Patrick Chao

Hello! I am a Statistics Ph.D. student at the Wharton school, University of Pennsylvania, gratefully advised by Edgar Dobriban. I am broadly interested in the statistical learning, diffusion models, distribution shift, adversarial attacks, and AI safety.

For my undergraduate education, I graduated from UC Berkeley, receiving a Bachelor's degree in Computer Science, Mathematics, and Statistics with honors. I was very fortunate to have been supervised by Will Fithian and Horia Mania.

Previously, I interned at Amazon AI, working on diffusion models for causality, and at Jane Street Capital as a trading intern.

Email  /  LinkedIn  /  Github

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Research
Adversarial Prompting for Black Box Foundation Models
Natalie Maus*, Patrick Chao*, Eric Wong, Jacob Gardner
Blog Post

Attacking foundation models like Stable Diffusion and GPT by creating unusual prompts and getting unexpected outcomes.

Interventional and Counterfactual Inference with Diffusion Models
Patrick Chao, Patrick Blöbaum, Shiva Kasiviswanathan

Using diffusion models to answer interventional and counterfactual queries by modeling observational data, achieving state-of-the-art performance.

AdaPT-GMM: Powerful and Robust Covariate-Assisted Multiple Testing
Patrick Chao, Will Fithian
Vignette | Talk Recording

A powerful and robust multiple testing method using covariates to model the local false discovery rate by fitting a Gaussian mixture model.

Different Definitions of Conic Sections in Hyperbolic Geometry
Patrick Chao, Jonathan Rosenberg
Involve Research Journal, 2018
arXiv

Showing the standard definitions of conic sections are no longer equivalent in hyperbolic geometry.

Teaching
Wharton Teaching Assistant: Intro to Business Statistics (STAT 1010), Intro to Statistics (STAT 1110), Sports Analytics (STAT 4010), Data Collection and Acquisition (STAT 4100/7100), Python for Data Science (STAT 7770) (2020-2023)
Berkeley Seal Teaching Assistant, CS189: Machine Learning, Spring & Fall 2019

Teaching Assistant, Data 100: Principles and Techniques of Data Science, Fall 2018




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Last updated February 2023.