Valerie Chen
I'm a fifth year Machine Learning PhD student at Carnegie Mellon University advised by Ameet Talwalkar. I am also a visiting researcher at the NYU Center for Data Science with He He. I previously interned at Microsoft Research in the FATE (Fairness, Accountability, Transparency, and Ethics of AI) group with Q. Vera Liao and Jennifer Wortman Vaughan. My work has been recognized by a NSF Graduate Research Fellowship, CMU Presidential Fellowship, and Rising Stars in Data Science.
I'm interested in the principled design of human-AI teams. My research aims to (1) build interactive AI systems that allow humans to complete tasks more effectively and (2) design scalable, interactive evaluation paradigms of team set-ups.
Previously, I completed my BS in Computer Science at Yale University, where I worked with Zhong Shao and Abhinav Gupta. I have also spent time at IBM Research and the Naval Research Laboratory.
New! We recently launched Copilot Arena, a platform for code LLM evaluation in the wild! Download the extension in the VSCode Marketplace and check out our github repository.
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Selected Work See here for a full list.
Need Help? Designing Proactive AI Assistants for Programming
Valerie Chen, Alan Zhu, Sebastian Zhao, Hussein Mozannar, David Sontag, Ameet Talwalkar
Preprint, 2024
The RealHumanEval: Evaluating Large Language Models' Abilities to Support Programmers
Hussein Mozannar*, Valerie Chen*, Mohammed Alsobay, Subhro Das, Sebastian Zhao, Dennis Wei, Manish Nagireddy, Prasanna Sattigeri, Ameet Talwalkar, David Sontag
CHI TREW Workshop, 2024
Do LLMs exhibit human-like response biases? A case study in survey design
Lindia Tjuatja*, Valerie Chen*,
Sherry Tongshuang Wu, Ameet Talwalkar, Graham Neubig
TACL, 2024
Understanding the Role of Human Intuition on Reliance in Human-AI Decision-Making with Explanations
Valerie Chen,
Q. Vera Liao, Jennifer Wortman Vaughan, Gagan Bansal
CSCW, 2023
Perspectives on Incorporating Expert Feedback into Model Updates
Valerie Chen*,
Umang Bhatt*, Hoda Heidari, Adrian Weller, Ameet Talwalkar
Patterns, 2023
Use-Case-Grounded Simulations for Explanation Evaluation
Valerie Chen,
Nari Johnson, Nicholay Topin*, Gregory Plumb*, Ameet Talwalkar
NeurIPS, 2022
Interpretable Machine Learning: Moving From Mythos to Diagnostics
Valerie Chen*,
Jeffrey Li*,
Joon Sik Kim**,
Gregory Plumb**,
Ameet Talwalkar
Communications of ACM, 2022
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