Chacha Chen
陈诧姹
PhD student
Chicago Human+AI lab
Department of Computer Science, University of Chicago
Email: chacha@uchicago.edu
I am a PhD student in Computer Science at UChicago, advised by Chenhao Tan.
Research Focus
- Understanding and improving LLMs for specialized tasks such as radiology and knowledge-intensive tasks
- Human-AI collaboration
I am passionate about putting humans at the center of AI development, including how to understand the process of human-AI interaction and how we can better build/deploy AI tools that can actually be useful in real-world settings.
Selected Publications (Full List)
LLMs in Expert Domains
GPT-4V Cannot Generate Radiology Report Yet
Yuyang Jiang*, Chacha Chen*, Dang Nguyen, Benjamin M. Mervak, Chenhao Tan.
ML4H 2024, NAACL 2025. [Paper]
Yuyang Jiang*, Chacha Chen*, Dang Nguyen, Benjamin M. Mervak, Chenhao Tan.
ML4H 2024, NAACL 2025. [Paper]
The Use of Generative Search Engines for Knowledge Work and Complex Tasks
Siddharth Suri, Scott Counts, Leijie Wang, Chacha Chen, Mengting Wan, Tara Safavi, Jennifer Neville, Chirag Shah, Ryen W. White, Reid Andersen, Georg Buscher, Sathish Manivannan, Nagu Rangan, Longqi Yang.
An empirical analysis of large-scale user interactions with Bing Chat, a GPT-4 backed generative search engine.
[Preprint]
Siddharth Suri, Scott Counts, Leijie Wang, Chacha Chen, Mengting Wan, Tara Safavi, Jennifer Neville, Chirag Shah, Ryen W. White, Reid Andersen, Georg Buscher, Sathish Manivannan, Nagu Rangan, Longqi Yang.
An empirical analysis of large-scale user interactions with Bing Chat, a GPT-4 backed generative search engine.
[Preprint]
Human-AI Collaboration
Can Domain Experts Rely on AI Appropriately? A Case Study on AI-Assisted Prostate Cancer MRI Diagnosis
Chacha Chen, Han Liu, Ziyang Guo, Jiamin Yang, Benjamin M. Mervak, Bora Kalaycioglu, Grace Lee, Emre Cakmakli, Matteo Bonatti, Sridhar Pudu, Osman Kahraman, Gul Gizem Pamuk, Aytekin Oto, Aritrick Chatterjee, Jessica Hullman, Chenhao Tan.
FAccT 2025 [Paper]
Chacha Chen, Han Liu, Ziyang Guo, Jiamin Yang, Benjamin M. Mervak, Bora Kalaycioglu, Grace Lee, Emre Cakmakli, Matteo Bonatti, Sridhar Pudu, Osman Kahraman, Gul Gizem Pamuk, Aytekin Oto, Aritrick Chatterjee, Jessica Hullman, Chenhao Tan.
FAccT 2025 [Paper]
Machine Explanations and Human Understanding
Chacha Chen*, Shi Feng*, Amit Sharma, Chenhao Tan.
FAccT 2023, TMLR 2023, and Best Paper at HMCaT @ ICML 2022
[Paper] [Slides] [Video]
[Machine Explanations Human Studies Literature Survey]
Chacha Chen*, Shi Feng*, Amit Sharma, Chenhao Tan.
FAccT 2023, TMLR 2023, and Best Paper at HMCaT @ ICML 2022
[Paper] [Slides] [Video]
[Machine Explanations Human Studies Literature Survey]
Towards a Science of Human-AI Decision Making: A Survey of Empirical Studies
Vivian Lai, Chacha Chen, Q. Vera Liao, Alison Smith-Renner, Chenhao Tan.
FAccT 2023. [Paper] [Slides] [Survey Website]
Vivian Lai, Chacha Chen, Q. Vera Liao, Alison Smith-Renner, Chenhao Tan.
FAccT 2023. [Paper] [Slides] [Survey Website]
Learning Human-Compatible Representations for Case-Based Decision Support.
Han Liu, Yizhou Tian, Chacha Chen, Shi Feng, Yuxin Chen, Chenhao Tan.
ICLR 2023. [Paper]
Han Liu, Yizhou Tian, Chacha Chen, Shi Feng, Yuxin Chen, Chenhao Tan.
ICLR 2023. [Paper]
Applied Machine Learning
UNITE: Uncertainty-based Health Risk Prediction Leveraging Multi-sourced Data
Chacha Chen, Junjie Liang, Fenglong Ma, Lucas Glass, Jimeng Sun, Cao Xiao.
WWW 2021. [Paper] [Slides]
Chacha Chen, Junjie Liang, Fenglong Ma, Lucas Glass, Jimeng Sun, Cao Xiao.
WWW 2021. [Paper] [Slides]
Toward a Thousand Lights: Decentralized Deep Reinforcement Learning for Large-Scale Traffic Signal Control
Chacha Chen, Hua Wei, Nan Xu, Guanjie Zheng, Ming Yang, Yuanhao Xiong, Kai Xu, Zhenhui Li.
AAAI 2020. [Paper]
Chacha Chen, Hua Wei, Nan Xu, Guanjie Zheng, Ming Yang, Yuanhao Xiong, Kai Xu, Zhenhui Li.
AAAI 2020. [Paper]
Experience
Microsoft Research, Redmond, WA, US
Research Intern, Summer 2023
Amazon, AWS, Santa Clara, CA, US
Applied Scientist Intern, Summer 2022
IQVIA, Analytics Center of Excellence, Boston, MA, US
Machine Learning Research Intern, Summer 2020
