I'm a Postdoctoral Research Associate in the Biostatistics Unit of the Medical Research Council at the University of Cambridge, working with
Sylvia Richardson. I completed a PhD in applied mathematics at the Center for research in economics and statistics (CREST), Paris supervised by Nicolas Chopin.
The topic was on high dimensional Bayesian computation, with a focus on improving Monte Carlo simulations for models with numerous parameters to be inferred.
From October 2017 to April 2018 I visited Pierre E. Jacob at the Department of Statistics at Harvard University.
I did my graduate studies in economics, mathematics and statistics under the double degree program of
Humboldt University Berlin and ENSAE ParisTech.
My research has applications in statistics and machine learning.
Below you can find a list of past and current projects.
My research interest lies in Monte Carlo methods and approximate inference in general and in particular Hamiltonian Monte Carlo, sequential Monte Carlo, quasi Monte Carlo, approximate Bayesian computation and variational inference. As a postdoc I am interested in computational methods for Bayesian inference in genomics.
I've had the pleasure of assisting in teaching several courses (i.e. teaching the tutorials), here are some.
- Mathematical Statistics - ENSAE ParisTech in Fall 2015, 2016 and 2017 with Nicolas Chopin
- Probability Theory - ENSAE ParisTech in Fall 2017 with Cristina Butucea
- Monte Carlo methods - ENSAE ParisTech in Spring 2016 and 2017 with Nicolas Chopin
- Introduction to statistics and econometrics - ENSAE ParisTech in Spring 2017 with Marco Cuturi
- Numerical Analysis - ENSAE ParisTech in Spring 2016 with Jérémie Jakubowicz
- Econometrics I - ENSAE ParisTech in Fall 2015 with Michael Visser
- Econometrics I - Humboldt University Berlin in Spring 2015 with Bernd Droge
I entirely held the following classes (lecture + tutorial):
- Python for Data Scientists - University of Technology of Troyes (France), Fall 2018 - Course material
- Spark for Data Scientists - University of Technology of Troyes (France), Fall 2018 - Course material
- Ph.D. Applied Mathematics, ENSAE and University Paris Saclay [2015-2018]
- M.Sc. Statistics, Humboldt University and Technical University, Berlin [2013-2015]
- Diploma Statistics and Economics, ENSAE, Paris [2012-2015]
- B.Sc. Economics, Humboldt University, Berlin [2010-2013]
- Improving approximate Bayesian computation via quasi Monte Carlo, Rencontre des jeunes statisticiens, Porquerolles, France, 4/5/2017
- Improving approximate Bayesian computation via quasi Monte Carlo, Young Statistician Meeting, UCL, London UK, 8/18/2016
- Improving approximate Bayesian computation via quasi Monte Carlo, Machine learning summer school, Tuebingen Germany, 6/26/2017
- Improving approximate Bayesian computation via quasi Monte Carlo, ABCruise, Helsinki Finland, 5/17/2016
- Hamiltonian Monte Carlo for Wishart distributions, International conference on Monte Carlo techniques, Paris France, 7/6/2016