Hi, I'm Chaoran Chen
I’m a third-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, Cybersecurity, Usable Privacy, and Large Language Models (LLMs). I use human-centered design methods to investigate the dual relationship between LLMs and privacy: how LLMs can help users better understand and manage their privacy (LLM for Privacy), and how privacy concerns should shape the design of LLMs themselves (Privacy for LLM). From building empathy-based sandbox environments that enable experiential privacy learning to developing contextual privacy risk assessments and real-time intervention tools, my work aims to transform LLMs from potential privacy threats into active privacy-enhancing agents. I also explore how emerging AI technologies, including generative models, can be responsibly designed to meet diverse human needs while safeguarding autonomy, transparency, and data security.
- 04/2025
- 📃 Attending CHI 2025 in Yokohama and will present our position paper at HEAL workshop - 03/2025
- 📃 Our paper “CLEAR: Towards Contextual LLM-Empowered Privacy Policy Analysis...” has been accepted in IUI 2025. - 10/2024
- 🇩🇪 Worked as a research intern at the Max Planck Institute for Security and Privacy in Bochum, Germany, under the mentorship of Abraham Mhaidli. - 08/2024
- 📃 Our paper “Careful About What App Promotion Ads Recommend! ...” has been accepted in NDSS 2025. - 05/2024
- 📃 Attended CHI 2024 in Hawaii and presented our paper...

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)

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
Arxiv preprint

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

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)

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)

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)