Thomas is Professor of Statistics at University of Regensburg and MRC Professor of Statistics and Programme Leader in the DART theme. His work has focused on developing and evaluating novel statistical methods for clinical studies. These methods are adapted for specific applications to ensure they can be used in the pharmaceutical industry and also in public sector research institutions. His current research focuses on model-based dose-finding trials as well as Master protocols.

He is actively engaged in national and international COVID-19 efforts as a Co-Investigator the RECOVERY trial, the early phase platform AGILE as well as the long COVID platform HEAL-COVID. 

Jonathan completed his PhD at LSHTM and subsequently held Research Fellow and Lecturer roles in the Medical Statistics department. He then took up a position in AstraZeneca's Statistical Innovation Group. Prior to rejoining LSHTM, he was a Reader in Statistics at the University of Bath. Jonathan's research has predominantly focused on the development on methods for handling missing data and measurement error. More recently, he has been working on the topic of 'estimands' in clinical trials, combining methods from causal inference and missing data.

Ellie is currently an NHIR Doctoral Fellow at the Imperial Clinical Trials Unit (ICTU). Their work focuses on the use of machine learning methods for discovering treatment effect heterogeneity in trials. Ellie joined ICTU in July 2019 as an NIHR Research Methods Summer Intern until September 2019.  Through the summer of 2020 they worked as the systematic review coordinator for the SCiPAD study before starting her Pre-doctoral Fellowship in October 2020. The first year of their fellowship was used to complete an MSc in Health Data Analytics and Machine Learning, during the second year the research causal machine learning methods for modelling conditional average treatment effects in trials. Since the end of their fellowship Ellie has worked on a similar project with the Alan Turing Institute and the MRC Clinical Trials Unit at University College London, and worked as a network meta-analysis statistician on topical treatments for Eczema at Imperial.

Haiyan Zheng is a CRUK PRC Fellow in Statistical Methodology at the University of Cambridge. She is passionate about efficient design and analysis of clinical trials, particularly in the field of precision medicine. She currently leads a three-year research programme to develop statistical methods that (1) simultaneously evaluate treatment effects in multiple subgroups, and (2) allow for mid-course adaptations in master protocol trials. 

Marta Bofill Roig is a postdoctoral researcher at the Institute for Medical Statistics and Center for Medical Data Science at the Medical University of Vienna. Her research is currently focused on methods and software for the design and analysis of platform trials, with particular interest in the use of non-concurrent control data. Marta graduated in Mathematics and did a Master in Statistics and Operations Research. She has a PhD in Statistics and Operations Research from the Universitat Politècnica de Catalunya, during which she worked on trial designs with multiple endpoints.

David Robertson is a Senior Research Associate at the MRC Biostatistics Unit, University of Cambridge, where he has been based since 2013. His research focuses on the development of novel methodology for the design and analysis of adaptive clinical trials. David held a Biometrika Trust Research Fellowship from 2018 - 2021, which explored questions around error rate control for clinical trial designs that test multiple hypotheses simultaneously. 

Annabel Webb is an early career statistician in the final year of her PhD in biostatistics at Macquarie University, Australia. Her PhD research focuses on developing novel analysis methods for complex time-to-event data, with a particular emphasis on interval censored data, time-varying covariate models, joint modelling and dynamic prediction. Annabel also works as a Biostatistician at the Cerebral Palsy Alliance Research Institute where she contributes to a variety of research projects, including developing prediction models for the early detection of cerebral palsy, and the design of clinical trials for evaluating early interventions for children at risk of cerebral palsy. 

Giorgos Bakoyannis is an Assistant Professor of Statistics at the Department of Statistics in Athens University of Economics and Business, Greece. He has received M.Sc. and Ph.D. degrees in Biostatistics from the National and Kapodistrian University of Athens in Greece.  Dr. Bakoyannis has served as a postdoctoral research fellow (2014-2015), Assistant Professor (2015-2022), and Associate Professor (2022-2023) in the Department of Biostatistics and Health Data Science at Indiana University, U.S.A. His research interests include nonparametric and semiparametric statistical methodology for survival and competing risks data, multistate models, statistical methodology for precision medicine, missing data, and causal inference.

Ronald is the head of the biostatistics group at the Oxford University Clinical Research Unit (Ho Chi Minh City, Vietnam) and Associate Professor at the Oxford University. His research interests include models for complex time-to-event data and complex longitudinal data, prediction based on time-updated marker values and causal inference. He (co)-authored around 200 peer reviewed scientific articles and wrote the book "Data analysis with competing risks and multiple states". He co-authored a highly cited tutorial on competing risks and multi-state models and has taught courses and tutorials on the analysis of competing risks data in over 10 countries.