CV and Research Interests
In general my research interests are mostly centred around the analysis of Statistical Models for Network Data, particularly, Semi and Nonparametric Methods, Dependence, Relational Event Models using counting
processes, and Bootstrap methods. In addition, I'm interested in Causal Inference, HighDimensional Statistics, Quantile Regression, Measurement Error Problems, Hawkes Processes and Survival Analysis. It is
particularly interesting if some of these areas overlap. I'm scientific member of the International Max Planck Research school (IMPRS) of the Max Planck Institut for
Mathematics in the Sciences, I'm a coorganizer of the Seminar for Statistical Learning and Probability/Dynamical Systems and 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 (20192020), at KU Leuven in the group of
Prof. Ingrid Van Keilegom (20202021) and at LSE in the group of
Prof. Qiwei Yao (20202021).
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 nonparametric 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 and PrePrints
Refereed Journals
 Testing For a Parametric BaselineIntensity in Dynamic Interaction Networks, with Enno Mammen and Wolfgang Polonik (Accepted at Journal of Business and Economic Statistics)  RCode
 Inference in Regression Discontinuity Designs with HighDimensional Covariates, with Christoph Rothe, The Econometrics Journal, Volume 26, Issue 2, May 2023, Pages 105123  RCode
 SemiParametric Estimation of Incubation and Generation Times by Means of Laguerre Polynomials, with Ingrid Van Keilegom, Journal of Nonparametric Statistics, 34:3, 570606, 2022  RCode
 Correlation bounds, mixing and mdependence under random timevarying network distances with an application to CoxProcesses, Bernoulli 27 (3) 1666  1694, August 2021  RCode
 Nonparametric inference for continuoustime event counting and linkbased dynamic network models, with Enno Mammen and Wolfgang Polonik, Electron. J. Statist. 13 (2) 2764  2829, 2019  RCode
Other Publications
ProgrammeCode
 The Rpackage QuantRegLaguerre can be downloaded here from github. It provides implementations for the quantile regression methodology used in the paper Efficient Quantile Regression under Censoring Using Laguerre Polynomials written by Ingrid Van Keilegom and myself. It contains functions for computing the estimator, performing crossvalidation, and finding the bootstrap estimate for the variance.
 The Rpackage HighDimRD which contains the methodology from Inference in Regression Discontinuity Designs with HighDimensional Covariates can be downloaded from the github repository HighDimRD.
 The Rcode used in the paper SemiParametric Estimation of Incubation and Generation Times by Means of Laguerre Polynomials is available on github in the repository SemiParametricLaguerre.
 R and Ccode which implements the procedures studied in my papers about counting processes on networks can be found on github in the repositories
EstimateEventNetwork and BaselineEstimation.
Online Seminar Talks
Teaching
 Summerterm 2024 (Leipzig University): Mathematische Statistik (Further Information on Moodle)
 Winterterm 2023/24 (Leipzig University): Causal Inference in Statistics
 Summerterm 2023 (Leipzig University): Mathematische Statistik
 Winterterm 2022/23 (Leipzig University): Statistical Network Analysis
 Summerterm 2022 (Leipzig University): Mathematische Statistik
 Springterm 2019 (University of Mannheim): Econometrics of Networks
