Michael A Osborne is Professor of Machine Learning at the University of Oxford and leads the Bayesian Exploration Lab . He serves as Director of the EPSRC Centre for Doctoral Training in Autonomous Intelligent Machines and Systems and co-directs the Oxford Martin AI Governance Initiative. His research focuses on Bayesian optimization, Gaussian processes, and probabilistic numerics with applications in quantum devices, battery modeling, and AI governance. Key Positions: Professor of Machine Learning, University of Oxford Official Fellow, Exeter College Co-founder of Mind Foundry Lead Researcher, Oxford Martin Programme on Technology and Employment Research Themes: Probabilistic modeling for quantum systems Uncertainty quantification in energy storage AI safety and societal impact analysis Automated experimental design Quantum device calibration Probabilistic numerical methods Technical Contributions: Bridging reality gap in quantum devices Efficient Bayesian quadrature techniques Personalized neurostimulation algorithms Automated measurement protocols Quantum-classical hybrid ML
Professor Rebecca Lawson is a Professor of Neuroscience and Computational Psychiatry at the University of Cambridge, affiliated with the Department of Psychology and Bye-Fellow at Peterhouse College. Her research focuses on understanding how humans learn to make predictions under uncertainty, with applications to mental health conditions such as anxiety and depression. She leads the Prediction and Learning (PaL) Lab, which combines computational modeling, neuroimaging (e.g., 7T MRI), and behavioral experiments to study cognitive processes in typical and atypical populations. Key research interests include computational psychiatry, autism spectrum disorders, neuroimaging techniques, and the neurochemical basis of learning mechanisms. She has received significant funding, including a £4.3m Wellcome Mental Health Award and the Sir Henry Dale Fellowship. Notable contributions include advancing theories of neural gain and sensory expectations in autism, as well as studies on uncertainty processing in anxiety and depression. Professor Lawson holds academic awards such as the BNPA Lishmann Prize and the BAP Psychopharmacology Award. She actively contributes to public engagement, including initiatives like Knit-a-Neuron and involvement with PrideinSTEM. Her lab collaborates internationally, with projects like the CamRAA study investigating autism-anxiety overlaps and the Chemical and Brain Basis of Uncertainty (CBBU) study exploring pharmacological interventions. Education: PhD in Cognitive Neuroscience (University of Cambridge), BA (Hons) Psychology & Philosophy (University of Glasgow). Grants: £4.3m Wellcome Award, Parke-Davis Fellowship, Lister Institute Prize. Labs/Teams: Principal Investigator of the PaL Lab; collaborations with MRC Cognition and Brain Sciences Unit, Yale University, and Brown University.
Johnny Golding is a Professor at the Royal College of Art (RCA), School of Arts & Humanities. His career spans roles such as Director of the Centre for Fine Art Research at Birmingham City University, Professor of Philosophy in the Visual Arts & Communication Technologies (2000–2012), and honorary Professorship in Philosophy and Imaging at Dundee School of Art (2009). Born in New York, he holds a PhD from the Universities of Toronto and Cambridge. Education : - PhD in Philosophy from the Universities of Toronto and Cambridge. - Earlier studies in Toronto and New York. Research Interests : Golding’s work explores post-Newtonian analytics, new materialisms, and the erotics of sense as 'radical matter.' His interdisciplinary approach bridges art, philosophy, and 'wild sciences' like AI, robotics, and quantum theory. Key themes include data proliferation's societal impact, emergent systems, and the interplay between art and technology. Recent Articles & Projects : Focus on Data Loam (2020), exploring future knowledge systems through art and science collaborations. Recent works address radical empathy, distributed intelligence, and the ethics of AI. His 2018 opera Entanglement: The Opera and installations like Of The Thick and the Raw exemplify his practice-led philosophy. Grants & Leadership : - Led the Data Loam project (FWF-PEEK funded), involving over 20 artists and scholars. - PI for AiDesign Labs on generative AI at RCA. Labs & Collaborations : - Radical Matter Lab (2017–2018), a pedagogical experiment at RCA. - Collaborations with institutions like the University of Applied Arts Vienna and the British Library.
Professor Andrew Hudson-Smith is the Director of the Bartlett Centre for Advanced Spatial Analysis (CASA) at University College London (UCL), where he holds the title of Professor of Digital Urban Systems. He leads UCL's academic and applied research in smart cities, digital twins, and urban informatics. His roles include Editor-in-Chief of the Future Internet Journal and academic lead for the Smart Queen Elizabeth Park project. He contributes to strategic initiatives such as the Greater London Authority Smart London Board and EPSRC Digital Economy Programme Advisory Board. Education: PhD (2003), MSc (1996) from UCL; BSc in Geography from the University of Plymouth (1992). Research focuses on digital urban systems, IoT applications, sustainable urban planning, and cyberphysical systems. Notable projects include urban heat island monitoring, participatory planning platforms, and metaverse-driven urban design. His work bridges technology, art, and public engagement, exemplified by initiatives like Tales of Things and the Haggle-O-Tron. Recent publications emphasize digital twins, metaverse urbanism, and IoT integration in urban environments. Awards include a Fellowship of the Royal Society of Arts. His work addresses SDGs 3 (Good Health) and 11 (Sustainable Cities), with a focus on equitable smart city development and public space innovation.
Professor Guy Williams is a leading academic at the University of Cambridge with a focus on imaging science and clinical neurosciences, affiliated with Downing College and the Wolfson Brain Imaging Centre . Holding a PhD in Physics from his initial Natural Sciences degree, he specializes in nuclear magnetic resonance (NMR) and MRI techniques for brain imaging. Education: BA, PhD in Physics His research centers on non-invasive imaging of brain structure and function, particularly in traumatic brain injury (TBI) and dementia. His work involves developing novel MRI pulse sequences and advanced data analysis algorithms, including AI-based diagnostic tools. He leads studies on white matter integrity post-trauma, longitudinal dementia assessment, and applications of MRI in disorders of consciousness and addiction. Recent publications highlight collaborations in traumatic brain injury outcomes, AI-guided dementia prediction, and neuroimaging of post-COVID cognitive deficits. His team's work on ultra-high field laminar fMRI and distortion correction methods has advanced clinical neuroscience applications. Key techniques include diffusion tensor imaging (DTI), 7 Tesla MRI, and positron emission tomography (PET/MR). His research spans from basic NMR physics to clinical translation, with a strong emphasis on multi-site studies and real-world diagnostic implementation.
Professor Julie Harris is a faculty member at the University of St Andrews, holding the position of Professor of Psychology within the School of Psychology and Neuroscience since 2005. She previously held academic posts at Newcastle University and the University of Edinburgh, and conducted postdoctoral research at the Smith-Kettlewell Eye Research Institute in California. Her research focuses on human visual processing, including vision and camouflage, depth perception, binocular stereopsis, and eye movements in natural environments. She earned a BSc in Physics from Imperial College London and a DPhil from Oxford University. Research interests include exploring how visual systems process environmental cues for depth and motion, with applications in camouflage design and stereo display technologies. Her lab employs psychophysical, behavioral, and computational methods. Notable projects address countershading camouflage effectiveness, motion-in-depth perception, and visual-motor interactions in driving scenarios. Selected grants include funding from BBSRC, Leverhulme Trust, and Medical Research Scotland. Collaborations span evolutionary biology, neuroscience, and applied vision science. She supervises PhD students Federico De Filippi and Rebecca Maguire. Awards include the Davida Teller Award Nomination and Fellowship in the Society of Biology. Labs/Teams: Julie Harris Lab (St Andrews), St Andrews Vision Labs, and the Institute of Behavioural and Neural Sciences. Current projects investigate warning signal design, visual perception in virtual environments, and the impact of visual processing on driving ability.
Professor Anil Seth is a leading cognitive and computational neuroscientist at the University of Sussex, where he holds a professorship in the School of Engineering and Informatics. He is Director of the Sussex Centre for Consciousness Science and Co-Director of the CIFAR Program on Brain, Mind, and Consciousness and the Leverhulme Doctoral Scholarship Programme. His research bridges neuroscience, psychology, philosophy, and AI to investigate the biological basis of consciousness and selfhood. His research interests include: Predictive processing approaches to perception Virtual and augmented reality in self-experience studies Mathematical modeling of perception and emergence Machine learning applications in subjective perception modeling Interoception and selfhood Neural mechanisms of conscious experience The recent publications reflect a strong focus on consciousness, neural dynamics, predictive models, and interdisciplinary approaches. Trends include the use of computational modeling, neurophenomenology, causal analysis, and the ethical implications of emerging neurotechnologies. His work increasingly integrates large language models and data-driven methods for analyzing subjective experience. His scientific awards include: Segerfalk Award Perspectives Award Highly Cited Researcher (Web of Science, 2019–2022) Royal Society Michael Faraday Prize (2023) Seth has secured substantial research funding from the European Research Council (ERC), EPSRC, Wellcome Trust, CIFAR, and the Sackler Foundation. He has supervised numerous research projects and doctoral students through interdisciplinary programs. He leads the Dreamachine project and has been an Engagement Fellow with the Wellcome Trust. He serves on editorial boards including Philosophical Transactions of the Royal Society B and is Editor-in-Chief of Neuroscience of Consciousness . He leads a multidisciplinary research group at the Sackler Centre, bringing together psychologists, mathematicians, neuroscientists, computer scientists, and philosophers. His team conducts innovative research using virtual reality, neuroimaging, and computational modeling to explore the nature of consciousness and self.
Dr. Caterina Albano is a Reader at Central Saint Martins, University of the Arts London. She holds a PhD in Renaissance Studies (London University, 1993–1998) and specializes in interdisciplinary research at the intersection of art, medical sciences, and cultural theory. Her work explores the cultural history of emotion, politics of memory, and contemporary art practices, with a focus on themes like fear, vulnerability, and the unconscious. Albano is a prominent curator, organizing exhibitions such as Psychoanalysis: The Unconscious in Everyday Life (Science Museum, London) and Crossing Over: Art, Science and Biotechnologies (Royal Institution). She also co-founded the Art and Science Research Group at CSM and chairs the College Research Degree Subcommittee. Her research integrates curatorial practice with academic inquiry, addressing topics such as neuroscience, biogenetics, and the ethics of air in contemporary art. Albano supervises doctoral students in art and curatorial practices and actively contributes to academic discourse through editorial roles and grant assessments. She speaks multiple languages, including Italian, French, German, and English, and her work bridges art, science, and humanities to explore complex cultural and societal issues.
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.
Duncan Astle is the Gnodde Goldman Sachs Professor of Neuroinformatics at the Department of Psychiatry, University of Cambridge. He serves as a Programme Leader at the Medical Research Council's Cognition and Brain Sciences Unit (MRC CBU) and is a Fellow of Robinson College. Astle heads the 4D Lab (Development, Dynamics, Disorders, Data Science), which provides a research home for approximately 15 Early Career Researchers working at the intersection of developmental cognitive neuroscience and advanced data science methodologies. Astle's research focuses on understanding childhood development through innovative analytical approaches. His work employs transdiagnostic methods to study children with attention, learning, and memory difficulties, moving beyond traditional diagnostic categories. He investigates how neural systems develop in childhood, how they relate to developmental disorders, and how they respond to intervention. His research integrates network science, machine learning, and generative modeling to capture the complexity of neurodevelopmental diversity, examining how cognitive skills, literacy, numeracy, and mental health interrelate over developmental time. His publication record reveals a strong focus on brain connectivity and organization across development. Recent work explores structural and functional neurodevelopmental trajectories, brain wiring economics, and the impact of environmental factors on neural development. Astle's research frequently employs advanced data science techniques to identify sub-populations of children with different cognitive or brain profiles, regardless of diagnosis, and to map non-linear relationships between brain organization and cognitive difficulties. His work has increasingly focused on transdiagnostic approaches to understanding developmental disorders and the application of computational models to developmental neuroscience. Astle actively supervises PhD students and has built a substantial research group that contributes to major projects including the Centre for Attention Learning and Memory (CALM) and Resilience in Education and Development (RED). His work has been supported by prestigious funding bodies including the Royal Society, the British Academy, the Medical Research Council, and the Economic and Social Research Council, as well as multiple charitable foundations. The 4D Lab, under Astle's leadership, utilizes state-of-the-art facilities at the University of Cambridge, including on-site magnetic resonance imaging and magnetoencephalography scanners. The lab contributes to building specialist cohorts such as CALM (800 children with cognitive difficulties plus 200 comparison children) and RED, which study children's development, resilience, and educational outcomes. Astle's team explores how growing up in adverse environments affects children's brains, behavior, and mental health, with the aim of identifying early markers of risk and resilience.
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.
Dr Stella Bolaki is Reader in American Literature and Medical Humanities at the School of English, University of Kent, and Co-Director of the Centre for Health and Medical Humanities. She has been a faculty member since 2011, after holding positions at the University of Glasgow and the University of Edinburgh, where she also held a postdoctoral fellowship at the Institute for Advanced Studies in the Humanities (IASH). Her educational background includes a BA from Athens and an MSc and PhD from the University of Edinburgh. BA, Athens MSc, University of Edinburgh PhD, University of Edinburgh Stella’s research spans interdisciplinary fields including contemporary American literature, medical humanities, disability studies, and Black feminist theory. Her work critically examines narratives of illness, chronic conditions, self-care, and the intersection of art and health. She has pioneered research on artists’ books as tools for wellbeing, testimony, and community engagement, particularly in contexts of trauma and social injustice. Her recent publications and projects reveal a consistent focus on expanding narrative forms in medical humanities—moving beyond traditional literary modes to include photography, performance, film, and digital storytelling. Themes of inequality, mental health, climate anxiety, and embodiment recur across her work, especially in her ongoing monograph on self-care. Fellow of the Higher Education Academy Wellcome Trust funding recipient British Academy funding recipient Research England grant awardee Kent’s AHRC Impact Acceleration Account funding Stella supervises doctoral research across a wide range of interdisciplinary topics and has co-supervised a CHASE-funded project on health zines. She contributes to teaching in American literature and medical humanities at the Kent and Medway Medical School. Her professional service includes editorial roles for Contemporary Cultural Studies in Illness, Health and Medicine and the Journal of Literary & Cultural Disability Studies , and leadership in the Eastern Arc Medical and Health Humanities Network and the Kent Medical Humanities Network. She leads public-facing research through creative workshops, exhibitions, and events such as ‘Artists’ Books and the Medical Humanities’ and ‘Mending the Psyche: Art as Reparation’, often in collaboration with NHS partners and community organizations.
Dr. George Cantwell is an Assistant Professor in the Department of Engineering at the University of Cambridge, affiliated with Cambridge Infectious Diseases. He specializes in computational methods for inference problems, particularly in disease spreading across networks. Education: PhD in Physics from the University of Michigan; postdoctoral fellowship at the Santa Fe Institute His research focuses on network science , complex systems , and statistical inference , with an emphasis on computational approaches. His work spans theoretical and applied domains, including: Message passing algorithms for heterogeneous networks Bias correction in social network analysis (friendship paradox) Statistical inference of network structure from noisy data Modeling judicial voting behavior through network interactions Computational cognitive neuroscience of category learning Recent publications highlight interdisciplinary applications in epidemiology, physics, and cognitive science. He actively mentors students in networks, complex systems, and statistical inference.
Catherine Polling is an NIHR Clinical Lecturer in General Psychiatry at King’s College London (KCL), affiliated with the Institute of Psychiatry, Psychology & Neuroscience (IoPPN) and the Health Inequalities Research Group . Her work focuses on mental health inequities, self-harm epidemiology, and mixed-methods research, particularly in urban and marginalized communities. Education: MBBS from University College London, MSc in Epidemiology from the London School of Hygiene and Tropical Medicine, PhD from KCL's Department of Psychological Medicine Research Interests: Catherine investigates health disparities in mental health services using advanced statistical methods (multi-level modeling, Bayesian disease mapping) and GIS-based data visualization. Her clinical work with the South London and Maudsley NHS Foundation Trust complements her academic focus on systemic racism and mental health outcomes. Teaching & Engagement: She lectures on urban mental health for KCL’s Urban Informatics MSc and co-leads training on racism in mental health services. She also facilitates reflective practice groups accredited by the Balint Society and contributes to curriculum reform via the Maudsley Cultural Psychiatry Group. Scientific Awards: NIHR Clinical Lecturer Fellowship Wellcome Training Fellowship Research Trends: Her publications emphasize self-harm risk factors, pandemic impacts on healthcare workers, ethnic disparities in mental health services, and the intersection of urban environments with mental health outcomes. She integrates large-scale clinical datasets, qualitative interviews, and spatial analysis to address systemic inequities.
Zhongying Deng is a Research Fellow in the Department of Applied Mathematics and Theoretical Physics (DAMTP) at the University of Cambridge, affiliated with the Cambridge Image Analysis research group. His work focuses on advancing medical imaging technologies and computer vision through deep learning and domain adaptation techniques. Key contributions include developing benchmark datasets like TrafficCAM and TrafficMOT for traffic analysis, A-Eval for abdominal organ segmentation, and foundational models for medical AI such as GMAI-VL. His research bridges theoretical advancements in neural networks and practical applications in healthcare and transportation. His research interests span image segmentation, domain adaptation, neural network architectures, and multimodal data integration. Notable projects include FCN+ for enhanced convolutional networks and Brain Foundation Models for neurodegenerative disease analysis. Deng collaborates extensively on interdisciplinary projects, combining mathematical modeling with computational tools to address real-world challenges in medical diagnosis and autonomous systems. Publications emphasize scalable medical image analysis frameworks (e.g., STU-Net, Sa-med2d-20m) and robust domain adaptation methods for cross-dataset performance. His datasets and models are widely recognized for enabling reproducible research and advancing state-of-the-art performance in critical areas like MRI reconstruction and multi-organ segmentation.
