| 2026 | CHI | Beyond Accuracy: Experts See AI Fact-Checks as Accurate but Less Useful. | Chenyan Jia, Apoorva Gondimalla, Angie Zhang, David Joseph Mullings, Alexander Boltz, Min Kyung Lee |
| 2026 | CHI | Contextualizing Datasets: Deepening Awareness of Data Biases through Critical Reflection of Civic Data. | Angie Zhang, Min Kyung Lee |
| 2025 | CHI | Gig2Gether: Datasharing to Empower, Unify and Demystify Gig Work. | Jane Hsieh, Angie Zhang, Sajel Surati, Sijia Xie, Yeshua Ayala, Nithila Sathiya, Tzu-Sheng Kuo, Min Kyung Lee, Haiyi Zhu |
| 2025 | CHI | Knowledge Workers' Perspectives on AI Training for Responsible AI Use. | Angie Zhang, Min Kyung Lee |
| 2024 | CHI | Data Probes as Boundary Objects for Technology Policy Design: Demystifying Technology for Policymakers and Aligning Stakeholder Objectives in Rideshare Gig Work. | Angie Zhang, Rocita Rana, Alexander Boltz, Veena Dubal, Min Kyung Lee |
| 2024 | CSCW | Worker Data Collectives as a means to Improve Accountability, Combat Surveillance and Reduce Inequalities. | Jane Hsieh, Angie Zhang, Seyun Kim, Varun Nagaraj Rao, Samantha Dalal, Alexandra Mateescu, Rafael Do Nascimento Grohmann, Motahhare Eslami, Haiyi Zhu |
| 2024 | CSCW | Empowering and Centering Impacted Stakeholders in AI Design. | Angie Zhang |
| 2023 | CHI | Stakeholder-Centered AI Design: Co-Designing Worker Tools with Gig Workers through Data Probes. | Angie Zhang, Alexander Boltz, Jonathan Lynn, Chun Wei Wang, Min Kyung Lee |
| 2022 | CHI | Algorithmic Management Reimagined For Workers and By Workers: Centering Worker Well-Being in Gig Work. | Angie Zhang, Alexander Boltz, Chun Wei Wang, Min Kyung Lee |
| 2021 | AIES | Participatory Algorithmic Management: Elicitation Methods for Worker Well-Being Models. | Min Kyung Lee, Ishan Nigam, Angie Zhang, Joel Afriyie, Zhizhen Qin, Sicun Gao |