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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
• +3 more

Leslie Ann Goldberg is a Senior Research Fellow at St Edmund Hall and Professor of Computer Science at the University of Oxford. She currently serves as Head of the Department of Computer Science (on sabbatical 2025-26) and focuses on foundational problems in Algorithms and Complexity Theory , particularly randomised algorithms for network communication, machine learning, and statistical physics models. Her research includes solving Aldous' 1987 conjecture on backoff protocol instability (with John Lapinskas), developing rigorous mathematical analysis frameworks for algorithmic efficiency, and advancing approximate counting techniques via Markov Chain Monte Carlo methods (with Andreas Galanis and collaborators). Key projects involve graph homomorphisms , Moran process dynamics , and #BIS complexity class analysis. Recent publications (2023-2024) span topics like Sybil defense mechanisms, low-temperature sampling on random graphs, and parameterised subgraph counting modulo 2. Her work demonstrates cross-disciplinary impact in computational biology, statistical physics, and database theory. Scientific Awards include Best Paper Prizes at ICALP 2016, ICALP 2010, and IPEC 2017. She supervises PhD student Paulina Smolarova and collaborates extensively with researchers in Oxford and beyond.

• Algorithms
• Complexity Theory
• Randomised Algorithms
• +5 more

Dr. Rasmus Ibsen-Jensen is a Lecturer in Computer Science at the University of Liverpool. Previously, he held a Postdoctoral position at IST Austria under Krishnendu Chatterjee and completed his PhD under Peter Bro Miltersen. Research Focus: Algorithmic game theory, strategy complexity in two-player zero-sum games, control flow graph algorithms, edit distance for automata, and theoretical biology applications. Teaching: Module Coordinator for second-year courses in database development (COMP207), C++ programming (COMP282), and industrial placement (COMP299). His work bridges computational game theory and formal verification, with recent publications exploring memory constraints in partial-information games, algebraic path properties in concurrent systems, and evolutionary spatial dynamics. While no scientific awards are explicitly mentioned in the provided text, his contributions to algorithmic complexity and interdisciplinary research (e.g., theoretical biology) highlight his academic impact.

• Algorithmic Game Theory
• Concurrent Systems
• Formal Verification
• +3 more

Alan Grafen is an Honorary Fellow at Jesus College, University of Oxford, and holds Tutorial Fellow roles at St John’s College in Quantitative Biology. His primary affiliation is the University of Oxford’s Faculty of Biology and Medicine. He is a leading evolutionary biologist specializing in mathematical and logical models of evolutionary processes. Research Interests: Grafen’s work focuses on evolutionary theory, particularly the formalization of Darwinism, inclusive fitness, signal evolution, and sexual/kin selection. He leads the Formal Darwinism Project to mathematically formalize natural selection’s role in evolution. His models include the mathematical underpinning of Zahavi’s handicap principle and advancements in reproductive value theory. Key Contributions: Published influential works like Modern Statistics for the Life Sciences (2002) and co-authored analyses of Richard Dawkins’ evolutionary ideas. His recent articles (2018–2024) explore natural vs. sexual selection distinctions, kin recognition stability, and extensions to Fisher’s fundamental theorem. Awards and Grants: Not explicitly listed, but his work has shaped evolutionary theory. His research spans theoretical models in Nature -level journals and interdisciplinary collaborations with statisticians and biologists. Labs/Teams: Directs the Formal Darwinism Project and collaborates with evolutionary theorists globally. His work bridges mathematics and empirical biology, influencing both academic and popular science discourse.

• Evolutionary Biology
• Mathematical Biology
• Theoretical Evolutionary Theory
• +4 more

Dr James Herbert-Read is an Associate Professor and Whitten Lecturer in Marine Biology at the Department of Zoology, University of Cambridge. He serves as Deputy Head of Department (Postgraduate Education) and leads the Marine Behavioural Ecology Group. His research focuses on understanding how animals, particularly marine organisms, collect and process information from their environments to make behavioral decisions, with emphasis on social interactions, adaptation mechanisms, and ecological constraints. His group employs theoretical frameworks, controlled experiments, and quantitative field studies to investigate behavioral diversity in marine species. Key themes include collective behavior, predator-prey dynamics, camouflage strategies, and the impacts of environmental stressors on animal decision-making. Recent publications highlight work on lionfish vocalization mechanisms, cuttlefish camouflage, citizen science applications in marine research, and behavioral responses to visual and acoustic noise. Scientific awards and affiliations include: Whitten Lecturer in Marine Biology Associate Professor, University of Cambridge He has supervised research projects on topics such as: Social attraction in invasive fish species Evolution of coordinated movement Neurophysiological basis for leadership in shoals Maternal effects on offspring exploration

• Behavioural Ecology
• Marine Biology
• Collective Animal Behaviour
• +4 more

Klaus Ritzberger is a Professor of Economics at the Department of Economics, Royal Holloway, University of London. He holds academic affiliations at multiple institutions, including the Institute for Advanced Studies (IHS) in Vienna and the Vienna Graduate School of Finance (VGSF). His career spans leadership roles, such as Chairman of the Department of Economics and Finance at IHS (1999–2005) and numerous visiting professorships globally. Education: Magister rer.soc.oec. (1982), University of Vienna Doktor rer.soc.oec. (1987), University of Vienna Habilitation in Economic Theory (1996), University of Vienna Research focuses on game theory, economic theory, and general equilibrium. His work explores strategic stability, evolutionary game theory, and institutional economics. Recent contributions include analyses of bankruptcy in uncertain equilibria and multi-lateral bargaining dynamics. Awards include the Economic Theory Fellow (2011) and multiple Oskar Morgenstern Awards. He has secured grants for projects like 'Foundations of the Theory of Extensive Form Games' (2009–2013) and serves on editorial boards of journals like Economic Theory and International Journal of Game Theory .

• Game Theory
• Economic Theory
• General Equilibrium
• +3 more

Dr. Eleanor Power is an Associate Professor in the Department of Methodology at the London School of Economics and Political Science (LSE). Her research focuses on the interplay between belief, practice, identity, and social relationships, with a particular emphasis on how reputational dynamics shape social inequality and cooperation. She combines ethnographic methods with social network analysis to study these phenomena in South India and cross-culturally. Education: Eleanor holds a PhD in Anthropology from Stanford University (2015). Prior to joining LSE in 2017, she was an Omidyar Postdoctoral Fellow at the Santa Fe Institute. She is fluent in English and Tamil. Research Interests: Eleanor examines signaling theory, religious practice, and the micro-dynamics of social inequality, including the 'reputational poverty trap.' Her current projects include co-directing the ENDOW project on social and economic inequality and leading the Rep2SI project on reputational dynamics. Her work bridges anthropology, sociology, and computational social science. Publications: Her recent work explores latent network models, cooperative behavior in South Indian communities, and the role of reputation in human social networks. She also collaborates on interdisciplinary projects, such as analyzing reproductive inequality across species and the impact of art workshops on prisoners' well-being. Awards: While no specific awards are listed, her research has been highlighted in LSE's 30th Anniversary celebrations for its interdisciplinary innovation and collaborative nature. Grants and Labs: Eleanor leads the Rep2SI project and co-directs the ENDOW project, indicating active grant-funded research. She is affiliated with LSE's Department of Methodology and has collaborated with institutions like the Santa Fe Institute.

• Social Network Analysis
• Ethnography
• Religion and Society
• +5 more

Professor Nir Oren is a faculty member at the School of Natural and Computing Sciences , University of Aberdeen. His research focuses on multi-agent systems , formal argumentation , computational trust theory , and norm-based reasoning . He currently supervises PhD students in Computing Science and serves as Dean for Research Performance. Research Specialisms: Artificial Intelligence, Operational Research Contact: n.oren@abdn.ac.uk Research Trends (2022–2025): Nir Oren's publications span argumentation theory , BDI agent modeling , resilience in autonomous systems , and human-machine collaboration . His recent work addresses responsibility-aware AI , medical explainability , and environmental sensor networks . Key methods include probabilistic reasoning , game theory , and logical formalisms .

• Multi-Agent Systems
• Formal Argumentation
• Computational Trust Theory
• +1 more

Andy White is a Professor in the School of Mathematical & Computer Sciences at Heriot-Watt University, specializing in mathematical biology. He holds dual roles in the Mathematics Department and the broader interdisciplinary research environment. His research focuses on developing mathematical models to address ecological and evolutionary questions, particularly in host-parasite dynamics and infectious disease management. He has held academic positions since 1999, progressing from a Lecturer to Professor by 2013. Education: PhD from University of Liverpool (1996), supervised by Professors Mike Begon and Roger Bowers. Early career included climate change research at NERC Centre for Ecology and Hydrology (1996–1999). Research Interests: Mathematical modeling of biological systems, including adaptive dynamics in host-parasite interactions, population dynamics of ecological systems, and disease transmission mechanisms. Key projects include analyzing the UK grey squirrel invasion and tuberculosis/African swine fever spread. Collaborations span institutions like UC Berkeley and the Institute of Game and Wildlife Research, Spain. Recent Article Trends: Focus on pathogen-mediated invasions, virulence evolution in multispecies contexts, hyperparasite dynamics, and the ecological impacts of predator recovery (e.g., pine marten effects on squirrel populations). These studies combine theoretical models with real-world conservation applications. Grants & Collaborations: Engages in interdisciplinary projects addressing global challenges like biodiversity conservation and disease management. Active in collaborations across Europe and North America. Labs/Teams: Leads research groups focused on mathematical ecology and epidemiology, with contributions to UN Sustainable Development Goals related to life on land and good health.

• Mathematical Biology
• Ecological Modeling
• Evolutionary Dynamics
• +3 more

Professor Hamid Sabourian holds the title of Professor of Economics and Game Theory at the Faculty of Economics, University of Cambridge, and serves as a Fellow of King's College. His work bridges theoretical and applied domains, focusing on economic theory, game theory, and behavioral economics with applications in organ transplantation, financial markets, and social learning. Education & Affiliations : Affiliated with the University of Cambridge's Faculty of Economics and King's College. Research Focus : Explores bounded rationality, strategic complexity, herding behavior, and mechanism design. His work connects abstract game theory with real-world issues in healthcare, financial systems, and collective decision-making. The article trends reveal a consistent focus on game theory applied to dynamic environments, with recurring themes in herding, strategic complexity, and mechanism design across domains like organ transplantation, financial markets, and innovation. His work often integrates mathematical rigor with behavioral insights, emphasizing rational decision-making under uncertainty and institutional constraints. Scientific Awards : Fellow of the British Academy (2013). Advising : Supervised PhD student Yifan Zhang. Grants : Received funding from the Economic and Social Research Council (ESRC) for research on herding in financial markets (2005-2009).

• Economic Theory
• Game Theory
• Microeconomic Theory
• +3 more

Michel Leseure serves as a Senior Lecturer in Mechanical Engineering within the School of Electrical and Mechanical Engineering at the University of Portsmouth, where he is affiliated with the Centre for Operational Research and Logistics and Centre of Operational Research and Decision Analysis. As an active PhD Supervisor accepting new doctoral candidates, he contributes to both academic instruction and research supervision in technology-focused programs. His research centers on evolutionary analysis of technical systems, notably applying cladistics (a biological classification method) to manufacturing systems. Additional expertise spans engineering economy, real options theory, and scenario analysis, with recent expansion into sustainable operations management, microgrid optimization, and renewable energy integration. His work bridges industrial engineering with environmental sustainability through lean methodologies and strategic decision frameworks. Analysis of his 2023-2025 publications reveals dominant themes in collaborative microgrid systems, where he pioneers approaches to mitigate renewable energy volatility using lean-heijunka strategies and precontracted order mechanisms. His research consistently addresses supply chain resilience, policy impacts on manufacturing investment, and sustainability-performance trade-offs across energy and industrial sectors. Leseure actively mentors doctoral researchers through the Centre for Operational Research and Logistics, focusing on operational decision-making in energy systems and sustainable manufacturing. His collaborative projects frequently involve international researchers, particularly with H. Feleafel and J. Radulovic, examining microgrid economics and supply chain adaptability under turbulent conditions.

• Evolution of Technical Systems
• Cladistics in Manufacturing
• Engineering Economy
• +6 more

Nguyen Dang is a Lecturer at the School of Computer Science, University of St Andrews, actively supervising PhD students and teaching AI-related modules including Artificial Intelligence (CS3105), Artificial Intelligence Practice (CS5011), Machine Learning (CS5014), and Uncertainty in Artificial Intelligence (CS5016). He leads the Centre for Interdisciplinary Research in Computational Algebra and maintains an active research profile with numerous publications in top conferences. University of St Andrews, School of Computer Science Lecturer (equivalent to assistant professor) Supervising PhD students including Tai Nguyen Teaching multiple AI and Machine Learning courses Dr. Dang's research focuses on the intersection of machine learning and optimization, particularly automated algorithm configuration and design. His work centers on leveraging machine learning techniques to automate the development of optimization algorithms, with special emphasis on deep reinforcement learning for Dynamic Algorithm Configuration and integrating machine learning into constraint programming. His research has significant applications across various domains, especially in automated constraint modeling. The publications reflect strong activity in combinatorial optimization, algorithm selection, and benchmark instance generation. His recent publications demonstrate consistent output in top venues including Artificial Intelligence Journal, GECCO, FOGA, and CP conferences, with notable achievements including Best Paper Awards at GECCO'2025 and GECCO'2022. The research spans theoretical foundations of parameter control, practical applications in constraint programming, and innovative approaches to algorithm configuration. Best paper award at GECCO'2025 Best paper award at GECCO'2022 Nomination for best paper award at FOGA'2023 Best paper award at GECCO'2017 Dr. Dang holds a Leverhulme Early Career Fellowship (2020-2023) worth £90,000 for his project on constraint-based automated generation of synthetic benchmark instances. He has secured additional funding including EPSRC High Performance Computing grants totaling over 2.2 million CPU hours and a COST Action grant. His research group actively develops tools and frameworks for automated algorithm configuration and benchmark instance generation, with several open-source datasets available on GitHub. He is involved with multiple research groups including the Centre for Interdisciplinary Research in Computational Algebra and collaborates extensively with researchers at University of St Andrews and internationally, including at Université de Paris I Panthéon-Sorbonne where he conducted visiting research.

• combinatorial optimisation
• algorithms
• machine learning
• +5 more

Douglas Yu is a Professor in the School of Biological Sciences at the University of East Anglia (UEA), where he also serves as Principal Investigator and Director of the Ecology, Conservation, and Environment Center (ECEC), a joint venture with the Kunming Institute of Zoology. He is a member of the Centre for Ecology, Evolution and Conservation and the Organisms and the Environment research group. His research focuses on cooperation in ecological systems, particularly mutualisms between species and conservation as cooperation between humans and nature. Key methodologies include environmental DNA (eDNA), metabarcoding, and game theory. He co-founded NatureMetrics to commercialize biodiversity monitoring tools. His work spans tropical ecology, conservation genetics, and human-wildlife conflict resolution, notably in the Amazon. His recent research outputs highlight trends in molecular biodiversity assessment, landscape-scale eDNA analysis, and integrating remote sensing with ecological data. He leads multiple NERC-funded projects and industry collaborations focused on pollination services, cocoa sustainability, and statistical frameworks for eDNA. He is actively involved in scientific governance, serving on the NERC Biomolecular Analysis Facility Steering Committee and UKRI grant panels. He also contributes to public discourse through media appearances on topics like leech-based disease surveillance and bee conservation. He teaches courses in evolutionary biology, conservation genetics, and statistical modeling using R. He welcomes PhD and postdoctoral researchers, especially those interested in fieldwork in East Asia.

• Metabarcoding
• Rapid Biodiversity Assessment
• Environmental DNA (eDNA)
• +12 more

Dr Vasileios Kotsidis is a Lecturer at the Faculty of Economics, University of Cambridge, and holds a Bibby Fellowship at St Catharine's College. He teaches Political Economy and Market Failures (PIIB Paper 5) in the Michaelmas term. His research bridges Microeconomics and Game Theory , focusing on modeling Social Preferences and Evolutionary Game Theory in strategic interactions. He explores preference formalizations, norm emergence, and social dynamics. He received his PhD from the University of Nottingham in 2018, supervised by Dr. Silvia Sonderegger and Dr. Daniele Nosenzo. His work combines theoretical and applied approaches to economic behavior. Scientific Awards : Cambridge Centre for Teaching and Learning Technology-enabled Learning Prize (2021) Contact: vk340@cam.ac.uk , Austin Robinson Building, Sidgwick Avenue, Cambridge CB3 9DD, UK. Office hours: Wednesday 12:00-2:00pm.

• Microeconomics
• Game Theory
• Social Preferences
• +1 more

Tim Rocktaschel is a Professor of Artificial Intelligence in the Department of Computer Science at University College London (UCL), where he has been working since 2018. He was promoted to Professor in October 2023, having previously served as an Associate Professor (2021-2023) and Lecturer (2018-2021) at the same institution. His educational background includes a Doctorat from University College London (2017) and a Diplom Informatiker from Humboldt-Universitat Berlin (2012). Rocktaschel's research focuses on the cutting edge of artificial intelligence, with particular emphasis on reinforcement learning, evolutionary computation, and open-ended learning systems. His work explores how AI systems can learn more efficiently through better exploration strategies, environment design, and the integration of language models with reinforcement learning frameworks. His recent publications reveal a strong trend toward developing more efficient and generalizable AI systems. The research spans unsupervised environment design, prompt engineering for self-improving systems, exploration strategies in reinforcement learning, and the application of language models to enhance policy learning. His work often bridges theoretical AI concepts with practical implementations, as evidenced by tools like GriddlyJS for reinforcement learning development. Rocktaschel maintains an active presence in the AI research community with numerous publications in top venues including NeurIPS, ICML, and the Journal of Artificial Intelligence Research. His work on zero-shot generalization, pragmatic understanding in language models, and open-ended learning environments has garnered significant attention in the field. He is actively involved in developing tools and datasets for the AI community, such as the large-scale NetHack dataset, which provides a complex environment for testing reinforcement learning algorithms. His research continues to push the boundaries of what's possible in artificial intelligence, particularly in creating systems that can learn and adapt in complex, open-ended environments.

• Artificial Intelligence
• Reinforcement Learning
• Evolutionary Computation
• +1 more