Shimon Whiteson is Professor of Computer Science at the University of Oxford, leading the Whiteson Research Lab focused on reinforcement learning, multi-agent systems, and deep learning. His research develops algorithms for efficient learning in complex environments. Current work explores meta-reinforcement learning frameworks that enable agents to rapidly adapt to new tasks, with applications in autonomous driving simulation and robotics. Recent innovations include novel methods for offline reinforcement learning, multi-agent coordination, and morphology-aware control. Publications demonstrate advances in: Meta-RL algorithm design for few-shot adaptation Multi-agent reinforcement learning environments and benchmarks Imitation learning in autonomous driving Bayesian methods for sample-efficient learning Research outputs include widely used benchmarks and tools including JaxMARL for accelerated multi-agent RL research. Current doctoral supervision focuses on temporal abstraction in RL, multi-agent coordination, and reinforcement learning theory.
Professor Hutan Ashrafian is a clinician-scientist and surgeon at the University of Leeds Business School, holding dual roles as Professor of Research Impact and Senior Research Fellow at Imperial College London. His expertise spans AI in healthcare, metabolic surgery, and ancient history. He pioneered STARD-AI and QUADAS-AI guidelines for AI diagnostics, collaborated on AI-driven breast cancer screening with Google and NHS, and led global health policy initiatives. Ashrafian’s work bridges medicine, history, and philosophy, including his contributions to understanding historical figures’ medical conditions, such as King Tutankhamun’s epilepsy. He has authored over 550 publications, 12 books, and holds a PhD in computational physiology and an MBA with distinction. Awards include the Hunterian Prize and Wellcome Trust Fellowship. His research also explores AI ethics, quantum physics paradoxes, and art-based medical diagnostics. Education: PhD in Computational Physiology (Imperial College London) MBA (Warwick Business School) MD (University College London) Bachelor of Science in Immunology (University College London) Research Interests: Ashrafian’s work spans: AI in Medicine: Diagnostic algorithms, guideline development (STARD-AI/QUADAS-AI), and ethical frameworks. Metabolic Surgery: Bariatric interventions, gut microbiome, and obesity treatments. Ancient History: Medical analyses of historical figures (e.g., Tutankhamun, Julius Caesar) and art-based pathology identification. Philosophy: AI rights (AIONAI law), temporal paradoxes, and the Simulation Argument. Awards: Royal College of Surgeons Arris and Gale Lectureship Hunterian Prize Wellcome Trust Research Fellowship Advising & Innovation: Supervised >50 PhD students, co-founded Oxford Medical Products (weight loss tech), and serves as CSO at Flagship Pioneering’s Preemptive Health division. He advises on NHS digital transformation and global health policy. Labs/Teams: Leads AI initiatives at Imperial’s Institute of Global Health Innovation and collaborates with Google, NICE, and international institutions on health tech solutions.
Simon King is a Professor of Speech Processing at the University of Edinburgh , affiliated with the School of Philosophy, Psychology and Language Sciences . He serves as Director of the Centre for Speech Technology Research (CSTR) and teaches courses like Speech Processing and Speech Synthesis , while directing the MSc in Speech and Language Processing . Research Interests His research focuses on: Developing new acoustic models (e.g., Linear Dynamical Models, factorial-HMMs) for speech recognition Advancing unit selection and HMM-based speech synthesis Integrating articulatory measurement data for enhanced modeling Exploring perceptual measures in synthesis criteria Building multilingual speech systems to identify universal speech building blocks Publication Trends Simon's recent work emphasizes deep learning (DNNs, LSTMs) in speech synthesis, multilingual frameworks , and articulatory-acoustic feature integration . His studies often bridge grapheme-based modeling , perceptual error reduction , and noise-robust synthesis . Scientific Awards EPSRC Advanced Research Fellowship (2005-2009) Students & Collaborations He has supervised numerous PhD students including Rasmus Dall, Tom Merritt, and Srikanth Ronanki. Current research fellows like Mirjam Wester and Zhizheng Wu contribute to projects such as Natural Speech Technology (NST) and Simple4All .
Professor Chris Holmes is a Professor of Biostatistics at the University of Oxford, where he moved from Imperial College London in February 2004. He is a Fellow at St Anne's College and works in the Department of Statistics. His research focuses on applications and statistical methods development in genomic sciences and genetic epidemiology, holding a prestigious Programme Leaders Grant in Statistical Genomics from the Medical Research Council. Prior to his position at Oxford, Professor Holmes completed his doctorate in Bayesian statistics at Imperial College London, investigating novel nonlinear pattern recognition methods. This was followed by a post-doctoral position and then a lectureship at Imperial. Before his academic career, he worked in industry for several years in scientific computing, developing techniques for real-time pattern recognition models in defense and SCADA systems. Professor Holmes has a broad interest in the theory, methods and applications of statistics and statistical modeling, with a particular foundation in Bayesian statistics which he views as providing a unified framework for stochastic modeling and information processing. His specific research interests include: Bayesian statistics and stochastic simulation Markov chain Monte Carlo methods Pattern recognition and nonlinear, nonparametric methods Spatial statistics Statistical genetics and genomics Genetic epidemiology His recent publications (2023-2025) demonstrate a strong focus on the intersection of biostatistics, artificial intelligence, and healthcare applications. His work spans multiple domains including AI-driven disease classification in neurology, genomic data analysis for health equity, machine learning tools for healthcare prediction, and addressing bias in medical AI systems. A notable trend across his research is the application of advanced statistical methods to solve pressing problems in genomics, epidemiology, and medical diagnostics, with an increasing emphasis on health equity and the ethical implications of AI in healthcare. Professor Holmes currently supervises PhD students Oscar Clivio, Sahra Ghalebikesabi, and Natalia Garcia Martin. His research is supported by multiple grants, including the MRC Programme Leaders Grant in Statistical Genomics which funds his work in statistical genomics. He is actively involved in three research groups at Oxford that reflect the breadth of his scholarly interests: Computational Statistics and Machine Learning Statistical Genetics and Epidemiology Statistical Theory and Methodology
Professor Anders C. Hansen is a mathematician at the University of Cambridge and University of Oslo, leading the Applied Functional and Harmonic Analysis group. His work bridges functional analysis, artificial intelligence, and computational mathematics, focusing on the Solvability Complexity Index (SCI) hierarchy and stability issues in deep learning. He has held prestigious fellowships, including a Royal Society University Research Fellowship and Peterhouse Bye-Fellowship. Educated at the University of Cambridge, UC Berkeley, and the Norwegian University of Science and Technology Developed groundbreaking theories in compressed sensing and deep learning, revealing algorithmic instability paradoxes Organized workshops on computational mathematics and AI interpretability His research explores the SCI hierarchy , exposing computational barriers in AI, quantum mechanics, and inverse problems. Key projects include Smale’s 18th problem and analyzing neural network stability. His work has transformed understanding of compressed sensing, particularly in medical imaging. Recent scientific awards include the Whitehead Prize (2019), IMA Prize (2018), and Leverhulme Prize (2017). Collaborations span institutions like Caltech, MIT, and the University of Vienna. As an educator, he teaches NST Part IA Mathematical Methods , Part II Numerical Analysis , and a Part III course on Compressed Sensing . His group has mentored 17 PhD and postdoctoral researchers since 2012.
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.
Dr Luke Garrod is a Senior Lecturer in Economics at Loughborough University's Loughborough Business School. He holds a PhD, MPhil, and BA from the University of East Anglia. His research focuses on industrial organization, competition policy, consumer policy, and behavioral economics, with a particular emphasis on modeling firm incentives in imperfectly competitive markets. He received the International Journal of Industrial Organization Best Theoretical Paper Award 2019 for his work on collusion mechanisms. His book on hub-and-spoke cartels provides critical insights into antitrust enforcement strategies. Teaching responsibilities include Principles of Microeconomics (ECA002) and Industrial Economics (ECC005). He serves as an Associate Editor for the International Journal of the Economics of Business and contributes to economic consultancy through his role at Economic Insight. His research has explored topics such as cartel damages quantification, digital market regulation, and the interplay between consumer protection and competition policies. Key awards include the 2019 Best Theoretical Paper Award, reflecting his contributions to advancing antitrust and competition policy frameworks. His work bridges theoretical economic modeling with practical regulatory applications, addressing emerging challenges in global competition dynamics and digital economy policies.
Andreas Vlachos is a Professor of Natural Language Processing and Machine Learning at the Department of Computer Science and Technology, University of Cambridge, and holds the Dinesh Dhamija Fellowship at Fitzwilliam College. His research spans dialogue modeling, automated fact-checking, imitation learning, semantic parsing, biomedical text mining, and trustworthiness in AI systems. PhD in Computer Science, University of Cambridge (supervised by Ted Briscoe and Zoubin Ghahramani) Lecturer at University of Sheffield Postdoctoral roles at UCL, University of Cambridge (NLIP group, Stephen Clark), and University of Wisconsin-Madison (Mark Craven) Current research focuses on evaluating and mitigating biases in language models, advancing fact-checking methodologies, and improving model robustness through interpolation, reinforcement learning, and causal reasoning. His work integrates natural logic, knowledge graphs, and multimodal evidence for verification tasks. Recent publications address uncertainty quantification, temporal planning benchmarks, and ethical framing of NLP artifacts. Grants from ERC, EPSRC, Facebook, Google, and the Alan Turing Institute fund his research team. Collaborations include Sebastian Riedel, Stephen Clark, and Mark Craven. Key projects explore disinformation detection, long-form generation, and confidence calibration in AI systems.
Professor Andrew Murray is a leading academic in Law with expertise in New Media and Technology Law. He holds the position of Professor of Law at the LSE Law School and directs the LSE Law, Society and Technology Group. His research focuses on digital rights, AI ethics, and regulatory frameworks for emerging technologies. Murray has held roles including Fellow of the Royal Society for the Arts and advisor to the Saudi Arabian government on e-commerce law. He has advised parliamentary committees, including the House of Lords Communications Committee on digital regulation, and delivered the prestigious TMC Asser Lecture on AI and human agency. Education: LL.B. Hons from Edinburgh University (1994), followed by academic roles at Stirling University and LSE since 2000. Professional memberships include the Society of Computers and Law (SCL) and the Higher Education Academy (HEA). He has been a visiting professor at Amsterdam Law and Technology Institute and Sciences Po Paris. Research interests span cyberspace regulation, AI governance, and the intersection of technology with human rights. Key publications include Human Rights in the Digital Age (2004) and The Regulation of Cyberspace (2007). Awards include recognition as an Independent Expert in Nominet UK dispute resolution (2001–2008) and a 2024 Leibniz Prize reviewer. Advocacy includes contributions to EU e-commerce directives and UK surveillance law debates. His work emphasizes balancing innovation with legal accountability in digital spaces.
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.
Malcolm McCulloch serves as Professor of Energy Systems and Group Leader of the Energy and Power Group within the Department of Engineering Science at the University of Oxford. He also holds the position of Co-Director for the Oxford Martin Programme on Integrating Renewable Energy and maintains affiliation with Christ Church college. His research spans four primary domains: domestic energy systems, electric vehicle technology, renewable generation, and energy solutions for developing regions. McCulloch's research focuses on practical energy transition challenges. His domestic energy work develops user-centric demand side management technologies and behavior change interventions, leading to the spin-out Intelligent Sustainable Energy (now Navetas Energy Management). In transportation, he pioneered the Morgan LifeCar hydrogen sports car project, resulting in high-efficiency motors and the Oxford Yasa Motors spin-out. His renewable generation research includes lightweight tidal turbines through Kepler Energy, while his Energy for Development work creates nano/micro grid solutions for distributed electrification. Analysis of his recent publications reveals a strong emphasis on integrating variable renewables through innovative market mechanisms, grid flexibility solutions, and electric vehicle integration. His work consistently addresses the technical and economic barriers to decarbonization, with increasing focus on peer-to-peer energy trading, thermal storage, and climate-resilient cooling solutions since 2020. McCulloch previously served as Co-Director of the Institute for Carbon and Energy Reduction in Transport (2008-2013) under the Oxford Martin School. His leadership extends to creating the Integrated Transport Network for Oxford and developing practical applications through multiple successful spin-out companies that bridge academic research and commercial implementation.
Professor Elaine Fahey is a leading scholar in EU law and global governance at the City Law School, City St George's, University of London, where she serves as Professor of EU Law and Deputy Head of Department (academic programmes). She is co-convener of the Institute for the Study of European Law (ISEL) and the UACES James Madison Trust EUFUtures initiative (2022–2025). Her academic career includes visiting professorships at Washington College of Law (American University), Keio University, and NYU, as well as fellowships at the European University Institute and the University of Graz. LLB, Trinity College Dublin LLM, Sidney Sussex College, University of Cambridge PhD, Trinity College Dublin Barrister-at-Law, Honorable Society of King’s Inns, Ireland Attorney-at-Law, State of New York Senior Fellowship, Higher Education Authority UK Her research focuses on the intersection of EU law with global governance, digital regulation, transatlantic relations, and the Area of Freedom, Security and Justice. She explores how the EU navigates legal frameworks beyond the nation-state, particularly in digital trade, cybersecurity, and data protection. Her work critically examines the EU’s role as a global regulatory actor and its interactions with international institutions. Her extensive publication record includes the monograph The EU as a Global Digital Actor (Hart, 2022) and numerous articles on digital sovereignty, data transfers, and transatlantic cooperation. Recent research analyzes the EU–US Trade and Technology Council (TTC), the evolution of the Privacy Shield, and strategic litigation in digital rights. Her work reveals a strong trend toward understanding how soft law, institutional design, and judicial decisions shape EU external relations and digital governance. Erasmus+ Jean Monnet Chair in Law & Transatlantic Relations (2019–2022) Emile Noël Fellow, NYU Law School Max Weber Fellow, European University Institute Senior Land Steiermark Fellow, University of Graz Senior Fellowship, Higher Education Authority UK Professor Fahey has supervised multiple PhD students, including Isabella Mancini, Giulio Kowalski, and Christos Karetsos, on topics such as algorithmic collusion, digital markets, and investment law. She has led significant research projects, including the ESRC-funded TRILATTRADE grant and the Marie Curie ITN on EU and Transatlantic Investment and Trade (EUTIP). She previously held leadership roles as Associate Dean (International) and interim Associate Dean (Research) at the City Law School. She is an elected member of the EU Studies Association (EUSA) Executive (2021–2025). She has also contributed to public policy through briefings for the Welsh Parliament and reports on CJEU litigation in Ireland. She is associated with research initiatives such as the Institute for the Study of European Law (ISEL) and has collaborated on interdisciplinary projects on Facebook regulation, transatlantic relations, and EU technological sovereignty. Her work bridges legal scholarship, policy, and international academic collaboration.
Professor Siân Bayne is a leading academic in digital education at the University of Edinburgh , where she serves as Assistant Principal for Education Futures and directs the Centre for Research in Digital Education . Her work bridges critical theory and practical innovation in higher education. Interdisciplinary research on digital education and futures studies Leadership in the Edinburgh Futures Institute and Moray House School of Education and Sport Global impact through UNESCO collaborations and UKRI GCRF projects Bayne’s research explores higher education futures , utopian theory , and digital enhancement , with a focus on: AI’s role in teaching and learning Ethical implications of educational technologies Anonymous social media in academic spaces Speculative scenarios for educational systems Global South digital education models Augmented reality applications in assessment Her 15 most recent publications span 2017-2025 , covering critical perspectives on: Generative AI and educational innovation Utopian design in universities Data governance in learning analytics Augmented reality pedagogy Digital cultural heritage Scientific recognition includes: IASH Sabbatical Fellowship (2023) Bayne leads Higher Education Futures initiatives and partners with institutions worldwide, including: UNESCO Global Education and Technology Report World Bank collaborations European university leadership programs She also drives major research centers like: Centre for Research in Digital Education UKRI GCRF Urban Disaster Risk Hub
Professor Carlo Harvey is a creative technologist at the School of Digital Arts (SODA), Manchester Metropolitan University. His interdisciplinary research merges games , machine learning , virtual production , and cultural heritage reinterpretation . He leads industry collaborations with entities like Jaguar Land Rover and Epic Games, focusing on AI-driven interactive audio, real-time visualization, and accessibility solutions. Award-winning projects : TIGA, Innovate UK, and Epic Games MegaGrant for Accession Industry partnerships : Automotive sector, cultural institutions His research spans human-computer interaction , multisensory virtual environments , and acoustic-visual cross-modal perception . Recent publications address robotic simulations, motion alignment, and haptic feedback systems. Scientific recognition : TIGA Award, Innovate UK Funding, Epic Games MegaGrant Advocacy : Digital inclusion, creative collaboration, social impact of technology
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.
