The team
Edwin van den Heuvel
Founder
Prof. Dr. Edwin van den Heuvel is professor in Statistics and dean of the department of Mathematics and Computer Science at TU/e.
Maurits Kaptein
Principal senior statistician
Prof. Dr. Maurits Kaptein is a professor of Applied Causality at the Technical University of Eindhoven and Co-founder and CEO of Scailable. Maurits his research focusses on statistical methods, sequential learning, and causal inference. Maurits is a (co-) author of several books, including the Springer book “Statistics for Data Scientists”. Maurits has published work in influential journals in the field such as the Journal of Machine Learning Research, the Journal of Statistical Software, and BMC Medical Research Methodology. Maurits is an active public speaker on topics ranging from the use of multi-armed bandit approaches in healthcare to the applications of AI models within the broader society.
Marta Regis
Principal statistician
Dr. Marta Regis is an assistant professor in biostatistics at Eindhoven University of Technology. Her expertise lies in models for repeated measurement data, including latent variable longitudinal models and intensive semi-periodic time series, such as physiological signals.
Richard Post
Principal statistician
Richard Post is an applied-driven mathematical statistician. He obtained his bachelor’s in mathematics and master’s in industrial and applied mathematics cum laude from the Eindhoven University of Technology (TU/e). In 2023, Richard obtained his PhD in statistics from TU/e under the supervision of prof. dr. Edwin van den Heuvel and prof. dr. Hein Putter (Leiden University Medical Center) with a dissertation titled “Causal effect heterogeneity: statistical formalization of the individual causal effect”. Richard’s research focuses on statistical theory to identify the individual causal effect distribution and the causal interpretation of effect estimates for time-to-event outcomes. Richard is an experienced teacher in statistics and has gained rich experience in interdisciplinary research by working with biochemists, geophysicists, epidemiologists, and medical doctors.
Stan Heidema
Statistician
Stan Heidema holds a Master of Science degree in Industrial and Applied Mathematics with a specialization in Statistics. Currently, he is a PhD candidate at Eindhoven University of Technology (TU/e) and the Teaching & Research Institute for Data Science Analytics (TRI-DSA). His research interests include methods in uncertainty quantification, outlier detection, and sequential statistics. His ongoing work involves the development of statistical and machine learning-based surveillance methods that utilize spatial-temporal detection techniques to identify outbreaks caused by travel-related infectious diseases.
Ivo Stoepker
Statistician
Ivo Stoepker holds a Master of Science degree in Industrial and Applied Mathematics specialized in statistics, and is currently a PhD candidate at Eindhoven University of Technology (TU/e). His current research focuses on hypothesis testing for faint effects – which is particularly relevant in anomaly detection contexts. He focuses on design of novel statistical methodology that can be employed flexibly and nonparametrically, while retaining statistical guarantees akin to parametric approaches.
Qinhao Wu
Data scientist
Qinhao Wu is a data scientist at the TRI-DSA of Eindhoven University of Technology (TU/e). He obtained his PhD degree in Medical Image Processing from the Department of Computer Science at the University of Manchester. His research interests cover texture analysis, machine learning and trustworthy artificial intelligence. He has rich experience in the medical/pharmaceutical area, including engineering and regulation compliance.
He works on research projects in the medical and pharmaceutical areas. Previously, he worked on the Rapid Microbiological Statistics project at TU/e as a full-stack software engineer to design the architecture and translate the statistical models into the TriMSA software for validating microbiological methods. This project was done in collaboration with three pharmaceutical companies as software users.