Yuansi Chen

Yuansi Chen

Quick Bio:

I just joined the Department of Statistical Science at Duke University as an Assistant Professor in Spring 2021. 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.
My main research interests lie on statistical machine learning, sampling, 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.

yuansi.chen at duke.edu
Curriculum Vitae (in pdf)
Github



"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

Google Scholar

Recent Papers:

An Almost Constant Lower Bound of the Isoperimetric Coefficient in the KLS Conjecture, [GAFA][arXiv]
Yuansi Chen. Geometric And Functional Analysis (GAFA) 2021
Domain Adaptation Under Structural Causal Models, [arXiv][Code on Github]
Yuansi Chen, Peter Bühlmann. 2020, preprint
Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients, [JMLR][arXiv]
Yuansi Chen, Raaz Dwivedi, Martin Wainwright, Bin Yu. Journal of Machine Learning Research (JMLR) 2020
The DeepTune Framework for Modeling and Characterizing Neurons in Visual Cortex Area V4, [bioRxiv]
Reza Abbasi-Asl*, Yuansi Chen*, Adam Bloniarz, Michael Oliver, Ben Willmore, Jack Gallant, Bin Yu. Submitted to Proceedings of the National Academy of Sciences (PNAS)
Log-concave sampling: Metropolis-Hastings algorithms are fast, [JMLR][arXiv][Code on Github]
Yuansi Chen*, Raaz Dwivedi*, Martin Wainwright, Bin Yu. Journal of Machine Learning Research (JMLR) 2019
Fast MCMC Algorithms on Polytopes, [JMLR][arXiv][C++ Implementation on Github]
Yuansi Chen*, Raaz Dwivedi*, Martin Wainwright, Bin Yu. Journal of Machine Learning Research (JMLR) 2018

Papers with code:

Fast and Robust Archetypal Analysis for Representation Learning, [CVPR][arXiv][Code&Demo]
Yuansi Chen, Julien Mairal and Zaid Harchaoui. IEEE Computer Vision and Pattern Recognition (CVPR) 2014