Honeycrisp: large-scale differentially private aggregation without a trusted core. - Edo Roth; Daniel Noble; Brett Hemenway Falk; Andreas Haeberlen (SOSP, 2019)

Fuzzi: a three-level logic for differential privacy. - Hengchu Zhang; Edo Roth; Andreas Haeberlen; Benjamin C. Pierce; Aaron Roth 001 (Proc. ACM Program. Lang., 2019)

Orchard: Differentially Private Analytics at Scale. - Edo Roth; Hengchu Zhang; Andreas Haeberlen; Benjamin C. Pierce (OSDI, 2020)

Bounded-time recovery for distributed real-time systems. - Neeraj Gandhi; Edo Roth; Robert Gifford; Linh Thi Xuan Phan; Andreas Haeberlen (RTAS, 2020)

Testing differential privacy with dual interpreters. - Hengchu Zhang; Edo Roth; Andreas Haeberlen; Benjamin C. Pierce; Aaron Roth 001 (Proc. ACM Program. Lang., 2020)

REBOUND: defending distributed systems against attacks with bounded-time recovery. - Neeraj Gandhi; Edo Roth; Brian Sandler; Andreas Haeberlen; Linh Thi Xuan Phan (EuroSys, 2021)

Do Not Overpay for Fault Tolerance! - Edo Roth; Andreas Haeberlen (RTAS, 2021)

Mycelium: Large-Scale Distributed Graph Queries with Differential Privacy. - Edo Roth; Karan Newatia; Yiping Ma 001; Ke Zhong; Sebastian Angel; Andreas Haeberlen (SOSP, 2021)

Arboretum: A Planner for Large-Scale Federated Analytics with Differential Privacy. - Elizabeth Margolin; Karan Newatia; Tao Luo; Edo Roth; Andreas Haeberlen (SOSP, 2023)

Releasing Large-Scale Human Mobility Histograms with Differential Privacy. - Christopher Bian; Albert Cheu; Yannis Guzman; Marco Gruteser; Peter Kairouz; Ryan McKenna; Edo Roth (CoRR, 2024)

Mayfly: Private Aggregate Insights from Ephemeral Streams of On-Device User Data. - Christopher Bian; Albert Cheu; Stanislav Chiknavaryan; Zoe Gong; Marco Gruteser; Oliver Guinan; Yannis Guzman; Peter Kairouz; Artem Lagzdin; Ryan McKenna; Grace Ni; Edo Roth; et al. (CoRR, 2024)

Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data? - Marika Swanberg; Ryan McKenna; Edo Roth; Albert Cheu; Peter Kairouz (CoRR, 2025)