Andreas Bender

About

I am a postdoctoral researcher and lecturer at the Department of Statistics at LMU Munich at the Chair of Statistical Learning and Data Science and senior consultant at the Statistical Consulting Unit (StaBLab). I obtained Ph.D. (Dr.rer.nat.) in Statistics. After my Ph.D. I was a Postdoc at the Big Data Institute, University of Oxford, working on spatial analysis in the context of infectious disease mapping and Interim Professor at the Institute of Statistics, University of Ulm.
Currently, I am the Coordinator of the Machine Learning Consulting Unit and lead the focus group Machine Learning Survival Analysis.
Additionally, I am Co-founder of the Open Science Initiative in Statistics, PhD Program Coordinator at the Munich Center for Machine Learning , member of mlr-org and serve a 2-year term as staff representative at the Department of Statistics, LMU Munich.

Contact

Institut für Statistik

Ludwig-Maximilians-Universität München

Ludwigstraße 33

D-80539 München

Andreas.Bender [at] stat.uni-muenchen.de

(+49)89 2180 3351

Research Interests

You Can Find me on

Software/Projects

Teaching

References

  1. Hornung R, Nalenz M, Schneider L, Bender A, Bothmann L, Bischl B, Augustin T, Boulesteix A-L (2023) Evaluating Machine Learning Models in Non-Standard Settings: An Overview and New Findings. arXiv:2310.15108 [cs, stat].
    link | pdf
    .
  2. Hartl WH, Kopper P, Xu L, Heller L, Mironov M, Wang R, Day AG, Elke G, Küchenhoff H, Bender A (2023) Relevance of Protein Intake for Weaning in the Mechanically Ventilated Critically Ill: Analysis of a Large International Database. Critical Care Medicine.
    link
    .
  3. Hendrix P, Sun CC, Brighton H, Bender A (2023) On the Connection Between Language Change and Language Processing. Cognitive Science 47, e13384.
    link|pdf
    .
  4. Coens F, Knops N, Tieken I, Vogelaar S, Bender A, Kim JJ, Krupka K, Pape L, Raes A, Tönshoff B, Prytula A, Registry C (2023) Time-Varying Determinants of Graft Failure in Pediatric Kidney Transplantation in Europe. Clinical Journal of the American Society of Nephrology.
    link
    .
  5. Wiegrebe S, Kopper P, Sonabend R, Bischl B, Bender A (2023) Deep Learning for Survival Analysis: A Review.
    link|pdf
    .
  6. Dandl S, Bender A, Hothorn T (2022) Heterogeneous Treatment Effect Estimation for Observational Data using Model-based Forests. arXiv:2210.02836
    link|pdf
    .
  7. Ramjith J, Bender A, Roes KCB, Jonker MA (2022) Recurrent Events Analysis with Piece-Wise Exponential Additive Mixed Models. Statistical Modelling, 1471082X221117612.
    link|pdf
    .
  8. Beaudry G, Drouin O, Gravel J, Smyrnova A, Bender A, Orri M, Geoffroy M-C, Chadi N (2022) A Comparative Analysis of Pediatric Mental Health-Related Emergency Department Utilization in Montréal, Canada, before and during the COVID-19 Pandemic. Annals of General Psychiatry 21, 17.
    link|pdf
    .
  9. Fritz C, Nicola GD, Günther F, Rügamer D, Rave M, Schneble M, Bender A, Weigert M, Brinks R, Hoyer A, Berger U, Küchenhoff H, Kauermann G (2022) Challenges in Interpreting Epidemiological Surveillance Data - Experiences from Germany. Journal of Computational & Graphical Statistics.
  10. Rügamer D, Bender A, Wiegrebe S, Racek D, Bischl B, Müller C, Stachl C (2022) Factorized Structured Regression for Large-Scale Varying Coefficient Models. arXiv preprint arXiv:2205.13080.
    link|pdf
    .
  11. Kopper P, Wiegrebe S, Bischl B, Bender A, Rügamer D (2022) DeepPAMM: Deep Piecewise Exponential Additive Mixed Models for Complex Hazard Structures in Survival Analysis Advances in Knowledge Discovery and Data Mining, pp. 249–261. Springer International Publishing.
    link|pdf
    .
  12. Hartl WH, Kopper P, Bender A, Scheipl F, Day AG, Elke G, Küchenhoff H (2022) Protein intake and outcome of critically ill patients: analysis of a large international database using piece-wise exponential additive mixed models. Critical Care 26, 7.
    link|pdf
    .
  13. Pretzsch E, Heinemann V, Stintzing S, Bender A, Chen S, Holch JW, Hofmann FO, Ren H, Bösch F, Küchenhoff H, Werner J, Angele MK (2022) EMT-Related Genes Have No Prognostic Relevance in Metastatic Colorectal Cancer as Opposed to Stage II/III: Analysis of the Randomised, Phase III Trial FIRE-3 (AIO KRK 0306; FIRE-3). Cancers 14, 5596.
    link|pdf
    .
  14. Sonabend R, Bender A, Vollmer S (2022) Avoiding C-hacking When Evaluating Survival Distribution Predictions with Discrimination Measures. Bioinformatics 38, 4178–4184.
    link|pdf
    .
  15. Python A, Bender A, Blangiardo M, Illian JB, Lin Y, Liu B, Lucas TCD, Tan S, Wen Y, Svanidze D, Yin J (2021) A Downscaling Approach to Compare COVID-19 Count Data from Databases Aggregated at Different Spatial Scales. Journal of the Royal Statistical Society: Series A (Statistics in Society).
    link | pdf
    .
  16. Bauer A, Klima A, Gauß J, Kümpel H, Bender A, Küchenhoff H (2021) Mundus Vult Decipi, Ergo Decipiatur: Visual Communication of Uncertainty in Election Polls. PS: Political Science & Politics, 1–7.
    link|pdf
    .
  17. Fabritius MP, Seidensticker M, Rueckel J, Heinze C, Pech M, Paprottka KJ, Paprottka PM, Topalis J, Bender A, Ricke J, Mittermeier A, Ingrisch M (2021) Bi-Centric Independent Validation of Outcome Prediction after Radioembolization of Primary and Secondary Liver Cancer. Journal of Clinical Medicine 10, 3668.
    link|pdf
    .
  18. Python A, Bender A, Nandi AK, Hancock PA, Arambepola R, Brandsch J, Lucas TCD (2021) Predicting non-state terrorism worldwide. Science Advances 7, eabg4778.
    link|pdf
    .
  19. Kopper P, Pölsterl S, Wachinger C, Bischl B, Bender A, Rügamer D (2021) Semi-Structured Deep Piecewise Exponential Models. In: In: Greiner R , In: Kumar N , In: Gerds TA , In: Schaar M van der (eds) Proceedings of AAAI Spring Symposium on Survival Prediction - Algorithms, Challenges, and Applications 2021, pp. 40–53. PMLR.
    link|pdf
    .
  20. Küchenhoff H, Günther F, Höhle M, Bender A (2021) Analysis of the early COVID-19 epidemic curve in Germany by regression models with change points. Epidemiology & Infection, 1–17.
    link|pdf
    .
  21. Bender A, Rügamer D, Scheipl F, Bischl B (2021) A General Machine Learning Framework for Survival Analysis. In: In: Hutter F , In: Kersting K , In: Lijffijt J , In: Valera I (eds) Machine Learning and Knowledge Discovery in Databases, pp. 158–173. Springer International Publishing.
    link | pdf
    .
  22. Sonabend R, Király FJ, Bender A, Bischl B, Lang M (2021) mlr3proba: An R Package for Machine Learning in Survival Analysis. Bioinformatics.
    link|pdf
    .
  23. Günther F, Bender A, Katz K, Küchenhoff H, Höhle M (2020) Nowcasting the COVID-19 pandemic in Bavaria. Biometrical Journal.
    link|pdf
    .
  24. Guenther F, Bender A, Höhle M, Wildner M, Küchenhoff H (2020) Analysis of the COVID-19 pandemic in Bavaria: adjusting for misclassification. medRxiv, 2020.09.29.20203877.
    link|pdf
    .
  25. Bender A, Python A, Lindsay SW, Golding N, Moyes CL (2020) Modelling geospatial distributions of the triatomine vectors of Trypanosoma cruzi in Latin America. PLOS Neglected Tropical Diseases 14, e0008411.
    link|pdf
    .
  26. Bauer A, Bender A, Klima A, Küchenhoff H (2019) KOALA: a new paradigm for election coverage. AStA Advances in Statistical Analysis.
    link|pdf
    .
  27. Bender A, Bauer A (2018) coalitions: Coalition probabilities in multi-party democracies.
    link|pdf
    .
  28. Bender A, Groll A, Scheipl F (2018) A generalized additive model approach to time-to-event analysis. Statistical Modelling 18, 299–321.
    link|pdf
    .
  29. Bender A, Scheipl F (2018) pammtools: Piece-wise exponential Additive Mixed Modeling tools. arXiv:1806.01042 [stat].
    link| pdf
    .
  30. Bender A, Scheipl F, Hartl W, Day AG, Küchenhoff H (2018) Penalized estimation of complex, non-linear exposure-lag-response associations. Biostatistics.
    link|pdf
    .
  31. Hartl WH, Bender A, Scheipl F, Kuppinger D, Day AG, Küchenhoff H (2018) Calorie intake and short-term survival of critically ill patients. Clinical Nutrition.
    link
    .
  32. Pratschke S, Bender A, Boesch F, Andrassy J, Rosmalen Mvan, Samuel U, Rogiers X, Meiser B, Küchenhoff H, Driesslein D, Werner J, Guba M, Angele MK (2018) Association between donor age and risk of graft failure after liver transplantation: An analysis of the Eurotransplant database - a retrospective cohort study. Transplant International 0.
    link
    .
  33. Maierhofer T, Pfisterer F, Bender A, Küchenhoff H, Moerer O, Burchardi H, Hartl WH (2017) Kosten als Instrument zur Effizienzbeurteilung intensivmedizinischer Funktionseinheiten. Medizinische Klinik - Intensivmedizin und Notfallmedizin, 1–7.
    link
    .
  34. Brandl S, Falk W, Klemmt H-J, Stricker G, Bender A, Rötzer T, Pretzsch H (2014) Possibilities and Limitations of Spatially Explicit Site Index Modelling for Spruce Based on National Forest Inventory Data and Digital Maps of Soil and Climate in Bavaria (SE Germany). Forests 5, 2626–2646.
    link
    .
  35. Ruëff F, Vos B, Oude Elberink J, Bender A, Chatelain R, Dugas-Breit S, Horny H-P, Küchenhoff H, Linhardt A, Mastnik S, Sotlar K, Stretz E, Vollrath R, Przybilla B, Flaig M (2014) Predictors of clinical effectiveness of Hymenoptera venom immunotherapy. Clinical & Experimental Allergy 44, 736–746.
    link
    .
  36. Guillemot V, Bender A, Boulesteix A-L (2013) Iterative Reconstruction of High-Dimensional Gaussian Graphical Models Based on a New Method to Estimate Partial Correlations under Constraints. PLoS ONE 8, e60536.
    link
    .
  37. Kuppinger D, Hartl WH, Bertok M, Hoffmann JM, Cederbaum J, Bender A, Küchenhoff H, Rittler P (2013) Nutritional screening for risk prediction in patients scheduled for extra-abdominal surgery. Nutrition 29, 399–404.
    link
    .
  38. Boulesteix A-L, Bender A, Lorenzo Bermejo J, Strobl C (2012) Random forest Gini importance favours SNPs with large minor allele frequency: impact, sources and recommendations. Briefings in Bioinformatics 13, 292–304.
    link
    .
  39. Stüber AT, Coors S, Schachtner B, Weber T, Rügamer D, Bender A, Mittermeier A, Öcal O, Seidensticker M, Ricke J, others (2023) A Comprehensive Machine Learning Benchmark Study for Radiomics-Based Survival Analysis of CT Imaging Data in Patients With Hepatic Metastases of CRC. Investigative Radiology, 10–1097.
    link
    .