We have an excellent lineup of top-class invited speakers covering a diverse range of topics in statistical modelling.
Brendan Murphy | University College Dublin, Ireland
Homepage: people.ucd.ie/brendan.murphy
Talk title (provisional): An unsupervised record linkage approach using household information to enhance individual matching across different databases
Brendan Murphy is a Full Professor of Statistics at the University College Dublin, Ireland. He is a current Editor of the Annals of Applied Statistics and a former President of the Irish Statistical Association. His research spans mixture modelling, cluster analysis, network models, Bayesian methods, and computational statistics.
Ruth King | University of Edinburgh, UK
Homepage: www.ed.ac.uk/profile/ruth-king
Talk title (provisional): Conditional ecological individual heterogeneity models: Accounting for survivorship bias
Ruth King is the Thomas Bayes’ Chair of Statistics, Director of the Bayes Centre, and co-founder of the Centre for Statistics at the University of Edinburgh. She is also an elected Fellow of the Learned Society of Wales, former President of the International Biometrics Society British and Irish Region, and winner of the Royal Statistical Society Barnett Award. Her research interests are broadly in the area of ecological modelling, including state-space models, capture-recapture models, Bayesian inference, and missing data analysis. She is a co-author of the books “Bayesian Analysis for Population Ecology” and “Modelling Population Dynamics”.
Sonja Greven | Humboldt University of Berlin, Germany
Homepage: www.wiwi.hu-berlin.de/en/Professorships/vwl/statistik/team/grevenso
Talk title (provisional): additive density-on-scalar regression in Bayes Hilbert spaces with an application to gender economics
Sonja Greven is a Full Professor of Statistics at HU Berlin. She leading a number of projects funded by the DFG (German Research Foundation Research), including the “DeSBi: Fusing deep learning and statistics” AI Research Unit as Spokesperson; “Flexible density regression methods” as Principal Investigator; and “Statistical modeling using mouse movements to model measurement error and improve data quality in web surveys” as Joint Principal Investigator. Her research interests lie primarily in the areas of functional data analysis and longitudinal data analysis.
Daniele Durante | Bocconi University, Italy
Homepage: danieledurante.github.io/web/
Talk title (provisional): Bayesian modelling of criminal networks
Daniel Durante is an Associate Professor of Statistics in the Department of Decision Sciences at Bocconi University. He is currently leading the ERC Starting Grant NEMESIS on modelling criminal networks and the Italian PRIN (Project of National Interest) CARONTE on competing/co-evolving causes of death. His research covers network science, computational social science, and demography; and he recently won the prestigious COPSS Emerging Leader Award for his contributions in these areas.
Cynthia Rudin | Duke University, USA
Homepage: users.cs.duke.edu/~cynthia/
Talk title (provisional): simpler machine learning models for a complicated world
Cynthia Rudin is a Distinguished Professor of Computer Science at Duke University, and Director of the Interpretable Machine Learning Lab. She previously held positions at MIT, Columbia University, and New York University (NYU), and holds degrees from the University at Buffalo and Princeton University. She has received a variety of prestigious awards and honours throughout her career, most notably the Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity; this is the “Nobel Prize of AI” and carries a monetary award of €1M. Her research is focused on machine learning tools that help humans to make better decisions, through interpretable machine learning and its application to critical societal problems in healthcare, criminal justice, and energy grid reliability.
Ewout Steyerberg | University Medical Center Utrecht, Netherlands
Homepage: https://www.clinicalpredictionmodels.org/homepage/personal-information
Short course title (provisional): Evaluation of prediction models and AI algorithms
Ewout Steyerberg is the Medical Scientific Division Manager at the Julies Center for Health Sciences at University Medical Center Utrecht, having previously been a Full Professor of Clinical Biostatistics and Medical Decision Making at Leiden University and Erasmus MC. His research focuses on prediction models (regression analysis and machine learning), especially in the context of biostatistics, clinical epidemiology, and decision making. He is the author of the well-known book “Clinical Prediction Models”.