Christian Hirsch

Christian Hirsch

Associate Professor for Data Science and Statistics

Aarhus University

Christian Hirsch

I am Associate Professor for Data Science and Statistics at Aarhus University, where I am studying random networks motivated from biology and health sciences via techniques from topological data analysis and stochastic geometry. I am a member of the Stochastics group at the Department of Mathematics. I am also affiliated with the AU DIGIT Centre and the AU Quantum Campus.

Before that, I was Assistant Professor at the University of Groningen and at the University of Mannheim. I was Postdoc at Aalborg University, at the LMU Munich and the WIAS Berlin. I received my PhD from Ulm University.


  • Statistical foundations of topological data analysis
  • Large deviations theory in stochastic geometry
  • Percolation theory of spatial random networks


  • PhD in Mathematics, 2014

    Ulm University

  • Diploma in Mathematics, 2010

    LMU Munich


Topological data analysis

Topological data analysis is based on an equally simple as intriguing principle. Leverage invariants from algebraic topology to gain novel insights into data. TDA is now applied in a wide variety of disciplines.

Large deviations

What is the probability that a random geometric graph in a sampling window has atypically few or atypically many edges or triangles? What are the sources leading to such rare events? These examples illustrate the core questions of large devations in geometric probability.

Spatial random networks

In the context of the Internet of Things and in 5G cellular networks, Device-to-Device (D2D) communication plays a key role. This technology aims to reduce the load on the base station by allowing users to communicate with one another, either directly or through several intermediate steps.


  • Postdocs
  • PhD theses
    • N.N. Lundbye (since 02/23). Statistical foundations of TDA
    • P. Juhasz (since 11/22). TDA-based models of evolving higher-order networks
    • D. Willhalm (05/20 - 04/24). Limit theory for spatial random networks
  • MSc theses
    • L. de Jonge (07/21). Absence of WARM percolation on geometric networks
    • Y. Couzinié (09/18). Sublinearly reinforced Pólya urns on graphs of bounded degree
    • F. Rudiger (09/18). Recurrence and transience of graphs generated by point processes
    • A. Hinojosa Calleja (08/16). Interference in ad-hoc telecommunication systems in the high-density limit
    • E. Rolly (06/16). Gibbs-Masse für Trajektorien von Nachrichten in einem Kommunikationsnetzwerk
    • A. Tóbiás (04/16). Highly dense mobile communication networks with random fadings
  • BSc theses
    • H.C. Hansen (01/24). Convex hull algorithms for the triangulation/construction of alpha complexes
    • B.H. Kristensen (06/23). Asymptotic normality of tessellation-based persistent Betti numbers
    • B. Buttenschøn (06/23). A law of large numbers for wide one-layer neural networks
    • L. Kriouar (07/21). Analysis of financial data with time series and persistent homology
    • H. Hong (07/21). Geometric and topological approaches to mode clustering
    • J. Langenbahn (12/19). Konvergenz des Pseudo-Marginalen MCMC Verfahren
    • H. Blocher (02/18). Poisson Matching
    • F. Brück (06/17). Percolation properties of Poisson graphs