People
Faculty
Maria del Rio-Chanona
Dr Maria del Rio-Chanona is a Lecturer (Assistant Professor) at University College London in the Computer Science department. Her research draws from network science, Large Language Models (LLM), as well as Agent-Based Models (ABM) to study the economic and employment impacts of the net-zero transition, the Covid-19 pandemic, and (Gen)AI. Maria completed her PhD in mathematics at the University of Oxford, where she was part of the complexity economics group of the Institute for New Economic Thinking, Oxford Martin School. She was a JSMF research fellow at the Complexity Science Hub, Vienna and a visiting scholar at the Harvard Kennedy School. Maria has worked alongside international policy organisations, including the International Monetary Fund, the World Bank, and the International Labour Organization.
Silvia Bartolucci
Dr Silvia Bartolucci is an Associate Professor in the Department of Computer Science at University College London (UCL), where she is part of the Financial Computing and Analytics Group. Her research leverages network, statistical physics and data-driven modelling tools to investigate critical behaviour in socio-economic systems, assessing protocols’ design and applications of blockchain technologies, monitoring trends and issues in traditional and decentralized financial markets. Before joining UCL, Dr. Bartolucci was a Research Associate in the Department of Finance at Imperial College Business School, working within the Centre for Financial Technology. She holds a Ph.D. in Applied Mathematics from King's College London and a background in Theoretical Physics from Sapienza University in Rome.
Paolo Barucca
Dr Paolo Barucca is Associate Professor at UCL Computer Science. He obtained his PhD in Theoretical Physics from Sapienza University of Rome. He works on Statistical Physics of Complex Systems, Statistical and Machine Learning in Finance and Economics. He collaborates with private and public institutions for teaching and research activities on machine learning and statistical data science in finance and economics applied to risk assessment and predictive modeling.
Alejandro Hermida Carrillo
Dr Alejandro Hermida Carrillo is an Imperial College Research Fellow (ICRF) in the Department of Management and Entrepreneurship at Imperial College Business School. Alejandro is passionate about understanding how different components of the self – such as personality, attitudes and beliefs – simultaneously shape and respond to socio-economic structures. In his fellowship, he studies the rise of autocratic leaders using digital trace data and Natural Language Processing. Before joining Imperial, Alejandro completed a PhD in Management at the LMU Munich, Germany, and degrees in Psychology (MSc, LMU Munich and Licenciatura, UNAM). He was also a visiting researcher at the Computational Culture Lab of Stanford Graduate School of Business.Speakers
Doyne Farmer
J. Doyne Farmer is Director of the Complexity Economics programme at the Institute for New Economic Thinking and Baillie Gifford Professor of Complex Systems Science at the Smith School of Enterprise and the Environment, University of Oxford. He is also External Professor at the Santa Fe Institute and CEO and Chief Scientist at Macrocosm. His current research is in economics, including agent-based modeling, financial instability and technological progress. He was a founder of Prediction Company, a quantitative automated trading firm that was sold to UBS in 2006. His past research includes complex systems, dynamical systems theory, time series analysis and theoretical biology. His book, Making Sense of Chaos: A Better Economics for a Better World, was published in 2024. During the 1980s he was an Oppenheimer Fellow and the founder of the Complex Systems Group at Los Alamos National Laboratory. While a graduate student in the 1970s he built the first wearable digital computer, which was successfully used to predict the game of roulette.
Neave O'Cleary
Neave O'Clery is Professor of Cities and Networks, and Director of Research, at the Centre for Advanced Spatial Analysis (CASA) at University College London where she leads an inter-disciplinary research group focused on data-driven models for economic development and developing cities. She is currently seconded part time to the UK Foreign, Commonwealth and Development Office. Her work spans a number of topics and fields including economic complexity and evolutionary economic geography, the informal economy, urban mobility and network science. Neave was previously a Senior Research Fellow at the Mathematical Institute at the University of Oxford, and before this a Fulbright Scholar at the Center for International Development at the Harvard Kennedy School. She is founder and Chair of the Oxford Summer School in Economic Networks, an annual multi-disciplinary summer school since 2017. She holds a PhD (mathematics) from Imperial College.
Pierpaolo Vivo
Pierpaolo Vivo studied Physics at the Università degli Studi di Parma (Italy), where he also graduated in Theoretical Physics cum laude in 2005. He then moved to Brunel University (West London), where he obtained his PhD in 2008. He spent three years as Postdoctoral Fellow at Abdus Salam ICTP - Trieste (Italy), where he worked in the Condensed Matter and Statistical Physics group. During the period 2011-2014 he worked as a research scientist at the Laboratoire de Physique Théorique et Modèles Statistiques (LPTMS) in Orsay, (France). He has been a permanent member of the Disordered Systems group at King's College London since September 2014, where leads the Quantitative and Digital Law Lab in the Department of Mathematics at King’s College London, a team of five people supported by a UKRI Future Leaders Fellowship that promotes a quantitative approach to issues around the complexity of legal systems. In this role, he collaborated on two guest-edited collections: “The physics of the law: legal systems through the prism of complexity science” (Frontiers in Physics, 2021) and “A complexity science approach to law and governance” (Philosophical Transactions of the Royal Society A, 2024).
Sanaz Talaifar
Sanaz Talaifar is an Assistant Professor in Organisational Behaviour at Imperial College London. She studies identity and its intersections with politics and technology using a multi-method approach that combines traditional methods (surveys, experiments) with novel methods (mobile sensing, experience sampling). She is particularly interested in theory-method synergy, wherein novel methods inform the development of theory and theoretical insights inform the development of novel methods. Previously, Sanaz was a Postdoctoral Scholar in Organizational Behavior at Stanford University and received her PhD in Social and Personality Psychology from the University of Texas at Austin. Outside of academia, she has worked in people analytics at Google and in executive search at Egon Zehnder.
Mike Yeomans
Mike Yeomans is an Assistant Professor in Strategy and Organisational Behaviour at Imperial College Business School. In his research, Mike studies the decisions we make in conversation. We are a social species, doing and learning so much with one another. And the things we choose to say can have profound impacts on our relationships in business, and in life. His work explores the many ways that language technology can help us understand and improve our conversational decisions, so that we can better pursue our social goals together.
Stefania Innocenti
Stefania Innocenti is a Departmental Research Lecturer (Assistant Professor equivalent) at the Smith School of Enterprise and the Environment at the University of Oxford. She is an applied economist working at the intersection of behavioural economics, environmental economics and public policy. Stefania co-leads the Economics of Sustainability programme at the School and at the Institute for New Economic Thinking. She is also an Associate Member of the Economics Department at the University of Oxford and a member of Brasenose College.
Mirco Musolesi
Mirco Musolesi is Professor of Computer Science at the Department of Computer Science at University College London, where he leads the Machine Intelligence Lab. He is also Professor of Computer Science at the University of Bologna, Italy. He has broad research interests spanning several traditional and emerging areas of Computer Science and beyond. More specifically, current research areas include AI-based decision making (in single- and multi-agent scenarios), generative artificial intelligence and computational models (in particular, learning models) of user/human/machine behaviour. Information about his research profile can be found at his personal webpage.
Milena Tsvetkova
Milena Tsvetkova is an Associate Professor of Computational Social Science at the Department of Methodology at the London School of Economics and Political Science. She is also the director of the HUMANET lab, funded by the ERC Consolidator grant with €2,000,000 in 2025–2030 to study interactions and collective outcomes in human-machine social systems. Milena is a computational social scientist, with a PhD in Sociology. She uses large-scale online experiments, network analysis, machine learning, and computational modeling to study fundamental social phenomena such as cooperation, contagion, segregation, and inequality in human and human-machine networks and communities.
