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.
- 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)
- Inference in Regression Discontinuity Designs with High-Dimensional Covariates, with Christoph Rothe (submitted) - R-Code
- Testing For a Parametric Baseline-Intensity in Dynamic Interaction Networks, with Enno Mammen and Wolfgang Polonik (submitted) - 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
- 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
- Summerterm 2022 (Leipzig University): Mathematische Statistik (Further Information on Moodle)
- Springterm 2019 (University of Mannheim): Econometrics of Networks