Julian G. Gerstenberg

During WS22/23 & SS23 at Philipps-Universität Marburg, interim professor in Probability and Statistics

DFG Project: Exchangeability Theory of ID-Based Data Structures with Applications in Statistics

Interests: probability, statistics, machine learning, data structures, software, python, logic and category theory
Research: nonparametric statistics and machine learning, exchangeability and data structure theory
Consultation: statistics, data modeling, mathematical modeling, python
For all: if you are interested to get in touch because of research or are interested in consultation, please send me an email!
Contact information: here

Publications, Preprints and in Preperation

• On solutions of the distributional Bellman equation
  J.Gerstenberg, R.Neininger, D.Spiegel, Electronic Research Archive, Volume 31, Issue 8: 4459-4483 (2023)
  
• Cramér-von-Mises tests for the distribution of the excess over a confidence level
  D.Gaigall, J. Gerstenberg, Journal of Nonparametric Statistics, 1-33, (2023)
  
• Exchangeable Laws in Borel Data Structures
  J.Gerstenberg, arXiv:2208.10667 (2022)
  
• Empirical process of concomitants for partly categorial data and applications in statistics
  D. Gaigall, J.Gerstenberg, H.Trinh, Bernoulli 28 (2) 803-829. DOI: 10.3150/21-BEJ1367 (2022)
  
• Exchangeable interval hypergraphs and limits of ordered discrete structures
  J.Gerstenberg, Annals of Probability, Vol.48, No.3, 1128-1167 (2020)
  
• General erased-word processes: Product-type filtrations, ergodic laws and Martin boundaries
  J.Gerstenberg, Stochastic Processes and their Applications, Vol.130, Iss.6, 3540-3573 (2020)
  
• Austauschbarkeit in Diskreten Strukturen: Simplizes und Filtrationen
  J. Gerstenberg, Dissertation, Leibniz Universität Hannover (2018)
  
• A boundary theory approach to de Finetti's theorem
  J.Gerstenberg, R.Grübel, K.Hagemann, arXiv:1610.02561 (2016)
  
• Algorithms for approximating solutions of the distributional Bellman equations, in preperation
  
• Confidence levels vs. thresholds: a study in tail estimation, in preperation
  

Positions

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Philipps-Universität Marburg
Oct 22 - Sep 23

Professurvetretung Stochastik

Goethe Universität Frankfurt
May 20 - Sep 22

Partially funded by DFG project "Exchangeability Theory of ID-Based Data Structures with Applications in Statistics" (502386356)

PostDoc with Prof. Ralph Neininger at Institut of Mathematics, Stochastics and Finance

AMAI GmbH
April 2019 - May 2020

Data scientist, development and integration of machine learning solutions

Leibniz Universität Hannover
Oct 2014 - April 2019

PhD student & PostDoc with Prof. Rudolf Grübel at Institut of Mathematical Stochastics

Teaching

• SS 2023: Measure and Integration theory (lecture, math, Marburg), Asymptotic nonparametric statistics (lecture, math, Marburg)
• WS 2022/23: Elementare Stochastik (lecture, many courses, Marburg), Ergodic theory (lecture, math, Marburg)
• WS 2021/22: Supervision of students (theses, math, Frankfurt), organization of lectures (Frankfurt)
• SS 2021: Selected Topics from Machine Learning (seminar, math, Frankfurt)
• WS 2020/21:Introduction to Theory and Application of Machine Learning (lecture, math, Frankfurt)
• WS 2018/19: Stochastics A (lecture, computer science, Hannover)
• SS 2018: Markov chains (lecture, math, Hannover)

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