| Visualizing Privacy-Utility Trade-Offs in Differentially Private Data Releases P Nanayakkara, J Bater, X He, J Hullman, J Rogers Proceedings on Privacy Enhancing Technologies 2022, 2022 | 58 | 2022 |
| REFORMS: Consensus-based Recommendations for Machine-learning-based Science S Kapoor, EM Cantrell, K Peng, TH Pham, CA Bail, OE Gundersen, ... Science Advances 10 (18), eadk3452, 2024 | 54* | 2024 |
| The worst of both worlds: A comparative analysis of errors in learning from data in psychology and machine learning J Hullman, S Kapoor, P Nanayakkara, A Gelman, A Narayanan Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society, 2022 | 51 | 2022 |
| What Are the Chances? Explaining the Epsilon Parameter in Differential Privacy P Nanayakkara, MA Smart, R Cummings, G Kaptchuk, EM Redmiles 32nd USENIX Security Symposium (USENIX Security 23), 1613-1630, 2023 | 46 | 2023 |
| Unpacking the expressed consequences of AI research in broader impact statements P Nanayakkara, J Hullman, N Diakopoulos Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 795-806, 2021 | 45 | 2021 |
| Anticipatory ethics and the role of uncertainty P Nanayakkara, N Diakopoulos, J Hullman Navigating the Broader Impacts of AI Research Workshop at NeurIPS 2020, 2020 | 17 | 2020 |
| What’s driving conflicts around differential privacy for the US census P Nanayakkara, J Hullman IEEE Security & Privacy 21 (5), 33-42, 2022 | 15 | 2022 |
| Examining Responsibility and Deliberation in AI Impact Statements and Ethics Reviews D Liu, P Nanayakkara, SA Sakha, G Abuhamad, SL Blodgett, ... Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society, 2022 | 11 | 2022 |
| Measure-Observe-Remeasure: An Interactive Paradigm for Differentially-Private Exploratory Analysis P Nanayakkara, H Kim, Y Wu, A Sarvghad, N Mahyar, G Miklau, ... 2024 IEEE Symposium on Security and Privacy (SP), 231-231, 2024 | 5 | 2024 |
| Toward Better Communication of Uncertainty in Science Journalism P Nanayakkara, J Hullman Computation + Journalism, 2020 | 5 | 2020 |
| Models matter: Setting accurate privacy expectations for local and central differential privacy MA Smart, P Nanayakkara, R Cummings, G Kaptchuk, E Redmiles arXiv preprint arXiv:2408.08475, 2024 | 4 | 2024 |
| Whose Policy? Privacy Challenges of Decentralized Platforms S Hwang, P Nanayakkara, Y Shvartzshnaider CHI'23 Workshops: Designing Technology and Policy Simultaneously: Towards A …, 2023 | 3 | 2023 |
| What to Consider When Considering Differential Privacy for Policy P Nanayakkara, J Hullman Policy Insights from the Behavioral and Brain Sciences, 23727322241278687, 2024 | 2 | 2024 |
| Comment on “NIST SP 800-226: Guidelines for Evaluating Differential Privacy Guarantees” R Cummings, S Hod, G Kaptchuk, P Nanayakkara, J Sarathy, J Seeman | 2 | 2024 |
| Trust and Friction: Negotiating How Information Flows Through Decentralized Social Media S Hwang, P Nanayakkara, Y Shvartzshnaider arXiv preprint arXiv:2503.02150, 2025 | | 2025 |
| Making Differential Privacy Usable Through Human-Centered Tools P Nanayakkara Northwestern University, 2024 | | 2024 |
| Communicating Differential Privacy Guarantees to Data Subjects P Nanayakkara | | 2023 |
