Profile
Abstract
Since 2022 I'm Junior Professor for Statistics at the Institute of Mathematics of Leipzig University, where I am part of the Stochastics group. There I conduct my reserach on the statistical analysis of network data (cf. Research Profile). Furthermore, I teach classes about mathematical statistics, statistcal network analysis and causal inference for students of the Diploma programs in mathematics and ecnomical mathematics. I also supervise their Diploma thesis.
Before coming to Leipzig I've had PostDoc positions at The London School of Economics and Political Science (UK), KU Leuven (Belgium), and Mannheim University. I've started my academic career at Heidelberg University, where I did my PhD in 2019 under the supervision of Enno Mammen.
Professional career
 10/2018  01/2020
Academic Employee at University of Mannheim  02/2020  06/2021
Academic Employee at KU Leuven  07/2021  03/2022
Research Officer at The London School of Economics and Political Science (LSE)  since 04/2022
Juniorprofessor for Statistics at Leipzig University
Education
 10/2015  04/2019
PhD at Heidelberg University
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.
 Rothe, C.; Kreiß, A. G.Inference in Regression Discontinuity Designs with HighDimensional CovariatesThe Econometrics Journal. 2022.
 Mammen, E.; Polonik, W.; Kreiß, A. G.Nonparametric inference for continuoustime event counting and linkbased dynamic network modelsElectronic Journal of Statistics. 2019. 13 (2). pp. 2764–2829.
 Kreiß, A. G.Correlation bounds, mixing and mdependence under random timevarying network distances with an application to CoxProcessesBernoulli. 2021. 27 (3). pp. 1666–1694.
 Kreiß, A. G.; Van Keilegom, I.SemiParametric Estimation of Incubation and Generation Times by Means of Laguerre PolynomialsJournal of Nonparametric Statistics. 2022. 34 (3). pp. 570–606.
 Mammen, E.; Polonik, W.; Kreiß, A. G.Testing For Global Covariate Effects in Dynamic Interaction Event NetworksJournal of Business & Economic Statistics. 2023.

Statistical Network Analysis
Aim of this course is to discuss problems relating to statistical network analysis. Networked data can for example appear in the anaylsis of social networks or economic applications. Possible topics are: Descriptive statistics of networks, networksampling, models for network data, clustering. The concenpts of the lectures will be illustrated through examples.
The first half of the course is a lectureclass, the second half of the course is a seminar.

Mathematical Statistics
In the first part of the course we want to understand the general, asymptotic theory of estimators in parametric models: We consider maximum likelihood estimation and show that it is optimal in a certain sense.
In the second part we study linear models and their extensions (generalised linear models and socalled random effects). Those play an important role in many applications.
In the last part of the course we discuss nonparametric kernel estimators.

Causal Inference in Statistics
It is often of interest to understand if one variable is causal for another, e.g., is revising for an exam causal for the grade. The main objective of this course is to understand when estimators allow for this interpretation. To answer these and related questions we will discuss docalculus and often used concepts like the potential outcomes framework, instrumental variables and differencesindifferences.
Research fields
Mathematics
Specializations
Ich beschäftige mich hauptsächlich mit der statistischen Analyse von Netzwerkdaten. Außerdem interessiere ich mich für nichtparametrische Probleme.
Contact for media inquiries
Phone: 03419732328