Hi there! I'm Tiffany.

I am a fourth-year PhD candidate in the UC Berkeley Statistics Department advised by Michael I. Jordan and Ryan Tibshirani. My work is supported by the NSF Graduate Research Fellowship.

I am broadly interested in developing methods and theory to address problems that emerge when machine learning models are applied to the real world. I am particularly excited about conformal prediction methods for interpretable model uncertainty, methods that are designed to operate in settings with distribution shift, and reasoning about the effects of strategic agents.

In summer 2024, I interned at Amazon NYC with Dean Foster and Omer Gottesman. Previously, I received an ScB in Applied Mathematics and an ScM in Computer Science from Brown University, where I was fortunate to work with Elizabeth Chen, Chip Lawrence, and Stephen Bach. I have also spent summers at Facebook and the Johns Hopkins University Applied Physics Laboratory.

Feel free to connect with me via email at tiffany_ding[at]berkeley[dot]edu, on Twitter (@tifding), or on LinkedIn.

News

May 2024: I started my internship at Amazon NYC.
April 2024: Our paper on how privacy arises endogenously in price discrimination games was accepted to FORC 2024.
April 2024: I passed my qualifying exam! Thanks to my chair, Jon McAuliffe, and my other committee members Ahmed Alaa, Rina Barber, Michael Jordan, and Ryan Tibshirani.
July 2023: I am co-organizing the Women in Machine Learning Un-Workshop @ ICML 2023.
June 2023: Our paper on performing class-conditional conformal prediction in limited-data, many-class settings was accepted to NeurIPS 2023.
July 2022: I presented a poster at the ICML 2022 Workshop on Distribution-Free Uncertainty Quantification.
January 2022: Our paper on weakly supervised learning using noisy partial labelers was accepted to AISTATS 2022.
December 2021: I presented a poster at the AGU 2021 Fall Meeting on my research (with Taehee Lee, Lorraine Lisiecki, and Charles Lawrence) about using Gaussian processes and state space models to infer historical sea levels.
May 2021: I was awarded the Jerome L. Stein Memorial Award for Undergraduate Excellence by Brown University's Dept. of Applied Math.
April 2021: I presented my honors thesis on applying Gaussian processes and state space models to infer historical sea levels using oxygen isotope records.
October 2020: I contributed a portrait of Dr. Sijue Wu (of the University of Michigan) to the Association of Women in Mathematics' EvenQuads playing cards project, which celebrates female mathematicians.
September 2020: Soryan Kumar and I won 2nd place in the Citadel East Coast Regional Datathon for our analysis of the optimal target audience for maximizing movie profitability.