nadja.klein at
statistik.tu-dortmund.de |
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N.N. |
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From April 2023, I will be professor for Uncertainty Quantification and Statistical Learning at the Research Center Trustworthy Data Science and Security (UA Ruhr) and the Department of Statistics (Technische Universität Dortmund) and am principal investigator in several research projects.
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Prof. Dr. Nadja Klein | ![]() |
Group Lead | ___________ |
from Apr. 2023 | Full research professorship (W3) for Uncertainty Quantification and Statistical Learning at the Department of Statistics (TU Dortmund) and Research Center Trustworthy Data Science and Security |
Oct. 2021 - Apr. 2023 | Full professorship (W3) for Statistics and Data Science, Humboldt-Universität zu Berlin |
Nov. 2019 - Apr. 2023 | Emmy Noether Research Group Leader in Statistics & Data Science, Humboldt-Universität zu Berlin |
Oct. 2018 - Sep. 2021 | (Non-tenured) Assistant professorship (W1) for Applied Statistics, Humboldt-Universität zu Berlin |
Apr. 2018 - Oct. 2018 | (Non-tenured) Assistant professorship (W1) for Statistics, Universität zu Köln |
Jul. 2016 - Feb. 2018 | Postdoctoral Feodor Lynen Fellow of the Alexander von Humboldt Foundation, Melbourne Business School, University of Melbourne, Host: Prof. Dr. Michael Smith |
Oct. 2015 - Sept. 2016 | Postdoctoral Fellow of the Fonds Wetenschappelijk Onderzoek - Vlaanderen, supervisor: Prof. Dr. Gerda Claeskens (unpaid leave) |
Jan. 2015 - Mar. 2018 | Postdoctoral researcher, Georg-August-Universität Göttingen |
Jan. 2015 | Dr. rer. nat. in Mathematics, Georg-August-Universität Göttingen
Thesis title: Bayesian Structured Additive Distributional Regression, summa cum laude Supervisor: Prof. Dr. Thomas Kneib, defence: 03/12/2014 |
Mar. 2012 - Dec. 2014 | Doctoral studies in Mathematics PhD school Georg-August University School of Science (GAUSS) Georg-August-Universität Göttingen |
Jan. 2012 | Diploma in Mathematics with a minor in Physics, Universität Hamburg Thesis title: Statistische Lebenszeitanalyse von Flugzeuggeräten, sehr gut Supervisor: Prof. Dr. Holger Drees, diploma examination: 26/01/2012 |
Apr. 2007 - Feb. 2012 | Studies in Mathematics with a minor in Physics, Johannes-Gutenberg-Universität Mainz and Universität Hamburg |
2022 | Dr. Moritz Berger: Fortgeschrittene Methoden zur Modellierung von diskreten Ereigniszeiten (Universität Bonn) |
from 2023 | Ivan Ustyuzhaninov |
since Oct. 2022 | PhD Victor Medina-Olivares |
2021 - 2022 | PhD Stephen Johnson |
2021 - 2022 | Dr. Tim Kutzker |
from Feb. 2023 | PhD thesis of Clara Hoffmann: Calibrated Deep Response Distributions for Understanding Disease Progression (Technische Universität Dortmund) |
since Sep. 2022 | PhD thesis of Ekin Celikkan: Bayesian Machine Learning with Uncertainty Quantification for Detecting Weeds in Crop Lands from Low Altitude Remote Sensing (Humboldt-Universität zu Berlin & HEIBRiDS PhD Program) |
since Jun. 2022 | PhD thesis of Christian Schlauch: Continual Bayesian Deep learning with knowledge integration (Humboldt-Universität zu Berlin & Continental AG/KI Wissen) |
since Jan. 2020 | PhD thesis of Annika Strömer: Boosting copulas Boosting copulas (Universität Bonn, joint supervision with Prof. Mayr) |
since Dec. 2019 | PhD thesis of Paul Bach: Properties of non-local priors for distributional regression (Humboldt-Universität zu Berlin) |
since Oct. 2019 | PhD thesis of Lucas Kock: Deep Gaussian mixture models (Humboldt-Universität zu Berlin) |
2020 - 2022 | PhD thesis of Nicolai Hans: Boosting copulas in medicine (Humboldt-Universität zu Berlin) |
2017 - 2022 | PhD thesis of Hannes Riebl: Spatio-temporal distributional regression modelling (Georg-August-Universität Göttingen, joint supervision with Thomas Kneib) |
2017 - 2020 | PhD thesis of Isa Marques: Recent advances in continuous space spatial statistics: From Non-stationarity to spatial confounding (Georg-August-Universität Göttingen, joint supervision with Thomas Kneib) |
2016 - 2020 | PhD thesis of Manuel Carlan: Bayesian distributional regression: From effect selection priors in generalized additive models for location, scale and shape to Bayesian conditional transformation models (Georg-August-Universität Göttingen, joint supervision with Thomas Kneib) |
2022 | Nomination to AcademiaNet (Swiss National Science Foundation; the expert database for outstanding female academics), Profile |
2022 | Gustav-Adolf-Lienert-Award of the International Biometric Sociecty, German Region (IBS-DR) for the Biometrics paper Bayesian Variable Selection for Non-Gaussian Responses: A Marginally Calibrated Copula Approach |
2022 | Leadership Programme for Female Professors 2022 |
2022 | Awarded membership in Die Junge Akademie at the Berlin-Brandenburg Academy of Science and National Academy of Sciences Leopoldina |
2018 | ISBA Young Researcher Travel Support |
since 2016 | Awarded membership in the Humboldt network (by the Alexander von Humboldt Foundation) |
2016 | Feodor Lynen Fellowship for Postdoctoral Researchers of the Alexander von Humboldt Foundation |
2016 | NSF-ISBA Junior Travel Support Grant of the US National Science Foundation |
2015 | Wolfgang-Wetzel-Price 2015 of the German Statistical Society for the JASA paper Bayesian Generalized Additive Models for Location, Scale and Shape for Zero-Inflated and Overdispersed Count Data |
2014 | Award of the Georg-August-Universität Göttingen for outstanding dissertation Bayesian Structured Additive Distributional Regression |
2014 | Award of the Universitätsbund Göttingen for the dissertation Bayesian Structured Additive Distributional Regression |
Oct. 2013 - Oct. 2014 | Awarded Membership in the Dorothea Schlözer Mentoring Programme, Georg-August-Universität Göttingen |
since Jun. 2022 | Partner Membership at the Institute of Informatics (Humboldt-Universität zu Berlin) |
since Jan. 2022 | Partner Membership at the Institute of Mathematics (Humboldt-Universität zu Berlin) |
since Oct. 2021 | Member of International Biometric Society (IBS) |
since May 2021 | Member of International Society of Bayesian Analysis (ISBA) |
since Jul. 2020 | Member of Die Junge Akademie at the Berlin-Brandenburg Academy of Science and National Academy of Sciences Leopoldina |
since Aug. 2019 | Member of the Math+ Research Center and Berlin Mathematical School (BMS), TU Berlin, FU Berlin and HU Berlin |
since May 2019 | Member of the Integrative Research Institute on Transformations of Human-Environment Systems (IRI THESys), HU Berlin |
since Jan. 2019 | Member of the Berlin Doctoral Program in Economics and Management Science (BDPEMS) |
since Dec. 2018 | Member of Biostatnet |
since Oct. 2018 | Member of the Joint Commission of the Master in Statistics, Berlin |
since Apr. 2018 | Associate member of the DFG Research Training Group 2300 Enrichment of European beech forests with conifers: impacts of functional traits on ecosystem functioning |
since Nov. 2018 | Member of Berlin Economics Research Associates (BERA) |
since Apr. 2018 | Member of The German Statistical Society (DStatG) |
since Jan. 2018 | American Statistical Association (ASA) Early Career Member |
since Aug. 2017 | Member of The German Association of University Professors and Lecturers (DHV) |
since Jan. 2017 | Member of the Bayesian Analysis and Modeling Research Group, University of Melbourne |
Mar. 2015 - Mar. 2018 | Member of the Centre for Statistics, Georg-August-Universität Göttingen |
Oct. 2012 - Dec. 2014 | Associate member of the DFG Research Training Group 1644 Scaling Problems in Statistics |
2022 | Member of the Commission of the intermediate evaluation for the assistant professorship Industrial Economics of Prof Schweighöfer-Kodritsch |
since Nov. 2021 | Examination Board of the Master in Statistics, Berlin |
since Oct. 2018 | Member of the Joint Commission of the Master in Statistics, Berlin |
since Dec. 2021 | Liaison professor of the German Academic Scholarship Foundation |
since Nov. 2021 | Speaker of the Research Group Artificial Intelligence, Junge Akademie at the Berlin-Brandenburg Academy of Science and National Academy of Sciences Leopoldina |
2020 | Course on “Good Supervision” |
from 2023 | PI of two sub-projects in DFG Research unit Fusing Deep Learning and Statistics towards Understanding Structured Biomedical Data (sub-project P5, sub-project P6) |
since Aug. 2021 | Experiment (Volkswagenstiftung) |
since Sep. 2020 | Individual Research Grant Boosting Copulas (joint with Prof. A. Mayr, Universität Bonn, DFG) |
since Nov. 2019 | Leader of the Emmy Noether Research Group Regression Models Beyond the Mean - A Bayesian Approach to Machine Learning (DFG) |
2020 - 2021 | Berlin University Alliance Seed Fund (joint with Prof. D. Nott, National University of Singapore) |
Oct. 2019 - Sep. 2021 | Klaus Tschira boost fund (German Scholars Organization e.V.) |
Aug. 2019 - Jul. 2020 | Transferbonus with Newsenselab (Humboldt Innovations) |
Oct. 2017 - Apr. 2018 | RTG 2300 Enrichment of European beech forests with conifers: impacts of functional traits on ecosystem functioning (speaker: Christian Ammer; own role: principle investigator until 04/2018) |
Jul. 2016 - Jun. 2018 | Feodor Lynen fellowship of the Alexander von Humboldt Stiftung Multivariate Conditional Distributions (principle investigator: N. Klein) |
Paul Bach | ![]() |
PhD Student |
Guillermo Briseno-Sanchez | ![]() |
PhD Student |
Tim-Moritz Bündert | ![]() |
Research Assistant |
Ekin Celikkan | ![]() |
PhD Student |
Clara Hoffmann | ![]() |
PhD Student |
Maarten Jung | ![]() |
Research Assistant |
Lucas Kock | ![]() |
PhD Student |
Victor Medina-Olivares, PhD | ![]() |
Postdoctoral Researcher |
Christian Schlauch | ![]() |
PhD Student |
Bettina Schmidt | ![]() |
PhD Student |
Michael Stanley Smith | ![]() |
Mercator Fellow |
Ivan Ustyuzhaninov | ![]() |
Postdoctoral Researcher |
Annalena Weißert | ![]() |
Student Assistant |
My research interests broadly lie at the intersection of machine learning and traditional statistical methods. This includes Bayesian Computational Methods, Bayesian Deep Learning, Machine Learning, Smoothing, Regularization and Shrinkage, Distributional Regression, Network Analysis as well as Spatial Statistics.
I am principal investigator in the following research projects.
See my Google Scholar entries for a complete list. Below you find some key publications and recent working papers.
We offer Bachelor's and Master's theses at the intersection of Statistics and Machine Learning. Should you be looking for a thesis or project in these areas, please see here for a list of available topics.
A selection of completed theses at the chair can be found below.