Jan Kapar
- Department: Statistical Methods in Epidemiology
- Unit: Emmy Noether Junior Research Group: Beyond Prediction - Statistical Inference
Education
Work Experience
- 2023: Research stay (5 months), Department of Human Health and Nutritional Sciences, University of Guelph
- since 2022: Doctoral Student Machine Learning, Faculty for Mathematics and Computer Science, Universität Bremen
- 2014 - 2015: Exchange Semester, Università degli Studi di Padova
- 2013 - 2016: M.Sc. Business Mathematics, Julius-Maxmilians-Universität Würzburg
- 2011 - 2013: B.Sc. Mathematics, Julius-Maxmilians-Universität Würzburg
Work Experience
- since 02/22: Doctoral Research Fellow, Leibniz BIPS
- 03/2017 - 01/2022: Consultant, Accenture GmbH
- 06/2016 - 09/2016: Intern, Accenture GmbH
- 11/2015 - 03/2016: Intern, DAIMLER AG
- 04/2013 - 07/2013: Student Assistant, Department of Mathematics, Julius-Maximilians-Universität Würzburg
Selected BIPS-Publications
Articles with peer review
- Golchian P, Kapar J, Watson DS, Wright MN. Missing value imputation with adversarial random forests-MissARF. Statistics in Medicine. 2026;45:3-5.
https://doi.org/10.1002/sim.70379 - Mendl-Heinisch C, Bittner N, Miller T, Dellani P, Bamberg F, Berger K, Bohmann P, Decker JA, Floel A, Greiser KH, Harries M, Kapar J, Keil T, Klett-Tammen C, Krist L, Kroncke T, Leitzmann M, Niendorf T, Peters A, Pischon T, Riedel O, Ringhof S, Schlett CL, Schulze MB, Wielputz MO, Wirkner K, Caspers S, Jockwitz C. Prediction of cognitive test scores: A comparison of brain structure, health, demographic and cognitive data across adulthood. GeroScience. 2026;
https://doi.org/10.1007/s11357-026-02232-9 Conference proceedings
- Kapar J, Koenen N, Jullum M. What's wrong with your synthetic tabular data? Using explainable AI to evaluate generative models. Cham. 2026.
https://doi.org/10.1007/978-3-032-08327-2_2 - Mensing D, Kapar J, Hirsch J, Günther M, Hahn H, Wright MN. Multimodal synthesis of MRI and tabular data with diffusion in a joint latent space via cross-attention. Vancouver, Canada. 2026.
https://doi.org/10.1117/12.3086603 - Vu BD, Kapar J, Wright MN, Watson DS. Autoencoding random forests. 2026.
https://tinyurl.com/autoencoding - Blesch K, Koenen N, Kapar J, Golchian P, Burk L, Loecher M, Wright MN. Conditional feature importance with generative modeling using adversarial random forests. Washington, D.C.. 2025.
https://doi.org/10.1609/aaai.v39i15.33712 - Dandl S, Blesch K, Freiesleben T, König G, Kapar J, Bischl B, Wright MN. CountARFactuals -- Generating plausible model-agnostic counterfactual explanations with adversarial random forests. Cham. 2024.
https://doi.org/10.1007/978-3-031-63800-8_5 - Watson DS, Blesch K, Kapar J, Wright MN. Adversarial random forests for density estimation and generative modeling. 2023.
https://proceedings.mlr.press/v206/watson23a.html Book chapters
- Wright MN, Burk L, Golchian P, Kapar J, Koenen N, Langbein S. Machine learning in epidemiology. New York. 2026.
https://doi.org/10.1007/978-1-4614-6625-3_81-1
For further publications please follow this link:
- Winter 2022/2023: Biometrical Methods (Tutorial)
The responsibility for the content of this page lies with Jan Kapar.