"Expressions in Multimedia" by Martha G. Trask "Secondary Effects" by Jeff Ostergren Join us for a reception Thursday, May 22, from 4 to 6 p.m. in the Celeste LeWitt Gallery. (north side of the food court)Martha G. Trask is an expressive mixed media artist who happens to work in our library.Jeff Ostergren infuses his paint with actual medications to tell stories about the intertwined histories of pharmaceuticals and color.

The exhibiting artists are Marsha Borden, Helena Chastel, Kathryn Frund, Phoebe Godfrey, Hugh MacDonald, Bob Pavlik, Dan Potter, and R. Douglass Rice. Open Air 2025 is open daily and will remain on view through October 6, 2025. June 19, 2025 iis the last day to visit indoor art exhibitions. Exhibitions inside the AVS Gallery will resume on September 11, 2025

For the full class schedule, descriptions, and to register, please visit the UConn Recreation website (https://recreation.uconn.edu/group-fitness-schedule/).

For new students only

Abstract:Differential privacy (DP) has emerged as the de facto standard for privacy-preserving data analysis, yet significant challenges persist in its practical deployment. This dissertation advances DP mechanisms across three critical dimensions. First, we introduce DPI (Differential Privacy for Infinite Disclosure), a novel technique that effectively bounds privacy leakage in infinite data streams while maintaining high utility through sensitivity compression and an innovative boosting mechanism. Second, UDP-FL (Universally Harmonizing Differential Privacy Mechanisms for Federated Learning) presents a framework that integrates diverse DP mechanisms to achieve superior privacy-utility tradeoffs and faster convergence, introducing mode connectivity-based analysis for convergence evaluation and demonstrating remarkable resilience against privacy attacks. Finally, we propose a Multi-Stakeholder Usability Study of DP-SGD, examining how data contributors, machine learning engineers, and compliance officers understand, implement, and verify differential privacy guarantees in machine learning deployments. Through mixed-methods research involving structured tasks, surveys, and interviews, this study aims to bridge the gap between theoretical guarantees and practical implementation.

For the full class schedule, descriptions, and to register, please visit the UConn Recreation website (https://recreation.uconn.edu/group-fitness-schedule/).