Andrew Chin

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I am a Biostatistics PhD candidate at the Johns Hopkins Bloomberg School of Public Health, working with Aki Nishimura on Markov chain Monte Carlo methods for high dimensional data. During my time here, I also interned at Sandia National Laboratories, where I worked on sequential Monte Carlo methods for Bayesian optimal experimental design under Tommie Catanach.

Previously, I was a software engineer in the Carnegie Mellon Machine Learning Department with the Delphi Group (led by Ryan Tibshirani and Roni Rosenfeld), building pipelines and tools for COVID-19 surveillance and forecasting. Before that, I worked in industry as a product manager and software engineer at Datavant.

I received my Bachelor's and Master's degrees in statistics from UC Davis, where I studied large scale network data under James Sharpnack.

Research

Sticky Hamiltonian Monte Carlo by traveling in and out of an alternative universe
A. Chin, A. Nishimura
In progress

Bouncy Hamiltonian samplers: A unifying framework for Hamiltonian Monte Carlo and piecewise deterministic processes
A. Chin, A. Nishimura
arXiv | Preprint

hdtg: An R package for high-dimensional truncated normal simulation
Z. Zhang, A. Chin, A. Nishimura, M. A. Suchard
arXiv | Preprint

Real-time estimation of Covid-19 infections: Deconvolution and sensor fusion
M. Jahja, A. Chin, R. J. Tibshirani
Statistical Science | 2022

An open repository of real-time COVID-19 indicators
A. Reinhart, [et al., including A. Chin]
Proceedings of the National Academy of Sciences | 2021

Code

bayesbridge
Python package for Bayesian Sparse Regression.
Added GPU support and implementing additional sampling algorithms.
github | PyPI

hdtg
R package for sampling from high-dimensional truncated normal distributions.
Implemented Exact HMC algorithm of Pakman and Paninski in C++/Rcpp.
github | CRAN

covidcast
R and Python packages for accessing and visualizing COVIDcast data.
Core contributor and maintainer from 2020-2021.
github | PyPI | CRAN

Teaching

Advanced Statistical Computing
Teaching Assistant
JHU Bloomberg School of Public Health | 3rd Term 23-24

Real Analysis I
Teaching Assistant
JHU Whiting School of Engineering | Fall Term 22-23

Statistical Computing, Algorithm, and Software Development
Teaching Assistant
JHU Bloomberg School of Public Health | 3rd Term 22-23, 3rd Term 23-24

Statistical Methods in Public Health
Lead Teaching Assistant
JHU Bloomberg School of Public Health | 2nd Term 24-25

Statistical Methods in Public Health
Teaching Assistant
JHU Bloomberg School of Public Health | 4th Term 22-23, 1st Term 23-24, 2nd Term 23-24