I am an assistant professor in the Department of Statistical Science at Duke University. Previously, 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. 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
. Before my PhD study, I obtained my Diplome d'Ingénieur (Eng. Deg. in Applied Mathematics) at Ecole Polytechnique
My main research interests lie on statistical machine learning, MCMC sampling, optimization, domain adaptation and statistical challenges that arise in computational neuroscience.
yuansi.chen at duke.edu
Teaching: Fall 2021 -
"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