Inria
Julie Josse is a senior researcher at Inria (national research center in digital science), leading the PreMeDICaL team in collaboration with Inserm (national research center in health). Her expertise lies in handling missing data, causal inference, and applying machine learning techniques to health data. Before joining Inria in 2020, she was a professor at École Polytechnique, where she also led the Master’s program in data science for business, in partnership with HEC Paris. Julie Josse has been a visiting researcher at institutions like Stanford University and Google Brain Paris, focusing on developing advanced statistical methods, particularly for personalized medicine. She is also known for her contributions to reproducible research and her open-source software development, including R packages like FactoMineR and missMDA. Josse’s current work integrates multi-source clinical data to improve decision-making in healthcare, especially for trauma patient management.
TU Wien
Eduard Gröller is Professor at the Institute of Visual Computing & Human-Centered Technology (VC&HCT), TU Wien, where he is heading the Research Unit of Computer Graphics. He is a scientific proponent and key researcher of the VRVis research center. The center performs applied research in visualization, rendering, and visual analysis. Dr. Gröller is Adjunct Professor of Computer Science at the University of Bergen, Norway. His research interests include computer graphics, visualization, and visual computing. He became a fellow of the Eurographics Association in 2009. Dr. Gröller is the recipient of the Eurographics 2015 Outstanding Technical Contributions Award and of the IEEE VGTC 2019 Technical Achievement Award.
CMU
Rebecca Nugent is the Stephen E. and Joyce Fienberg Professor of Statistics & Data Science, the Department Head for the Carnegie Mellon Statistics & Data Science Department, and an affiliated faculty member of the Block Center for Technology and Society. She received her PhD in Statistics from the University of Washington in 2006. Prior to that, she received her B.A. in Mathematics, Statistics, and Spanish from Rice University and her M.S. in Statistics from Stanford University. She was won several national and university teaching awards including the American Statistical Association Waller Award for Innovation in Statistics Education and serves as one of the co-editors of the Springer Texts in Statistics. She recently served on the National Academy of Sciences study on Envisioning the Data Science Discipline: The Undergraduate Perspective and is the co-chair of the current NAS study Improving Defense Acquisition Workforce Capability in Data Use. She is the Founding Director of the Statistics & Data Science Corporate Capstone program, an experiential learning initiative that matches groups of faculty and students with data science problems in industry, non-profits, and government organizations. She has worked extensively in clustering and classification methodology with an emphasis on high-dimensional, big data problems and record linkage applications. Her current research focus is the development and deployment of low-barrier data analysis platforms that allow for adaptive instruction and the study of data science as a science.