UCL Psychology and Language Sciences



Behavioural data science is an emerging interdisciplinary field which combines behavioural theory (from e.g. psychology and behavioural economics) and computational data science approaches (from e.g. statistics and computer science) to better predict and provide insights into human behaviour. This involves the development and application of advanced computational models to data, efficient and reliable techniques to collect more informative data, and new techniques to enhance the interpretability of behavioural data. These methodological advances are informed by recent understanding of the internal and external drivers of human behaviour. In behavioural data science, developments in methods and theory go hand-in-hand. The UCL Centre for Behavioural Data Science provides a focal point for these activities. Work at the Centre focuses on three broad areas:

  1. Conducting research on human behaviour (in various domains) using state-of-the-art data science techniques, and advancing and developing data science techniques to collect and extract the most information from behavioural data.
  2. Providing education on the foundations and latest developments in behavioural data science techniques. Members of the centre have extensive experience in teaching stattistics and data science at the BSc, MSc, and PhD level.
  3. Helping others in applying behavioural data science to provide genuine behavioural insights. This can be in the form of collaboration, consultation, or otherwise.

In support of these aims, we organize a weekly seminar series, as well as workgroups, workshops, etc.



Prof Maarten Speekenbrink is Director of the UCL Centre for Behavioural Data Science and Professor of Mathematical Psychology at UCL Experimental Psychology. He is an internationally renowned researcher on human learning and decision making. His research combines advanced computational modelling with behavioural research. He is an expert on a wide variety of advanced data acquisition (e.g. adaptive optimal design, Bayesian optimization) and analysis techniques (e.g. hidden Markov models, state-space methods, Gaussian processes). He has published widely on both substantive and methodological topics in behavioural data science.


Dr Henrik Singmann is Vice-Director of the UCL Centre for Behavioural Data Science and Associate Professor of Quantitative Psychology at UCL Experimental Psychology. His main research interests concern the development and implementation of computational methods and statistical tools for psychology and related disciplines. In addition to his methodoogical work, he is developing and testing mathematical models of higher-level cognition (especially in reasoning, decision making, and memory) and applying advanced statistical methods to applied problems (e.g., gambling research).

Core members

Dr Stephen Dewitt (UCL Experimental Psychology)

Dr Duarte Goncalves Dias Da Silva (UCL Economics) s a lecturer (assistant professor) in economics. His research combines economic theory and experiments to study behaviour in both individual decision-making and strategic settings. His current research focus is on explaining patterns relating choice, response time, and belief formation in decision making, inference problems, and strategic interaction.

Dr Simmy Grover (UCL Experimental Psychology)

Prof Bradley Love (UCL Experimental Psychology)

Prof Ioanna Manolopoulou (UCL Statistical Science) is a Professor of Statistical Science at the UCL Department of Statistical Science and Associate Director of the HDRUK-Turing PhD programme. Her main research interests lie in developing, extending or re-evaluating Bayesian models with a view to producing inferences which are useful and interpretable in practical applications. The focus is on flexible Bayesian modelling tools such as mixture models and tree models and applications of interest range from health data science to retail analytics.

Prof Mirco Musolesi (UCL Computer Science)

Dr Adam Parker (UCL Experimental Psychology) is a Lecturer in Experimental Psychology. His research seeks to understand how humans process written language via eye movement recordings. He is also interested in transparency and research integrity and is actively integrating these principles into his research methods training across the BSc programmes at UCL, where he convenes PSYC0037 Research Project and PALS0043 Advanced Statistical Research Methods.

Prof David Shanks (UCL Experimental Psychology) is Professor of Psychology and conducts research on human learning and memory; judgment and decision-making; computational modeling, especially with neural network and signal detection models; amnesia, the hippocampus, and the implicit-explicit distinction; economic psychology and rationality.

Dr Metodi Siromahov (UCL Experimental Psychology)

Dr Martin Vasilev (UCL Experimental Psychology) is a Lecturer in Behavioural Statistics at UCL. His research expertise is in the analysis of eye-tracking data, linear mixed models, computational modelling, machine learning, and evidence synthesis.

Postdoctoral Fellows

Dr Noam Markovitch (UCL Experimental Psychology) is a Postdoctoral fellow interested in harnessing diverse data analytic approaches to gain insights into pressing social phenomena. She is currently focusing on using computational decision-making models to investigate the underlying mechanisms behind the decision to stay in consensual yet unwanted sexual interactions.

Dr Ken Luo (UCL Experimental Psychology)

Dr Charlie Pilgrim (UCL Experimental Psychology)

Dr Brett Roads (UCL Experimental Psychology)

Doctoral Fellows

Danny Ball (UCL Institute of Cognitive Neuroscience)

Victor Btesh (UCL Experimental Psychology)

Calvin Deans-Browne (UCL Experimental Psychology) is a PhD student interested in how we reason about arguments we see in our everyday lives. More specifically, he researches what features people (dis)like in arguments, how people evaluate the quality of these arguments as a function of their beliefs, and potential mechanisms that link the beliefs they hold with the evaluation of the arguments they see.

Yuyang Ding (UCL Experimental Psychology) is a PhD student studying topics related to financial decision-making. His current research interests mainly focus on investigating the decision-making patterns of investors by asking participants to trade in a virtual stock market with real-time price changes. His research combines behavioural experments with computational modelling with a particular focus on evidence accumulation processes.

Marcus Glennon (UCL Clinical Psychopharmacology Unit) is a PhD student studying the neuroplasticity-inducing effects of psychedelics, their impact on memory, and how we may be able to harness these effects in a clinical setting for memory-based disorders.

Jona Leka (UCL Experimental Psychology)

Maximilian Maier (UCL Experimental Psychology) is a PhD student studying topics related to applied statistics and decision-making psychology. His main contribution to his applied statistics is the development of a new Bayesian meta-analysis method to correct for publication bias (robust Bayesian meta-analysis, RoBMA). In his experimental work, he used behavioural research as well as computational modelling to study topics related to moral and altruistic decision-making.

Trisevgeni Papakonstantinou (UCL Experimental Psychology) is a PhD student studying the cognitive mechanisms involved in the formation and revision of complex mental models, through experimental methods, computational modeling and analysis of naturalistic data. She has a background as a behavioural data scientist in the field of health behaviour change, with experience in industry and government.

Ursule Taujanskaite (UCL Clinical Psychopharmacology Unit) is a PhD student working on the psychopharmacology of psychosis, trauma and intrusive memories.

Laina Townsend (UCL Institute of Cognitive Neuroscience)

Orestis Zavlis (UCL Psychoanalysis Unit) is a PhD student working at the intersection of computational science and relational psychoanalysis. His research includes experimental testing and computational modelling of relational beliefs (that is, beliefs about oneself and others) and how they can inform personality psychopathologies.