Sebastian Schmon,

DPhil (Oxon)

Welcome to my webpage. I am a Research Scientist in the Complexity Research team at Improbable. My research interests lie at the intersection of statistics, machine learning and probability theory. In particular, I am interested in constructing and analysing practical algorithms and simulation techniques for complex statistical or machine learning models such as intractable Bayesian models or large scale simulation engines. A list of publications can be found below. I obtained my DPhil (Oxford parlance for PhD) at the Department of Statistics of the University of Oxford under the supervision of Arnaud Doucet and George Deligiannidis.

As a consultant with several years of experience I have supported start-ups as well as large multinational companies to improve their analytical capabilites.

Past Teaching

University of Oxford

  • Applied Probability, 3rd year Mathematics (Michaelmas 2015)
  • Advanced Simulation, 4th year Mathematics and MSc Statistics (Hilary 2016, 2017, 2018)
  • Graphical Models, 4th year Mathematics and MSc Statistics (Michaelmas 2016, 2017, 2018)
  • Prelims: Probability, 1st year Mathematics (Michaelmas 2016)
  • Part A: Probability, 2nd year Mathematics (Michaelmas 2016)
  • Part A: Statistics, 2nd year Mathematics (Hilary 2017)

Free University Berlin

  • Statistics for Economists (2012, 2013, 2014), Introduction to probability and random variables, summary statistics, graphical data analysis
  • Statistical Inference (2012) Point estimation, large sample properties and limiting theorems, confidence sets and tests, linear regression
  • Statistical Modelling (2013) Generalised linear models, computational issues and implementation, application to economics.