steganography in image translation. Notable publications span topics from eye-tracking segmentation to urban land use mapping, reflecting a strong interdisciplinary approach. Dr. Chen collaborates on projects involving historical map digitization and benchmarking datasets for computer vision tasks. No awards or grants are mentioned. Their work contributes to advancing geomatic engineering through innovative solutions in digital mapping and spatial data analysis.

Bernard Kochمشاهده پروفایل

استادیار

• Science of science
• Culture
• Cultural evolution
• +۲ مورد دیگر

Bernard Koch is an Assistant Professor in the Department of Sociology at the University of Chicago. His research focuses on the science of science, culture, cultural evolution, AI ethics, and computational social science. Prior to joining the University of Chicago, he was a Postdoctoral Research Fellow at Northwestern University’s Kellogg School of Management. He earned his Ph.D. in Sociology from UCLA in 2023. His work bridges sociology and computational methods, exploring topics such as machine learning applications in social research, ethical implications of AI, and cultural dynamics. Recent projects include analyzing the role of large language models (LLMs) in social simulations and confronting the misuse of genetics in online contexts. Koch’s articles span themes like data-centric machine learning (DMLR), the historical development of deep learning, and the lifecycle of datasets in research. He also investigates cultural evolution through case studies like music subcultures and material culture diversification. He holds no listed awards but has contributed to interdisciplinary collaborations, including genomics research on the Mnemiopsis leidyi organism. While no formal advisees are listed, his research group likely engages in computational social science projects.

• Adversarial Machine Learning
• Text Processing
• Machine Learning Algorithms
• +۳ مورد دیگر

Nura Aljaafari is a researcher in the Department of Computer Science, focusing on adversarial machine learning and text processing. Her work explores the robustness of machine learning models against adversarial attacks and defenses, particularly in federated learning and natural language processing contexts. Dr. Aljaafari holds a Doctor of Philosophy (Ph.D.) in Computer Science, providing expertise in advanced computing and machine learning methodologies. Her research interests center on adversarial machine learning, text processing, and enhancing the security of machine learning algorithms. Her recent studies include analyzing token compositionality in large language models and interpreting conceptual frameworks in GPT models, highlighting her focus on model interpretability and reliability. Earlier work includes investigating adversarial attacks in federated learning systems and developing defenses for license plate recognition systems. While her profile does not explicitly list awards or grants, her publications have garnered significant attention, with citations in cybersecurity and machine learning fields. Collaborations include developing bioinformatics tools using GANs and analyzing organizational security practices in Saudi Arabian contexts.

Rocco OLIVETOمشاهده پروفایل

استاد

• Software Engineering
• Artificial Intelligence
• Machine Learning
• +۷ مورد دیگر

Prof. Rocco OLIVETO is a Full Professor at the University of Molise, affiliated with the School of Biosciences and Territory. His research spans software engineering, artificial intelligence, cybersecurity, and healthcare technology. He focuses on empirical studies of developer practices, AI-driven code analysis, vulnerability detection in smart contracts, and human-centric computing. His work also addresses challenges in game development, mobile app optimization, and wearable health monitoring systems. Notable research areas include code readability assessment, machine learning applications in healthcare diagnostics, and the effectiveness of AI tools like GitHub Copilot. He has contributed to projects like QualAI (continuous quality improvement for AI systems) and 2Vita-B (cognitive and physical rehabilitation systems). His empirical studies often bridge academic research with real-world developer workflows, emphasizing practical applicability. Prof. Oliveto's recent work explores topics such as automated gameplay analysis for game debugging, detection of engagement issues in video games, and robust methods for identifying security vulnerabilities. He has also investigated Dockerfile quality, developer frustration metrics, and the ethical implications of AI in administrative document simplification.

Jack Mostowمشاهده پروفایل

استاد پژوهشی

• Educational Technology
• Artificial Intelligence
• Natural Language Processing
• +۳ مورد دیگر

Jack Mostow is a Research Professor affiliated with the Human-Computer Interaction Institute at Carnegie Mellon University. His work focuses on educational technology, artificial intelligence, and natural language processing. He is renowned for developing Project LISTEN's automated reading tutor that listens to children's oral reading, integrating speech recognition and machine learning to improve literacy. His research addresses challenges in child literacy, automated assessment, and the application of AI in education. Key contributions include advancing speech recognition accuracy for children’s voices, designing adaptive tutoring systems, and exploring EEG and visual features to gauge learning states. He has contributed to global education initiatives, such as the XPRIZE field study, and developed tools for iterative improvement of intelligent tutoring systems. His work emphasizes scalable educational technologies for under-resourced regions and data-driven approaches to enhance learning outcomes. Mostow’s publications span over two decades, addressing topics like reinforcement learning for instructional policies, semi-supervised affect perception, and difficulty-controllable question generation. His research bridges AI, education, and human-computer interaction, aiming to create systems that adapt to learners’ needs while advancing computational methods for educational analytics.

Yuting Chenمشاهده پروفایل

مدرس ارشد

• Contract Management
• Project Governance
• Dispute Resolution
• +۳ مورد دیگر

Dr. Yuting Chen is a Senior Lecturer at the University of Greenwich, School of Construction, Property, and Surveying. She holds a PhD in Construction Project Management, CFA certification, and a PGCert in International Business Law, with ongoing studies in Adjudication via RICS. Her roles include Deputy Head of School, Programme Leader for MSc Construction Project Management, and External Examiner at Regent's University London and the University of the West of Scotland. Education: PhD in Construction Project Management (2016–2021). Key qualifications include CFA, PGCert in International Business Law, and ongoing Diploma in Adjudication. Research Interests: Contract lifecycle analysis, including contract management, project governance, dispute resolution, and NLP-driven risk identification in construction contracts. Her work explores the interplay between contractual frameworks and trust in project outcomes, cultural influences on contract design, and digital tools for contract analysis. Grant and Funding: Secured £100,000 in research funding. Supervises 6 PhD students focusing on contract-related topics. Active in teaching innovation, invited to share methods at teaching conferences. Labs/Teams: Involved in interdisciplinary projects linking legal frameworks, technology (e.g., GIS, AI), and construction governance. Provides consulting and training in contract management, including FIDIC-certified courses.

• Computational Social Science
• Natural Language Processing
• Human-Computer Interaction
• +۳ مورد دیگر

Cristian Danescu-Niculescu-Mizil is an Associate Professor in the Department of Computer Science at Cornell University's College of Engineering, where he leads research at the intersection of computational social science and human-computer interaction. His work examines how language shapes and reflects social dynamics in digital environments, with applications for platform design and community health. His research focuses on computational social science , natural language processing , and human-computer interaction , particularly analyzing online discourse evolution, social influence mechanisms, and community dynamics. Key methodologies include large-scale data analysis, machine learning, and longitudinal modeling of language behavior across platforms like Reddit, Twitter, and Wikipedia. Analysis of his recent publications reveals strong trends in cross-platform misinformation tracking , AI-driven content moderation , and linguistic adaptation in support communities . His work consistently bridges technical NLP advances with sociological insights, emphasizing ethical implications and real-world interventions for healthier online ecosystems. Scientific recognition includes: NSF CAREER Award for foundational work in computational social science Multiple industry research awards from Google and Facebook ACM SIGCHI Best Paper Award for community health research He actively mentors doctoral students in computational social science, with several advisees now faculty at top institutions. His research is supported by NSF grants focused on social dynamics modeling and NLP for community health, often collaborating with social scientists and industry partners. Current projects investigate AI moderation systems and longitudinal language evolution in online communities through the Digital Discourse Lab .