Towards Auditability for Fairness in Deep Learning. - Ivoline C. Ngong; Krystal Maughan; Joseph P. Near (CoRR, 2020)

Prediction Sensitivity: Continual Audit of Counterfactual Fairness in Deployed Classifiers. - Krystal Maughan; Ivoline C. Ngong; Joseph P. Near (CoRR, 2022)

Olympia: A Simulation Framework for Evaluating the Concrete Scalability of Secure Aggregation Protocols. - Ivoline C. Ngong; Nicholas Gibson; Joseph P. Near (SaTML, 2024)

Evaluating the Usability of Differential Privacy Tools with Data Practitioners. - Ivoline C. Ngong; Brad Stenger; Joseph P. Near; Yuanyuan Feng (SOUPS @ USENIX Security Symposium, 2024)

SoK: Usability Studies in Differential Privacy. - Onyinye Dibia; Brad Stenger; Steven Baldasty; Mako Bates; Ivoline C. Ngong; Yuanyuan Feng; Joseph P. Near (CoRR, 2024)

Protecting Users From Themselves: Safeguarding Contextual Privacy in Interactions with Conversational Agents. - Ivoline C. Ngong; Swanand Ravindra Kadhe; Hao Wang 063; Keerthiram Murugesan; Justin D. Weisz; Amit Dhurandhar; Karthikeyan Natesan Ramamurthy (ACL (Findings), 2025)

Differentially Private Learning Needs Better Model Initialization and Self-Distillation. - Ivoline C. Ngong; Joseph P. Near; Niloofar Mireshghallah (NAACL (Long Papers), 2025)

SoK: Usability Studies in Differential Privacy. - Onyinye Dibia; Prianka Bhattacharjee; Brad Stenger; Steven Baldasty; Mako Bates; Ivoline C. Ngong; Yuanyuan Feng; Joseph P. Near (Proc. Priv. Enhancing Technol., 2025)