BUDS: Balancing Utility and Differential Privacy by Shuffling. - Poushali Sengupta; Sudipta Paul 004; Subhankar Mishra (ICCCNT, 2020)

FLaPS: Federated Learning and Privately Scaling. - Sudipta Paul 004; Poushali Sengupta; Subhankar Mishra (MASS, 2020)

Learning With Differential Privacy. - Poushali Sengupta; Sudipta Paul 004; Subhankar Mishra (CoRR, 2020)

Fairly Private Through Group Tagging and Relation Impact. - Poushali Sengupta; Subhankar Mishra (MDAI, 2021)

Balancing Explainability-Accuracy of Complex Models. - Poushali Sengupta; Yan Zhang 002; Sabita Maharjan; Frank Eliassen (CoRR, 2023)

Privacy-preserving transactive energy systems: Key topics and open research challenges. - Daniel Gerbi Duguma; Juliana Jia Yu Zhang; Meysam Aboutalebi; Shiliang Zhang; Catherine Banet; Cato Bjørkli; Chinmayi Prabhu Baramashetru; Frank Eliassen; Hui Zhang; Jonathan Muringani; Josef Noll; Knut Inge Fostervold; et al. (CoRR, 2023)

BUDS+: Better Privacy with Converger and Noisy Shuffling. - Poushali Sengupta; Sudipta Paul 004; Subhankar Mishra (DTRAP, 2023)

Privacy-Utility-Fairness: A Balanced Approach to Vehicular-Traffic Management System. - Poushali Sengupta; Sabita Maharjan; Frank Eliassen; Yan Zhang 002 (CoRR, 2025)