Jessica Hwang

Timeline

1. By 2014

   Statistics at Harvard

   Born in Washington, D.C., to Taiwanese immigrant parents, both scientists, she earns a BA and an MA in Statistics at Harvard University by 2014. As a teaching fellow for an introductory probability class, she is invited to co-author a statistics textbook with her professor.

2. 2014

   A Soros Fellowship

   In 2014, as a first-year PhD candidate in statistics at Stanford, she receives one of 30 Paul & Daisy Soros New American Fellowships. A member of the Statistics for Social Good working group, she plans to partner with advocacy groups and use statistics to address social problems.

3. 2017

   A Stanford teaching award

   In 2017, she and Ya Le receive Stanford's biennial Centennial Teaching Assistant Awards, given for outstanding instruction, service, and dedication by teaching assistants in the schools of Humanities and Sciences, Earth Sciences, and Engineering.

4. April 2017–March 2019

   The Climate Forecast Rodeo

   From April 2017 to April 2018, she and fellow Stanford PhD student Paulo Orenstein work with Microsoft researcher Lester Mackey and climatologist Judah Cohen on the Sub-Seasonal Climate Forecast Rodeo, a year-long real-time contest to predict temperature and precipitation in the western United States. By March 2019, the judging panel has awarded the team first prize in 2-to-4 week temperature forecasting, second prize in 4-to-6 week precipitation forecasting, and first prize again for temperature hindcasts.

5. September 2018

   Subseasonal forecasting with machine learning

   In September 2018, she posts "Improving Subseasonal Forecasting in the Western U.S. with Machine Learning" to arXiv as first author, with Paulo Orenstein, Judah Cohen, Karl Pfeiffer and Lester Mackey. The paper presents an ensemble of two regression models and releases the SubseasonalRodeo dataset.

6. 2019

   Introduction to Probability, second edition

   In 2019, Chapman & Hall publishes the second edition of Introduction to Probability, a 634-page textbook she writes with Harvard's Joseph K. Blitzstein while a graduate student in Stanford's statistics department.

7. 2022

   A NeurIPS Outstanding Paper

   In 2022, NeurIPS names Gradient Estimation with Discrete Stein Operators an Outstanding Paper; she co-authors it with Jiaxin Shi, Yuhao Zhou, Michalis Titsias and Lester Mackey. The paper introduces a variance reduction technique based on Stein operators for discrete distributions and uses it to build control variates for the REINFORCE leave-one-out estimator.

8. As of October 2026

   Lecturer in Data Science

   As of October 2026, she is a Lecturer in Data Science at Stanford University. Her courses include Data Narratives (DATASCI 120), Introduction to Probability Theory (STATS 117) and Probability Theory for Statistical Inference (STATS 118).