Martin Lindquist is Professor of Biostatistics at Johns Hopkins University. His research focuses primarily on statistical problems relating to functional magnetic resonance imaging (fMRI). He is actively involved in developing new analysis methods to enhance our ability to understand brain function using human neuroimaging, and has a long-standing interest in assessing the reliability of various neuroimaging measures. He has published over 50 articles, serves on the editorial boards of several scientific journals, and is a Fellow of the American Statistical Association.

Malcolm MacLeod is Professor of Neurology and Translational Neurosciences at the University of Edinburgh, Honorary Consultant Neurologist at NHS Forth Valley, and an affiliate member of the Meta-Research Innovation Center (METRICS) at Stanford University. He serves as a member of the UK Home Office Animals in Science Committee and a Commissioner at the UK MHRA Commission for Human Medicines. With David Howells, he was founding co-ordinator of the Collaborative Approach to Meta-Analysis and Review of Animal Data from Experimental Studies (CAMARADES, www.camarades.info). His research focusses on the development of novel treatments for neurological diseases. This work includes: 1) clinical trials in stroke; 2) the application of systematic review and meta-analysis of preclinical data to selecting drugs to take forward to clinical trial in stroke, multiple sclerosis, spinal cord injury and amyotrophic lateral sclerosis; and 3) the development of novel interventions which might improve the rigour of published preclinical research. He has a long-standing interest in factors influencing the robustness of scientific findings, with a particular focus on the impact of risks of bias such as the failure to randomise treatment allocations, blind animal handling and outcome assessment, or report outcome in animals excluded from analysis.

Stan Lazic is Co-founder and Chief Scientific Officer at Prioris.ai Inc. – a company building probabilistic machine learning models in the pharmaceutical, life science, and healthcare sectors. Previously, he was Associate Director in Statistics and Machine Learning at AstraZeneca and spent ten years in the pharmaceutical industry. He has a PhD in Neuroscience and Master’s in Computational Biology from the University of Cambridge and has written a book on experimental design for biologists. He is on the Advisory Board of the UK Reproducibility Network and his research interests include the design and analysis of biological experiments, improving the reproducibility of biomedical research, and novel applications of Bayesian methods.

Eric-Jan Wagenmakers is Professor at the Psychological Methods Unit at the University of Amsterdam and Honorary Professor at the Experimental Psychology Unit of the University of Groningen. He has promoted the preregistration of analysis plans in order to separate what is pre-planned from what is post-hoc, as well as the use of replication studies, sometimes in the form of adversarial collaborations. He has outlined the limitations of traditional inference methods (i.e., p-values and confidence intervals) and developed and promoted Bayesian inference procedures as a useful alternative. These are described in a coursebook (Bayesian Cognitive Modeling: A Practical Course, Lee & Wagenmakers, 2013) and form an integral part of JASP, an open source statistical software package that allows users to execute Bayesian hypothesis tests with ease (“SPSS done right“). He is a past president for the Society of Mathematical Psychology and has published over 160 articles in international peer-reviewed journals. He has received several awards and grants, including the William K. Estes Early Career Award, the Paul Bertelson Early Career Award, and an ERC consolidator grant.

William Browne has been Professor of Statistics within the Graduate School of Education at the University of Bristol since 2014. Prior to that he was Professor of Biostatistics in the School of Veterinary Sciences, also at Bristol. In March 2016 he became the first director of the Bristol Data Institute. He also co-directs the Centre for Multilevel Modelling. His research focuses on statistical methods and software development, in particular random effect (multilevel) modelling and Monte Carlo Markov chain methods, along with application of such methods in diverse fields, including education, veterinary science, animal behavior and ecology. He has written software (MLPowSim) for sample size calculations in random effect models and was an author of the ARRIVE guidelines for reporting the results of animal experiments. His methodology/software development research has been funded by the UK’s ESRC where his current grant has a strand on reproducibility of statistical analyses. His more applied collaborative work has been funded by BBSRC, EPSRC, NERC, RSPCA and Welcome Trust amongst others.

Marcus Munafò is Professor of Biological Psychology in the School of Experimental Psychology at the University of Bristol, Director of the Tobacco and Alcohol Research Group, and an affiliate member of the Meta-Research Innovation Center (METRICS) at Stanford University. His group is part of the UK Centre for Tobacco and Alcohol Studies, and the Medical Research Council Integrative Epidemiology Unit at the University of Bristol. His research focuses on understanding pathways into, and the consequences of, health behaviors and mental health, with a particular focus on tobacco and alcohol use. This work includes: 1) observational and genetic epidemiology; 2) the laboratory study of cognitive and neurobiological mechanistic pathways; and 3) the development of novel individual- and population-level interventions that target these mechanisms. He has received a number of awards, including the British Psychological Society Health Psychology Early Career Award, the Society for Research on Nicotine and Tobacco Young Investigator Award, an American Cancer Society Union Internationale Contre Cancer Fellowship, the European College of Neuropsychopharmacology Fellowship Award, the British Association of Psychopharmacology Award, and the British Association of Psychopharmacology Cambridge Cognition Award. He has a long-standing interest in factors influencing the robustness of scientific findings, with a particular focus on the impact of low statistical power, and the incentive structures that shape the behavior of scientists.

Glyn Lewis is Professor of Psychiatric Epidemiology at University College London Division of Psychiatry. His main research interests are in the public health and epidemiology of psychiatric disorder. He trained in psychiatry at the Maudsley Hospital and Institute of Psychiatry, UK and in epidemiology at the London School of Hygiene and Tropical Medicine. His research involves identifying factors that are possible causal factors for depression, anxiety and schizophrenia. He also carries out randomised controlled trials concerned with the management of depression in primary care, investigating both psychological and pharmacological treatments. He has an interest in how research findings can be applied to clinical practice and in teaching clinicians about critical appraisal of the scientific literature.