Adriene Beltz is an Assistant Professor of Psychology at the University of Michigan. She is a quantitative developmentalist who creates and implements innovative time-indexed analyses to understand biopsychosocial influences on gender disparities in psychopathology and cognition across the lifespan. Dr. Beltz received her Ph.D. in Psychology, specializing in Social, Cognitive, and Affective Neuroscience from the Pennsylvania State University working with Dr. Sheri Berenbaum on human behavioral neuroendocrinology, and then she transitioned to a post-doctoral position in Human Development and Family Studies at the same university working with Dr. Peter Molenaar on network analysis approaches for brain and behavioral data. Her work has been funded by the National Institutes of Health, Jacobs Foundation, and James S. McDonnell Foundation. She has also received awards from the Association for Psychological Science as well as Divisions 5 (Methods) and 6 (Behavioral Neuroscience) of the American Psychological Association.

Markus Eronen is an Assistant Professor in the Department of Theoretical Philosophy at the University of Groningen. He received his PhD at the University of Osnabrück (Germany) in 2010, and his previous positions include a postdoctoral fellowship of the Research Council Flanders (FWO), a visiting scholarship at UC Davis, and Assistant Professor in the Department of Theory and History of Psychology at the University of Groningen. His current research is focused on (1) causal discovery and the problems of psychological causation, (2) complexity, networks, and levels of organization, and (3) the theory crisis and the nature of psychological theories.

Christian Gische is a postdoc in the Department of Psychological Research Methods at Humboldt-Universität zu Berlin. He studied at Julius-Maximilians University of Würzburg where he received a bachelor’s and master’s degree in economics. Furthermore, he received a master’s degree in statistics at Humboldt-Universität zu Berlin where he also obtained his Ph.D. in psychology in 2021. His interdisciplinary research touches on diverse fields such as structural equation modeling, graph-based models, dynamical systems, and causal inference. His current research focuses on understanding the underlying assumptions of parametric structural models from a causal perspective.

Ellen Hamaker is Professor of Longitudinal Data Analysis at the Department of Methodology and Statistics, Faculty of Social and Behavioural Sciences, Utrecht University. She obtained a Master’s degree in Clinical Psychology from Utrecht University in 1999, and a PhD in Psychological Methodology from the University of Amsterdam in 2004. Her research consists of the development, evaluation, and refinement of innovative statistical techniques for the analysis of panel data and intensive longitudinal data such as obtained with daily diaries and experience sampling methods. She is best known for her work on the random intercept cross-lagged panel model (RI-CLPM) and dynamic structural equation modeling (DSEM). A common theme in her work is to bridge the gap between statistical models and substantive research questions. She has obtained various research grants that helped her build the Dynamic Modeling Lab, which is currently supported by an ERC consolidator grant she obtained in 2019.

Kosuke Imai is Professor in the Department of Government and the Department of Statistics at Harvard University and an affiliate of the Institute for Quantitative Social Science. His areas of expertise include causal inference, computational social science, program evaluation, and survey methodology. Imai leads the Algorithm-Assisted Redistricting Methodology Project (ALARM) and is the author of Quantitative Social Science: An Introduction (Princeton University Press, 2017). Outside of Harvard, Imai had been teaching at Princeton University for 15 years and has served as the President of the Society for Political Methodology from 2017 to 2019. He is also Professor of Visiting Status in the Graduate Schools of Law and Politics at The University of Tokyo.

Konrad Kording runs his lab at the University of Pennsylvania. Konrad is interested in the question of how the brain solves the credit assignment problem and similarly how we should assign credit in the real world (through causality). In extension of this main thrust he is interested in applications of causality in biomedical research. Konrad has trained as student at ETH Zurich with Peter Konig, as postdoc at UCL London with Daniel Wolpert and at MIT with Josh Tenenbaum. After a decade at Northwestern University he is now PIK professor at UPenn.

Martin Lindquist is a Professor of Biostatistics at Johns Hopkins University. His research focuses on mathematical and statistical problems relating to functional Magnetic Resonance Imaging (fMRI). Dr. Lindquist is actively involved in developing new analysis methods to enhance our ability to understand brain function using human neuroimaging. He has published over 100 articles and serves on the editorial boards of several scientific journals both in statistics and neuroimaging. He is a fellow of the American Statistical Association. In 2018 he was awarded the Organization for Human Brain Mapping's 'Education in Neuroimaging Award' for teaching statistical issues to the neuroimaging community and the development of online classes that have taught fMRI methods to more than 80,000 students world-wide.

Maya L. Petersen is an Associate Professor of Biostatistics and Epidemiology and co-Director of the UC Berkeley-UC San Francisco Joint Program in Computational Precision Health. Her methodologic work focuses on the intersection of causal inference, machine learning, and non-parametric statistical inference, and on adaptive, cluster-randomized and sequentially randomized experimental designs. She applies these methods in areas including global health, community-based interventions, implementation science, and HIV treatment and prevention.

Julia Rohrer is a personality psychologist at Leipzig University. Her work covers a broad range of topics, including the effects of birth order, age patterns in personality, and the correlates and determinants of subjective well-being. Her methodological interests include causal inference and Open Science practices.