جستجوی استاد راهنمای دانشگاهی

Andrew Zisserman is a Royal Society Research Professor at the University of Oxford's Department of Engineering Science, affiliated with the Visual Geometry Group (VGG). His research focuses on computer vision, artificial intelligence, and neural networks, with significant contributions to multimodal learning, video understanding, and 3D scene analysis. He leads projects exploring visual-language models, audio-visual synchronization, and clinical imaging applications. Key research areas include: Video analysis and temporal modeling Multimodal systems for sign language translation and action recognition 3D shape estimation and physical property inference Foundation models and cross-modal retrieval Recent work highlights: Developed Flamingo and Tapir models for video-language tasks Advancements in spinal MRI analysis and clinical imaging Leadership in EGO4D and VoxCeleb challenges Honors include Fellowship of the Royal Society (FRS) and the ISSLS Prize in Clinical Science 2023 for spinal analysis innovations. His lab collaborates globally, emphasizing real-world applications in healthcare and autonomous systems.

• Computer Vision
• Artificial Intelligence
• Machine Learning
• +۴ مورد دیگر

David Stillwell serves as Professor of Computational Social Science at Cambridge Judge Business School and Academic Director of The Psychometrics Centre, University of Cambridge. His research leverages big data to understand human psychology and behavior, with significant contributions in personality prediction from digital footprints and personalized advertising applications. His educational background includes: BSc in Psychology from the University of Nottingham (2007) MSc in Research Methods from the University of Nottingham (2008) PhD in Decision Making from the University of Nottingham (2012) Dr. Stillwell's research centers on computational social science and psychometrics, pioneering the myPersonality Facebook application that collected data from over 6 million users. His work demonstrates computers can predict personality as accurately as spouses, reveals psychological targeting's advertising effectiveness, and establishes links between personality-matched spending and life satisfaction. He also explores linguistic honesty markers through profanity analysis and personality-based dating patterns. His recent publications (2019-2025) reveal a strong trajectory toward AI evaluation using psychometric frameworks, particularly in medical and general-purpose AI assessment. Key themes include fairness metrics in language models, crisis emotional responses through social media, and computational personality recognition - demonstrating consistent innovation at the psychology-technology intersection. He has received significant recognition: Top 10 most influential papers of 2013 by Altmetric Nieman Journalism Lab highlight of 2013 Named in 'top 30 thinkers under 30' by Pacific Standard Magazine Dr. Stillwell maintains active industry engagement through consultancy with Barclays, Hilton, and Ubisoft on projects spanning computer-adaptive testing systems to interactive experiences like Predictive World for Watch Dogs 2. His policy impact is substantial, with citations by the European Data Protection Supervisor, World Bank, and multiple national governments, leading to speaking engagements at the European Parliament and Bank of England. As Academic Director of The Psychometrics Centre, he leads a global hub for advancing psychological assessment through innovative methods including Concerto open-source software, collaborating with organizations ranging from the European Commission to major corporations on psychometric applications in people analytics and digital behavior.

• Psychometrics
• Computational Social Science
• Big Data Analytics
• +۳ مورد دیگر

Dr. Oana Cocarascu is a Senior Lecturer in Artificial Intelligence at the Department of Informatics, Faculty of Natural, Mathematical & Engineering Sciences, King's College London. She holds a PhD and MEng in Computing (Artificial Intelligence) from Imperial College London and conducts applied research focusing on how artificial intelligence can be deployed to support real-world applications, with machine learning and natural language processing as core components of her work. Her research interests span argument mining, explainable AI, machine learning, natural language processing, and symbolic reasoning. She is particularly focused on developing AI systems that can provide transparent, accountable, and ethical decision-making processes. Her work addresses critical challenges in bias mitigation, fairness metrics, fact verification systems, and argumentation-based explanations for complex AI decisions. Analysis of her recent publications (2023-2025) reveals a strong focus on fairness in AI systems, with particular attention to individual fairness metrics and nuanced evaluation frameworks. She has made significant contributions to fact verification systems, especially in multimodal contexts involving charts and tabular data. Her work increasingly integrates argumentation theory with natural language processing to create explainable AI systems that can justify their decisions through structured reasoning. Dr. Cocarascu leads an EPSRC-funded project titled 'A framework for evaluating and explaining the robustness of NLP models' (2024-2027) and is actively involved in the Natural Language Processing Group at KCL. Her research fingerprint shows strong activity in argumentation (100%), decision-making (74%), artificial intelligence (50%), explainable AI (39%), and bias mitigation (35%). She has contributed to numerous high-impact publications in top venues including ACL, EMNLP, AAAI, and the Journal of Artificial Intelligence Research, with a particular focus on making AI systems more transparent, accountable, and aligned with human values. Her work intersects with UN Sustainable Development Goals, particularly those related to reducing inequality and building resilient infrastructure.

• Argument mining
• Explainable AI
• Machine learning
• +۵ مورد دیگر

Jose Apesteguia is an ICREA Research Professor at the Department of Economics and Business, Universitat Pompeu Fabra, Barcelona, Spain. His research focuses on behavioral economics, decision theory, experimental economics, and game theory, with particular emphasis on topics such as behavioral heterogeneity, rationality measures, stochastic choice models, and social preferences. Apesteguia has collaborated extensively with scholars like Miguel A. Ballester and Jörg Oechssler, producing influential work on topics ranging from imitation dynamics to the impact of language on moral decisions. His research integrates theoretical frameworks with experimental methods, exploring how individuals make decisions under uncertainty, time preferences, and social contexts. Key contributions include the development of measures of rationality and welfare, as well as analyses of behavioral adaptation and the role of information in competitive environments. His work frequently bridges economic theory with empirical validation, addressing real-world issues such as rule compliance in public institutions and team performance in organizations. Apesteguia’s publications span top journals including the American Economic Journal: Microeconomics , Journal of Economic Theory , and Econometrica . He teaches advanced courses on bounded rationality and behavioral decision theory at the undergraduate and graduate levels. His research has been applied to fields like finance (e.g., copy trading behavior) and public policy (e.g., promoting compliance in libraries).

• Behavioral Economics
• Decision Theory
• Game Theory
• +۸ مورد دیگر

Michael O'Boyle is a Professor at the University of Edinburgh's School of Informatics, where he serves as Director of the ARM Research Centre of Excellence and the EPSRC Centre for Doctoral Training in Pervasive Parallelism. Holding an EPSRC Established Career Research Fellowship, he leads pioneering work in compiler technology for heterogeneous architectures, bridging theoretical advances with practical high-performance computing applications. Professor O'Boyle's research spans multiple cutting-edge areas including heterogeneous code discovery and optimization, neural machine translation for program synthesis, deep neural network system stack optimization, software-defined hardware, and compiler/architecture co-design. His approach integrates constraint analysis, program synthesis, and machine learning to address complex challenges in high-performance computing across diverse hardware platforms. His recent publications reveal a strong trend toward integrating machine learning with traditional compiler techniques, particularly in neural program synthesis, tensor optimization, and architecture-aware compilation. This work represents a paradigm shift in compiler design, moving from rule-based systems to learning-based approaches that can automatically adapt to diverse hardware targets. IEEE/ACM CGO 2025 Distinguished Paper Award for 'Tensorize: Fast Synthesis of Tensor Programs from Legacy Code' IEEE/ACM CGO 2024 Test of Time Award ACM GPCE 2023 Best Paper Award for 'C2TACO: Lifting Tensor Code to TACOM' ACM ASPLOS 2021 Distinguished Paper Award IEEE HPCA 2021 Best Paper Award for 'Prodigy: Improving the Memory Latency of Data-Indirect Irregular Workloads' Professor O'Boyle has successfully mentored numerous PhD students who have secured prominent positions in academia (including at Cambridge, Edinburgh, Leeds, and McGill) and industry (including Meta, NVIDIA, Qualcomm, Huawei, and Microsoft). His research is supported by significant funding from EPSRC, ARM, and European projects including Bonseyes and Transmuter, demonstrating strong international recognition and industry impact. He leads the influential Compiler and Architecture Design (CArD) Group at the University of Edinburgh and is a founder of the HiPEAC Network of Excellence, which has grown into a major European initiative connecting researchers and practitioners in high-performance and embedded computing.

• Heterogeneous Code discovery and Optimisation
• Neural Machine Translation and Neural Synthesis
• Deep Neural Network system stack
• +۷ مورد دیگر

Mark Gales is Professor of Information Engineering at the University of Cambridge and an Official Fellow at Emmanuel College. He is currently on sabbatical leave for the 2024/25 academic year. Prior to his academic career, he worked as a consultant at Roke Manor Research Ltd, developing radar systems, before transitioning to speech and language processing. PhD in 'Model-Based Techniques for Robust Speech Recognition' (University of Cambridge, 1995) BA in Electrical and Information Sciences (University of Cambridge, 1988) His research focuses on speech and language processing , particularly in automated language assessment and low-resource speech technology . He leads the Automated Language Teaching and Assessment (ALTA) Institute , which collaborates with Cambridge University Press & Assessment (CUP&A) to develop commercial tools like Linguaskill and Speak & Improve . These platforms provide automated spoken/written assessment for millions of users globally. Recent publications highlight his work in LLM-driven speech processing , including adversarial attacks on foundation models, end-to-end spoken error correction, and uncertainty estimation frameworks. His team's research spans multilingual capabilities, with deployments in languages ranging from Dholuo to Tok Pisin . Awards : IEEE Fellow, ISCA Fellow Leadership : Fellows' Steward at Emmanuel College Mark has contributed extensively to Hidden Markov Model (HMM) applications in speech recognition, which underpinned early automatic speech systems. His work now bridges LLM-based language assessment with cross-lingual transfer learning and robustness testing for real-world deployments.

• Speech Processing
• Language Assessment
• Natural Language Processing
• +۳ مورد دیگر

Rogério de Lemos is a Senior Lecturer in Computing Science and Director of Postgraduate Research (PGR) at the School of Computing, University of Kent. He previously served as an invited assistant professor at the University of Coimbra, Portugal, and as a Senior Research Associate at the Centre for Software Reliability (CSR) at the University of Newcastle upon Tyne, UK. Dr. de Lemos' research focuses on architecting resilient systems, particularly in resilient AI, self-adaptive software systems, and authorization infrastructures. He belongs to both the Programming Languages and Systems Group and the Cyber Security Group at the University of Kent. His specific research interests include: Software engineering for self-adaptive systems assurances and resilience evaluation Dynamic generation of processes Handling insider threats using self-adaptive authorization Architectural abstractions for fault tolerance Verification and validation of dependable software architectures Software development for safety-critical systems Dependability and bioinspired computing His publication trends show increasing emphasis on practical applications of self-adaptive systems in cyber security contexts, with recent work spanning network traffic analysis, cryptographic function detection, and cloud-edge security architectures. His research bridges theoretical foundations with practical implementations, particularly in cyber security and resilient systems architecture. Dr. de Lemos currently leads the "Collaborative and Confidential Information Sharing and Analysis for Cyber Protection" project funded by the European Union's Horizon 2020 Programme. His past projects include "ADAAS: Assuring Dependability in Architecture-based Adaptive Systems" and multiple collaborations with NCR on sensor fusion and fault tolerance. As Director of Postgraduate Research, he oversees the School of Computing's research degree programs and likely supervises PhD students in resilient systems and cyber security, though specific student names are not listed in the available information.

• Resilient AI
• Self-adaptive software systems
• Authorisation infrastructures
• +۷ مورد دیگر

Professor Sandra Wachter is a leading academic in legal and ethical implications of AI, Big Data, and robotics at the Oxford Internet Institute (OII) , University of Oxford, and as Humboldt Professor at the Hasso Plattner Institute. She leads the OII's governance of emerging technologies (GET) research programme , focusing on AI regulation, algorithmic bias, and human rights. Affiliations : Berkman Klein Center (Harvard University), World Economic Forum, UNESCO, IEEE, World Bank, Bonavero Institute of Human Rights, Oxford Martin School, and more. Research : Legal and ethical frameworks for AI, explainability (notably Counterfactual Explanations ), fairness metrics, and combating algorithmic discrimination through her Conditional Demographic Disparity (CDD) tool. Awards : Alexander von Humboldt Foundation Research Award (2025), O2RB Excellence in Impact Award (2021, 2018), Computer Weekly Women in UK Tech (2021), Privacy Law Scholar (2019), CognitionX Outstanding Achievements (2023, 2017). Impact : Her work is implemented by Google, IBM, Amazon, and Microsoft; influences NHS and MHRA policies; and has been cited in major media outlets including The New York Times, BBC, and Nature.

• Data Ethics
• Artificial Intelligence
• Big Data
• +۹ مورد دیگر

Arthur Gervais is a Professor of Information Security at University College London's Department of Computer Science. His work focuses on blockchain systems, smart contract security, and decentralized finance (DeFi) risk analysis. He has published extensively on topics ranging from privacy technologies to systemic vulnerabilities in financial cryptography. Research Interests: Gervais investigates security challenges in blockchain ecosystems, including censorship mechanisms, zero-knowledge proofs, and DeFi liquidation risks. His interdisciplinary approach bridges computer science, cryptography, and financial systems. Publications Trends: Recent articles emphasize empirical studies of DeFi attacks, hybrid fuzzing for smart contract verification, and privacy trade-offs in blockchain mixers. His work spans conferences like ACM SIGMETRICS, IEEE Security & Privacy, and World Wide Web Conference.

• Blockchain Security
• Smart Contracts
• Decentralized Finance (DeFi)
• +۳ مورد دیگر

Aybars Tuncdogan is a Reader in Digital Innovation and Information Security at King’s Business School, King’s College London. He holds affiliations with the King’s AI Institute, King’s Cybersecurity Centre (Informatics), and King’s Cybersecurity Group (War Studies). A Fellow of the Higher Education Academy, he also serves on the editorial review board of Industrial Marketing Management . Education : PhD in Management, Rotterdam School of Management, Erasmus University MPhil in Business Research (Distinction), Erasmus University Bachelor’s in Business Management & Computer Science (Honors), Earlham College Research Interests : His work focuses on three pillars of digital innovation: generation (crowdsourcing, AI), marketing (digital brand personality, sales ambidexterity), and protection (information security, corporate espionage). He integrates psychology (individual differences, social identity) and computer science (machine learning/AI) frameworks. Publications Trends : Recent work addresses cybersecurity challenges in retail, AI ethics in healthcare, and interdisciplinary innovation. He frequently publishes in top-tier journals like Journal of Management and Scientific American , blending academic rigor with practitioner impact. Awards & Contributions : 2015 Best Paper Award (shared) Edited books including Oxford Handbook of Individual Differences and Strategic Renewal Teaching & Pedagogy : Develops innovative teaching methods like inquiry-based learning to foster student creativity. Taught modules on digital marketing, consumer behavior, and research methods. Labs/Teams : Contributes to cybersecurity initiatives at King’s, focusing on AI-driven defense mechanisms and organizational cyber resilience strategies.

• Digital Innovation
• Information Security
• Marketing Strategy
• +۳ مورد دیگر

Nora Uglik-Marucha is an NIHR Doctoral Research Fellow at King’s College London’s Department of Biostatistics & Health Informatics, affiliated with the Institute of Psychiatry, Psychology & Neuroscience. Her work focuses on autism in women and misophonia through advanced psychometric methodologies. She holds MSc and BSc degrees in Clinical Neuropsychiatry and Psychology from King’s College London. Research interests include gender bias in autism screening tools, measurement invariance analysis, and questionnaire development. Her doctoral project develops novel autism assessment tools for women under Dr. Silia Vitoratou and Prof. Francesca Happé. Key contributions include the S-Five tool for misophonia assessment and validation studies across cultures. She has published on misophonia mechanisms, cross-cultural measurement robustness, and autism screening equity.

• Autism in women
• Psychometrics
• Questionnaire development
• +۴ مورد دیگر

Sharon Abrahams is a Professor of Neuropsychology and holds a Personal Chair at the University of Edinburgh's School of Philosophy, Psychology and Language Sciences. She leads research in clinical and experimental neuropsychology, focusing on neurodegenerative diseases like motor neurone disease/ALS and frontotemporal dementia. Her work integrates neuroimaging, cognitive assessment, and clinical intervention. She is affiliated with the Euan MacDonald Centre for Motor Neurone Disease, the Centre for Clinical Brain Sciences, and Edinburgh Neuroscience. Current PhD students include Monica de Icaza Valenzuela, Debbie Gray, and Caroline McHutchison. Abrahams has secured over 17 research grants since 2008, including projects on cognitive screening in MND, apathy impact, and the ECAS tool. Her research emphasizes cognitive and behavioral changes in ALS, with a focus on early detection, staging, and patient quality of life. Notable contributions include the Edinburgh Cognitive and Behavioural ALS Screen (ECAS), validated across multiple languages and populations.

• Clinical Neuropsychology
• Neuroimaging
• Neurodegenerative Diseases
• +۴ 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.

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

Professor Emma Moore is a leading sociolinguist at the School of English, University of Sheffield . Specializing in the social dimensions of language, her work integrates methodologies from anthropology and sociology to investigate how linguistic variation constructs identity and social affiliations. Research focus: Sociolinguistic style, dialect contact, youth language, identity negotiation, and community-based fieldwork Key projects: Adolescence and grammar (1999-), Isles of Scilly dialect (2008-), language and inequality (2014-), language perception software (2016-) Educational background : PhD in Sociolinguistics, University of Manchester Stanford University (USA) during PhD research Research trends across her 2021-2025 publications reveal interdisciplinary exploration of: Socio-syntactic variation Clinical linguistics (2025 MDS-UPDRS studies) Digital discourse post-pandemic Indexicality and cognitive representations Dialect contact in insular communities Educational policy implications Scientific recognition : British Academy Mid-Career Fellow (2019-2020) Elected Fellow, Royal Anthropological Institute (2014) AHRC/BA funded research projects (1999-2015) Research group leadership : Mentored 9 PhD students (2004-2024) and supervised 3 undergraduate SURE projects, including analyses of: Gender in rap performance Language style and workplace inequality Oral history digitization Professional contributions : Editorial Board: Language in Society (2015-), Gender and Language (2011-2017) External Examiner: Lancaster University MA in English Language (2013-2017) Collaborative software development for dialect perception testing

• Sociolinguistics
• Syntax
• Language Variation
• +۱۲ مورد دیگر

Cecilia Mascolo is a Professor of Mobile Systems at the University of Cambridge , specifically in the Department of Computer Science and Technology . She co-directs the Centre for Mobile, Wearable System and Augmented Intelligence and is a Fellow of Jesus College, Cambridge . Her research focuses on mobile systems , machine learning for mobile health , and earable technology . She has been awarded prestigious grants such as the ERC Advanced Research Grant (2019-2025) and the EPSRC Open Research Fellowship (2025-2030). Currently on sabbatical at Harvard University , her work bridges systems and machine learning for health applications. Education: PhD in Computer Science from the University of Bologna, Italy. Previous Affiliation: Faculty at University College London before 2008. Her research spans mobile and wearable systems for health and behavior monitoring, focusing on on-device machine learning , uncertainty-aware models , and audio-based diagnostics . Key areas include federated learning , edge computing , and respiratory disease progression analysis via wearables. She explores earable technology for physiological monitoring, gait analysis, and even toothbrushing tracking using in-ear sensors. Her recent publications highlight advancements in earable-based health monitoring , including heart rate estimation , respiratory rate detection , and ECG analysis using machine learning. She emphasizes longitudinal health data from consumer devices, advocating for scalable diagnostics beyond traditional clinical standards. Scientific Awards: ERC Advanced Research Grant EPSRC Open Research Fellowship Best Paper Award - IEEE Percom 10-Year Impact Award - ACM Ubicomp Computer Laboratory Ring Hall of Fame Best Paper Award Student: Andrea Ferlini - ACM SIGMOBILE Doctoral Dissertation Runner-up She leads the Mobile Systems Research Laboratory , mentoring a team of 15 researchers (postdocs and PhD students), and has graduated over 25 PhD students. Her teaching includes Mobile Health courses at the University of Cambridge, and she serves as Director of Studies for Computer Science at Jesus College.

• Mobile Systems
• Wearable Computing
• Machine Learning
• +۵ مورد دیگر