About me
I am an associate professor in the Seminar for Statistics of ETH D-MATH. Previously, I was an assistant professor in the Department of Statistical Science at Duke University from Spring 2021 to Spring 2024. I was a postdoc fellow at ETH Foundations of Data Science (ETH-FDS) in ETH Zürich under the supervision of Prof. Peter Bühlmann. I obtained my PhD in the Department of Statistics at UC Berkeley in 2019. I was very fortunate to be advised by Prof. Bin Yu. During my PhD, I was also fortunate to work with Prof. Martin Wainwright and Prof. Jack Gallant. Before my PhD study, I obtained my Diplome d'Ingénieur (Eng. Deg. in Applied Mathematics) at Ecole Polytechnique in France.
My main research interests lie on statistical machine learning, MCMC sampling, domain adaptation and statistical challenges that arise in computational neuroscience.
In the news: Quanta Magazine article about the work on the KLS conjecture
For prospective students
- If you already have a master degree or are about to receive one, apply directly to the Zurich Graduate School of Mathematics for a position in the Department of Mathematics (two deadlines a year)
- Otherwise, you may consider applying to master programmes in D-MATH
For current ETHZ master students looking for a master thesis topic
You may take a look at the following topics on my Google Scholar and see if there is a fit
- Markov chain Monte Carlo sampling algorithms, theory and coding
- Statistical modeling in computational neuroscience: calcium imaging data from mice visual cortex