Hi, I'm Chaoran Chen
I’m a fourth-year PhD student in the Department of Computer Science and Engineering at the University of Notre Dame. I am co-advised by Dr. Toby Jia-Jun Li and Dr. Fanny Yanfang Ye. Before joining ND, I received my M.S. degrees in Educational Technology and Applied Learning Science from Carnegie Mellon University. I received my Bachelor's degree in Industrial Design from Tongji University.
My research lies at the intersection of Human-Computer Interaction, Usable Privacy and Security, and Large Language Models (LLMs). I use human-centered design methods to investigate the dual relationship between LLMs and privacy/security: the Privacy and Security of LLMs (i.e., risks and vulnerabilities introduced by the use of LLMs) and LLMs for Privacy and Security (i.e., how LLMs can be used as tools to improve user privacy and security). My work argues that novel interface and interaction designs are essential to bridge these two perspectives and to empower end users in navigating the shifting privacy and security landscape shaped by generative AI.
- 09/2025
- ✈️ Attending UIST 2025 in Busan, Korea, and will present our paper "Why am I seeing this: Democratizing End User Auditing for Online Content Recommendations." - 08/2025
- ✈️ Attending SOUPS 2025 in Seattle and will present our poster "The Obvious Invisible Threat: LLM-Powered GUI Agents' Vulnerability to Fine-Print Injections." - 08/2025
- 📃 Two co-authored papers accepted to the HAIPS@CCS workshop - 07/2025
- 💻 Started my research internship at Google as a Student Researcher. - 07/2025
- 📃 Our paper “Towards a Design Guideline for RPA Evaluation: A Survey of Large Language Model-Based Role-Playing Agents” has been accepted in ACL 2025 Findings.

Why am I seeing this: Democratizing End User Auditing for Online Content Recommendations
Chaoran Chen, Leyang Li, Luke Cao, Yanfang Ye, Tianshi Li, Yaxing Yao, Toby Jia-jun Li
In the Proceedings of the 38th Annual ACM Symposium on User Interface Software and Technology (UIST 2025)

Towards a Design Guideline for RPA Evaluation: A Survey of Large Language Model-Based Role-Playing Agents
Chaoran Chen, Bingsheng Yao, Ruishi Zou, Wenyue Hua, Weimin Lyu, Toby Jia-Jun Li, Dakuo Wang
Findings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL Findings 2025)

CLEAR: Towards Contextual LLM-Empowered Privacy Policy Analysis and Risk Generation for Large Language Model Applications
Chaoran Chen, Daodao Zhou, Yanfang Ye, Toby Jia-jun Li, Yaxing Yao
Proceedings of the 30th ACM Conference on Intelligent User Interfaces (IUI 2025)

Careful About What App Promotion Ads Recommend! Detecting and Explaining Malware Promotion via App Promotion Graph
Shang Ma, Chaoran Chen, Shao Yang, Shifu Hou, Toby Jia-Jun Li, Xusheng Xiao, Tao Xie, Yanfang Ye
Network and Distributed System Security Symposium ((NDSS 2025)

An Empathy-Based Sandbox Approach to Bridge Attitudes, Goals, Knowledge, and Behaviors in the Privacy Paradox
Chaoran Chen, Weijun Li, Wenxin Song, Yaxing Yao, Yanfang Ye, Toby Jia-jun Li
In the Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems (CHI 2024)

Symbolic Prompt Tuning Completes the App Promotion Graph
Zhongyu Ouyang, Chunhui Zhang, Shifu Hou, Shang Ma, Chaoran Chen, Chunhui Zhang, Toby Li, Xusheng Xiao, Chuxu Zhang, Yanfang Ye
Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2024)

ARDW: An Augmented Reality Workbench for Printed Circuit Board Debugging
Ishan Chatterjee, Tadeusz Pforte, Aspen Tng, Farshid Salemi Parizi, Chaoran Chen, Shwetak Patel
In the Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology (UIST 2022)[video]

Patterns for representing knowledge graphs to communicate situational knowledge of service robots
Shengchen Zhang, Zixuan Wang, Chaoran Chen, Yi Dai, Lyumanshan Ye, Xiaohua Sun
In the Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (CHI 2021)[video]

AI-Sketcher: A Deep Generative Model for Producing High-Quality Sketches
Nan Cao, Xin Yan, Yang Shi, Chaoran Chen
The thirty-third AAAI conference on artificial intelligence (AAAI 2019)