Quick Bio:
I am a postdoc fellow at
ETH Foundations of Data Science (ETH-FDS) in ETH Zürich under the supervision of
Prof. Peter Bühlmann. Previously, I obtained my PhD in the
Department of Statistics at UC Berkeley in 2019. My Phd study was advised by
Prof. Bin Yu. During my PhD, I am fortunate to also work with
Prof. Martin Wainwright and
Prof. Jack Gallant.
My main research interests lie on statistical machine learning, optimization and the applications in neuroscience. In particular, I am interested in domain adaptation, stability, MCMC sampling algorithms, convolutional neural networks and statistical problems that arise from computational neuroscience. Before my PhD study, I obtained my Diplome d'Ingénieur (Eng. Deg. in Applied Mathematics) at
Ecole Polytechnique in France.
News: I am excited to be joining the Department of Statistical Science at Duke University as an Assistant Professor in Spring 2021!
yuansi.chen at stat.math.ethz.ch
"It is necessary and true that all of the things we say in science, all of the conclusions, are uncertain, because they are only conclusions. They are guesses as to what is going to happen, and you cannot know what will happen, because you have not made the most complete experiments."
-- Richard P. Feynman