Understanding Privacy Norms Around LLM-Based Chatbots: A Contextual Integrity Perspective
Proceedings of the 2025 AAAI/ACM Conference on AI, Ethics, and Society (AIES 2025). Acceptance rate: 32%.
User Privacy
The User Empowerment Lab studies the designs that allow companies to invasively collect user data and to expose users’ data to their friends and loved ones.
Publications
Trust-Enabled Privacy: Social Media Designs to Support Adolescent User Boundary Regulation
Proceedings of the 21st Symposium on Usable Privacy and Security (SOUPS 2025).
Privacy as Social Norm: Systematically Empowering Teen Privacy Management on Social Media
Proceedings of the ACM on Human-Computer Interaction (CSCW), 9(2):CSCW151, 2025.
Building the Beloved Community: Designing Technologies for Neighborhood Safety
Proceedings of the 2025 ACM Conference on Human Factors in Computing Systems (CHI 2025). Acceptance rate: 25%.
Best paper honorable mention (top 5%)
Tuning into the World: Designing Community Safety Technologies to Reduce Dysfunctional Fear of Crime
In Proceedings of the 2024 ACM Conference on Designing Interactive Systems (DIS 2024). Acceptance rate: 27%.
Let Kids Wonder, Question and Make Mistakes: How the Designers of Children’s Technology Think about Child Well-being
Proceedings of the 22nd Annual ACM Interaction Design and Children Conference (IDC 2023). Acceptance rate: 29%.
Deceptive Design Patterns in Safety Technologies: A Case Study of the Citizen App
Proceedings of the 2023 ACM conference on human factors in computing systems (CHI 2023).
Best paper award (top 1%)
Is Someone Listening? Audio Related Privacy Perceptions and Design Recommendations from Guardians, Pragmatists, and Cynics
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), 5(3):1-23, 2021.
A Privacy-Focused Systematic Analysis of Online Status Indicators
Proceedings on 20th annual Privacy Enhancing Technologies Symposium (PoPETS), 2020(3):384-403. Acceptance rate: 19%.
User Experiences with Online Status Indicators
Proceedings of the 2020 ACM conference on human factors in computing systems (CHI 2020). Acceptance rate: 24%.