معرفی
Pascal Kilian is a postdoctoral researcher at the Methods Center within the Faculty of Economics and Social Sciences at the University of Tübingen. His work lies at the intersection of machine learning, psychometrics, and social sciences, with applications in education and sports analytics.
- PhD in Mathematics, University of Tübingen (2018)
- BSc/MSc in Mathematics and Physics, University of Tübingen (2007–2012)
His research focuses on modeling human behavior through advanced statistical and machine learning techniques. Key areas include latent variable models, variational autoencoders, mixed-effects machine learning, and longitudinal data analysis. He applies these methods to problems such as predicting student dropout in mathematics and identifying talent in youth soccer.
The recent publications reflect a strong trend toward integrating deep learning with psychometric theory, particularly in modeling multidimensional performance data. His work increasingly bridges artificial intelligence and behavioral science, with emphasis on non-linear dynamic models and individualized forecasting.
He has received recognition for his doctoral work:
- Doctoral Award for Excellent PhD Thesis, University of Tübingen (Tübingen School of Education)
Kilian has been involved in externally funded research projects, including those supported by the Federal Ministry of Education and Research (BMBF) and the Deutsche Telekom Stiftung. While no formal advisees are listed, he collaborates closely with senior researchers such as Prof. Augustin Kelava and Dr. Judith Glaesser. He contributes to the development of the mixedML framework and supports the DFB's Talent Identification and Development (TID) program through scientific analytics.
He is affiliated with the Methods Center at the University of Tübingen, a hub for interdisciplinary methodological innovation in the social sciences, where he contributes to both applied research and method development in machine learning and psychometrics.
