Differentially Private Densest Subgraph Detection. - Dung Nguyen 002; Anil Vullikanti (ICML, 2021)

Privacy-first health research with federated learning. - Adam Sadilek; Luyang Liu; Dung Nguyen 002; Methun Kamruzzaman; Stylianos Serghiou; Benjamin Rader; Alex Ingerman; Stefan Mellem; Peter Kairouz; Elaine O. Nsoesie; Jamie Macfarlane; Anil Vullikanti; et al. (npj Digit. Medicine, 2021)

Differentially Private Community Detection for Stochastic Block Models. - Mohamed S. Mohamed; Dung Nguyen 002; Anil Vullikanti; Ravi Tandon (ICML, 2022)

Differentially Private Community Detection for Stochastic Block Models. - Mohamed Seif; Dung Nguyen 002; Anil Vullikanti; Ravi Tandon (CoRR, 2022)

Differentially Private Partial Set Cover with Applications to Facility Location. - George Z. Li; Dung Nguyen 002; Anil Vullikanti (IJCAI, 2023)

Faster approximate subgraph counts with privacy. - Dung Nguyen 002; Mahantesh Halappanavar; Venkatesh Srinivasan 001; Anil Vullikanti (NeurIPS, 2023)

Computing epidemic metrics with edge differential privacy. - George Z. Li; Dung Nguyen 002; Anil Vullikanti (AISTATS, 2024)

Differentially private exact recovery for stochastic block models. - Dung Nguyen 002; Anil Kumar S. Vullikanti (ICML, 2024)

Contrastive Explainable Clustering with Differential Privacy. - Dung Nguyen 002; Ariel Vetzler; Sarit Kraus; Anil Vullikanti (AAMAS, 2025)

Controlling the Spread of Epidemics on Networks with Differential Privacy. - Dung Nguyen 002; Aravind Srinivasan; Renata Valieva; Anil Vullikanti; Jiayi Wu (CoRR, 2025)

A Framework for Multi-source Privacy Preserving Epidemic Analysis. - Zihan Guan 001; Zhiyuan Zhao 002; Fengwei Tian; Dung Nguyen 002; Payel Bhattacharjee; Ravi Tandon; B. Aditya Prakash; Anil Vullikanti (CoRR, 2025)