Dr. Alexander Kreiß

Contact

Email: alexander.kreiss@math.uni-leipzig.de
Phone: +49 (0) 341-9732-328
Office: A437, Augusteum
Office Hours: By appointment (just send me an email)

You can also find me on Github and Research Gate.

CV and Research Interests

I am a Juniorprofessor at Leipzig University in the Institute of Mathematics. In general my research interests lie in the asymptotic analysis of Semi- and Non-parametric Statistical Methods with a particular focus on Statistical Network Analysis, High-Dimensional Statistics, Dependent Data, Quantile Regression, Measurement Error Problems and Survival Analysis. I'm affiliated with the HKMetrics Network.

Before coming to Leipzig, I was a PostDoc at the University of Mannheim in the group of Prof. Christoph Rothe (2019-2020), at KU Leuven in the group of Prof. Ingrid Van Keilegom (2020-2021) and at LSE in the group of Prof. Qiwei Yao (2020-2021).
I've studied Mathematics with minor subject Electronics at TU Darmstadt (Bachelor 2012, Master 2015) and at the University of Bristol (Master 2014). From October 2015 to April 2019 I was a PhD student at Heidelberg University under the supervision of Prof. Enno Mammen (Heidelberg) and Prof. Wolfgang Polonik (UC Davis). In my thesis Local Maximum Likelihood Estimation of Time Dependent Parameters in Dynamic Interaction Networks I've studied non-parametric estimation of the parameter function in a model for interactions among actors in a network. The results of my thesis have been published in two papers (Electronic Journal of Statistics and Bernoulli, see below). I was member of the RTG 1953 from 2015 to 2018.

Current Projects

• Sparse Network Estimation Using Hawkes Processes (preliminary title), with Enno Mammen (Heidelberg University) and Wolfgang Polonik (UC Davis).
• Non-Parametric Quantile Regression under Censoring (preliminary title), with Ingrid Van Keilegom (KU Leuven).
• Autoregressive Networks (preliminary title), with Qiwei Yao (LSE)

Publications and Preprints

• Testing For a Parametric Baseline-Intensity in Dynamic Interaction Networks, with Enno Mammen and Wolfgang Polonik (submitted) - R-Code
• Inference in Regression Discontinuity Designs with High-Dimensional Covariates, with Christoph Rothe, The Econometrics Journal, 2022 - R-Code
• Semi-Parametric Estimation of Incubation and Generation Times by Means of Laguerre Polynomials, with Ingrid Van Keilegom, Journal of Nonparametric Statistics, 2022 - R-Code
• Correlation bounds, mixing and m-dependence under random time-varying network distances with an application to Cox-Processes, Bernoulli 27 (3) 1666 - 1694, August 2021 - R-Code
• Nonparametric inference for continuous-time event counting and link-based dynamic network models, with Enno Mammen and Wolfgang Polonik, Electron. J. Statist. 13 (2) 2764 - 2829, 2019 - R-Code

Programme-Code

• The R-package HighDimRD which contains the methodology from Inference in Regression Discontinuity Designs with High-Dimensional Covariates can be downloaded from the github repository HighDimRD.
• The R-code used in the paper Semi-Parametric Estimation of Incubation and Generation Times by Means of Laguerre Polynomials is available on github in the repository SemiParametric-Laguerre.
• R and C-code which implements the procedures studied in my papers about counting processes on networks can be found on github in the repositories Estimate-Event-Network and Baseline-Estimation.

Online Seminar Talks

• German Probability and Statistics Days, October 2021: Website - Video
• EcoDep Seminary, April 2021: Website - Video
• Bernoulli-IMS One World Symposium, August 2020: Website - Video

Teaching

• Winterterm 2022/23 (Leipzig University): Statistical Network Analysis (Further Information on Moodle)
• Summerterm 2022 (Leipzig University): Mathematische Statistik
• Springterm 2019 (University of Mannheim): Econometrics of Networks