Curriculum Vitae

Education

• Ph.D in Biostatistics, University of Zurich, 03/2020–02/2023
• M.S. in Biostatistics, University of Zurich, Switzerland, 09/2018–02/2020
• B.S. in Molecular Medicine, University of Freiburg, Germany, 10/2015–06/2018

Work experience

• 03/2024–present Assistant professor of Statistics
  • Vienna University of Economics and Business
• 03/2023–02/2024 Postdoctoral researcher
  • University of Copenhagen
  • Collaborators: Prof. Niklas Pfister, Prof. Jonas Peters
  • Funded by a “Postdoc.Mobility” grant from the Swiss National Science Foundation on Distributional Instrumental Variables Estimation (DIVE)
• 04/2022–07/2022 Visiting PhD student
  • University of Copenhagen
  • Supervisor: Prof. Jonas Peters
• 03/2020–02/2023: PhD candidate in Biostatistics
  • University of Zurich, Zurich University of Applied Sciences
  • Supervisors: Prof. Beate Sick, Prof. Torsten Hothorn
• 11/2018–08/2019: Research assistant
  • Functional Genomics Center Zurich, University of Zurich, ETH Zurich
  • Supervisor: Dr. Witold Wolski
• 01/2017–08/2018: Research assistant
  • University of Freiburg
  • Supervisor: Prof. Oliver Schilling

Teaching Experience

Current teaching responsibilities

• Data Analytics (WU)

• Statistik (WU)

Student supervision

Master students

• Nicola Stella, 2024
  • Using anchor regression for out-of-distribution generalization of widely used risk prediction models
  • ETH Zurich, co-supervised with Olga Demler and Peter Bühlmann
• Andrea Götschi, 2022
  • Applications of ordinal neural network transformation models
  • University of Zurich, co-supervised with Beate Sick
• Maic Rakitta, 2021
  • Generalized linear anchor regression
  • ETH Zurich, co-supervised with Peter Bühlmann
• Tran Xuan Thanh Elsener, 2021
  • Hyperparameter tuning in linear anchor regression
  • University of Zurich, co-supervised with Beate Sick

Teaching experience

• STA406 Generalized Regression (UZH, FS19/20/21, lecturer/teaching assistant)

• STA408 Statistical methods in epidemiology (UZH, SS20, lecturer/teaching assistant)

• STA402/MAT924 Likelihood inference (UZH, FS19, teaching assistant)

• Physical chemistry for molecular medicine (ALU, SS18, teaching assistant)

Reviewing

Editorial responsibilities

• 03/2024–present: Associate Editor for Advances in Statistical Analysis

• 09/2022–present: Junior Editor for the Journal of Statistical Software

Peer review

Journals

• Journal of the Royal Statistical Society, Series B (Statistical Methodology)
• Electronic Journal of Statistics
• Journal of Computational and Graphical Statistics
• Statistical Methods in Medical Research
• Advances in Statistical Analysis

Conferences

• AISTATS 2024
• UAI 2024

Awards and Scholarships

• 12/2022: Postdoc.Mobility grant (Swiss National Science Foundation)
  • Title: Distributional Instrumental Variables Estimation (DIVE)
• 12/2021: GRC Travel Grant (University of Copenhagen, Host: Prof. Jonas Peters)
• 2015–2020: Full scholarship of the Academic Foundation of the German People
• 2015–2020: Full scholarship of the Lion’s Club Viersen e.V.

Languages

• English (Full professional proficiency)
• German (Native proficiency)
• Mandarin Chinese (HSK 4)
• French (Basic knowledge)

Software

• Programming languages
  • R, Bash, Julia, Python
• Miscellaneous
  • Git, SVN, make, LaTeX, knitr, Docker

For more projects, check out my GitHub profile.

Maintained R packages

Kook L (2024). “comets: Covariance Measure Tests for Conditional Independence.” R package available on GitHub and CRAN.

Kook L (2023). “tramicp: Model-Based Causal Feature Selection for General Response Types.” R package available on GitHub and on CRAN.

Kook L, Baumann PFM, Rügamer D (2022). “deeptrafo: Fitting Deep Conditional Transformation Models.” R package available on CRAN.

Kook L (2022). “tramvs: Optimal Subset Selection for Transformation Models.” R package available on CRAN.

Kook L, Tamasi B, Siegfried S, Pawel S, Hothorn T (2021). “tramnet: Penalized Transformation Models.” R package available on CRAN.

Contributed R packages

Rügamer D, Pfisterer F, Kook L, Baumann P, Kolb C (2022). “deepregression: Fitting Deep Distributional Regressions.” R package available on CRAN.

Kook L, Wolski W (2021). “prora: ORA, sigORA and GSEA Functionalities for Proteomic Data.” R package available on GitHub.

Contributed Python packages

Huang S, Kook L (2024). “pycomets: Covariance Measure Tests for Conditional Independence.” Python package available on GitHub.

Publications

My publications are also indexed on my Google Scholar profile.

Preprints

Kook L, Pfister N (2024). “Instrumental Variable Estimation of Distributional Causal Effects.” arXiv preprint arXiv:2406.19986. doi, pdf, GitHub.

Campanella G, Kook L, Häggström I, Hothorn T, Fuchs TJ (2022). “Deep conditional transformation models for survival analysis.” arXiv preprint arXiv:2210.11366. doi, pdf.

Kook L, Götschi A, Baumann PF, Hothorn T, Sick B (2022). “Deep interpretable ensembles.” arXiv preprint arXiv:2205.12729. doi, pdf, Software.

Methodology

Kook L, Baumann PFM, Dürr O, Sick B, Rügamer D (2024). “Estimating Conditional Distributions with Neural Networks using R package deeptrafo.” Journal of Statistical Software, 111(10), 1-36. doi, pdf, Software.

Kook L, Lundborg AR (2024). “Algorithm-agnostic significance testing in supervised learning with multimodal data.” Briefings in Bioinformatics, 25(6). doi, pdf, GitHub, CRAN.

Kook L, Saengkyongam S, Lundborg AR, Hothorn T, Peters J (2024). “Model-based causal feature selection for general response types.” Journal of the American Statistical Association. doi, pdf, GitHub, Software.

Kook L, Kolb C, Schiele P, Dold D, Arpogaus M, Fritz C, Baumann PFM, Kopper P, Pielok T, Dorigatti E, Rügamer D (2024). “How Inverse Conditional Flows Can Serve as a Substitute for Distributional Regression.” UAI 2024. doi.

Rügamer D, Kolb C, Weber T, Kook L, Nagler T (2024). “Generalizing Orthogonalization for Models with Non-linearities.” ICML 2024. doi.

Siegfried S, Kook L, Hothorn T (2023). “Distribution-Free Location-Scale Regression.” The American Statistician, 1-12. doi, pdf, Software.

Marmolejo-Ramos F, Tejo M, Brabec M, Kuzilek J, Joksimovic S, Kovanovic V, González J, Kneib T, Bühlmann P, Kook L, Briseño-Sánchez G, Ospina R (2022). “Distributional regression modeling via generalized additive models for location, scale, and shape: An overview through a data set from learning analytics.” WIREs Data Mining and Knowledge Discovery, e1479. doi, pdf.

Pawel S, Kook L, Reeve K (2023). “Pitfalls and potentials in simulation studies: Questionable research practices in comparative simulation studies allow for spurious claims of superiority of any method.” Biometrical Journal. doi, pdf, Software.

Rügamer D, Kolb C, Fritz C, Pfisterer F, Kopper P, Bischl B, Shen R, Bukas C, Barros de Andrade e Sousa L, Thalmeier D, Baumann PFM, Kook L, Klein N, Müller CL (2023). “deepregression: A Flexible Neural Network Framework for Semi-Structured Deep Distributional Regression.” Journal of Statistical Software, 105(1), 1–31. doi, pdf, Software.

Herzog L, Kook L, Götschi A, Petermann K, Hänsel M, Hamann J, Wegener S, Sick B (2022). “Deep conditional transformation models for functional outcome prediction after acute ischemic stroke.” Biometrial Journal. doi, pdf, GitHub.

Kook L, Sick B, Bühlmann P (2022). “Distributional Anchor Regression.” Statistics and Computing, 32(3), 39. doi, pdf, GitHub , Software.

Kook L, Herzog L, Hothorn T, Dürr O, Sick B (2022). “Deep and Interpretable Regression Models for Ordinal Outcomes.” Pattern Recognition. doi, pdf, Software.

Kook L, Hothorn T (2021). “Regularized Transformation Models: The tramnet Package.” The R Journal. doi, pdf, Software.

Biomedicine

Baumgartner P, Kook L, Altersberger VL, Gensicke H, Ardila-Jurado E, Kägi G, Salerno A, Michel P, Gopisingh KM, Nederkoorn PJ, Scheitz JF, Nolte CH, Heldner MR, Arnold M, Cordonnier C, Schiava LD, Hametner C, Ringleb PA, Leker RR, Jubran H, Luft AR, Engelter ST, Wegener S, the Thrombolysis F (2023). “Safety and effectiveness of IV Thrombolysis in retinal artery occlusion: A multicenter retrospective cohort study.” European Stroke Journal. doi, pdf.

Herzog L, Kook L, Hamann J, Globas C, Heldner MR, Seiffge D, Antonenko K, Dobrocky T, Panos L, Kaesmacher J, Fischer U, Gralla J, Arnold M, Wiest R, Luft AR, Sick B, Wegener S (2023). “Deep Learning Versus Neurologists: Functional Outcome Prediction in LVO Stroke Patients Undergoing Mechanical Thrombectomy.” Stroke. doi, pdf.

Schmidt MT, Studer M, Kunz A, Studer S, Bonvini JM, Bueter M, Kook L, Haile SR, Pregernig A, Beck-Schimmer B, Schläpfer M (2023). “There is no evidence that carbon dioxide-enriched oxygen before apnea affects the time to arterial desaturation, but it might improve cerebral oxygenation in anesthetized obese patients: a single-blinded randomized crossover trial.” BMC Anesthesiology, 23(1), 41. doi, pdf.

Fröhlich K, Brombacher E, Fahrner M, Vogele D, Kook L, Pinter N, Bronsert P, Timme-Bronsert S, Schmidt A, Bärenfaller K, Kreutz C, Schilling O (2022). “Benchmarking of analysis strategies for data-independent acquisition proteomics using a large-scale dataset comprising inter-patient heterogeneity.” Nature Communications, 13(1), 2622. doi, pdf.

Fahrner M, Kook L, Fröhlich K, Biniossek ML, Schilling O (2021). “A Systematic Evaluation of Semispecific Peptide Search Parameter Enables Identification of Previously Undescribed N-Terminal Peptides and Conserved Proteolytic Processing in Cancer Cell Lines.” Proteomes, 9(2). doi, pdf.

Ohmer M, Tzivelekidis T, Niedenführ N, Volceanov-Hahn L, Barth S, Vier J, Börries M, Busch H, Kook L, Biniossek ML, Schilling O, Kirschnek S, Häcker G (2019). “Infection of HeLa cells with Chlamydia trachomatis inhibits protein synthesis and causes multiple changes to host cell pathways.” Cellular microbiology, 21(4), e12993. doi, pdf.

Drendel V, Heckelmann B, Schell C, Kook L, Biniossek ML, Werner M, Jilg CA, Schilling O (2018). “Proteomic distinction of renal oncocytomas and chromophobe renal cell carcinomas.” Clinical proteomics, 15(1), 25. doi, pdf.

Saporito-Magriñá CM, Musacco-Sebio RN, Andrieux G, Kook L, Orrego MT, Tuttolomondo MV, Desimone MF, Boerries M, Borner C, Repetto MG (2018). “Copper-induced cell death and the protective role of glutathione: the implication of impaired protein folding rather than oxidative stress.” Metallomics, 10(12), 1743-1754. pdf.

Talks

Kook L (2024). “Instrumental variable estimation of distributional causal effects.” Invited talk, ICSDS, Nice.

Kook L (2024). “Instrumental variable estimation of distributional causal effects.” Invited talk, University of Limerick, Ireland.

Kook L (2024). “Instrumental variable estimation of distributional causal effects.” Invited talk (host: Stefan Feuerriegel), LMU Munich, Germany.

L (2024). “Algorithm-agnostic inference with multimodal data.” Invited talk, Bernoulli-ims 11th World Congress in Probability and Statistics, Bochum.

Kook L (2023). “Model-based causal feature selection for general response types.” Invited talk, UZH Econometrics Seminar.

Kook L (2023). “Distributional regression with neural networks in R.” Invited talk, CMStatistics Berlin.

Kook L (2023). “Invariant causal prediction for non-additive noise models.” Contributed talk, EMS Warsaw.

Kook L (2023). “Invariant causal prediction for non-additive noise models.” Contributed talk, NORDSTAT Gothenburg.

Kook L (2022). “Ensembling deep transformation models.” Invited talk, CMStatistics London.

Kook L, Herzog L, Dürr O, Hothorn T, Wegener S, Sick B (2021). “Interpretable effect estimates in semi-structured deep distributional regression.” ISCB’42, Lyon (online).

Kook L (2021). “Ordinal neural network transformation models.” Invited talk, LMU Munich (online).

Kook L, Herzog L, Grabner H, Wegener S, Sick B (2021). “Improving treatment decisions in acute stroke using deep-learning based risk analysis.” Freenovation Science Forum (online).