Sayan Biswas

Sayan Biswas

sayan.biswas@epfl.ch or bizwas05@gmail.com

EPFL IC IINFCOM SACS,
BC 166 (Bâtiment BC), Station 14,
1015 Lausanne, Switzerland.

About Me

I am a Postdoctoral Researcher in the Scalable Computing Systems (SaCS) lab at EPFL, Switzerland, led by Prof. Anne-Marie Kermarrec. I completed my PhD in Computer Science at INRIA and École Polytechnique in France, under the supervision of Prof. Catuscia Palamidessi. During my PhD, I have been a Visiting Scholar at the School of Computing at Macquarie University in Sydney, Australia (hosted by Prof. Annabelle McIver and Dr. Natasha Fernandes) and at WMG at The University of Warwick in Coventry, England (hosted by Prof. Carsten Maple and Prof. Graham Cormode).

My research primarily centres on designing distributed trustworthy systems for analysing data and training models in decentralised frameworks. Occasionally, I get fascinated by, and end up working on, some of the challenges of location privacy, aiming to build privacy-preserving and secure location-based systems. I focus on exploring and optimising the trade-off between privacy and utility from a foundational perspective. My current research revolves around decentralised learning, federated learning, and fair and trustworthy decentralized systems, with a particular emphasis on privacy and personalisation.

I study, talk, and do mathematics most of the time; when not, I am typically immersed in techno music, chess, cricket, philosophy, puzzles, or stand-up comedy. Lately, I’ve rekindled my love for (non-academic) reading and have become a collector of seemingly useless facts from all corners of life — because who doesn’t need to know how often penguins defecate? I am also trying to learn French with limited success so far. The list of some of my current favourite results and theorems in mathematics (a list that, obviously, everyone should maintain) includes:

Publications


Peer-reviewed conferences

  • (2024) Sayan Biswas, Mathieu Even, Anne-Marie Kermarrec, Laurent Massoulie, Rafael Pires, Rishi Sharma, Martijn de Vos: “Noiseless Privacy-Preserving Decentralized Learning”. Proceedings of the 25th Privacy Enhancing Technologies Symposium (PoPETs) 2025, Issue 1, pp 824-844. PDF , DOI: 10.56553/popets-2025-0043

  • (2023) Sayan Biswas, Kangsoo Jung, Catuscia Palamidessi: “Tight Differential Privacy Guarantees for the Shuffle Model with k-Randomized Response”. Proceedings of the 16th International Symposium on Foundations and Practice of Security (FPS) 2023, pp 440-458, LNCS 14551, Springer. PDF , DOI: 10.1007/978-3-031-57537-2_27

  • (2023) Sayan Biswas, Catuscia Palamidessi: “PRIVIC: A privacy-preserving method for incremental collection of location data”. Proceedings of the 24th Privacy Enhancing Technologies Symposium (PoPETs) 2024, Issue 1, pp 582-596. PDF , DOI: 10.56553/popets-2024-0033

  • (2023) Filippo Galli, Sayan Biswas, Kangsoo Jung, Tommaso Cucinotta, Catuscia Palamidessi: “Group privacy for Personalized Federated Learning”. Proceedings of the 9th International Conference on Information Systems Security and Privacy (ICISSP) 2023, pp 252-263, SciTePress Digital Library. PDF , DOI: 10.5220/0011885000003405

  • (2022) Sayan Biswas, Graham Cormode, Carsten Maple: “Impact of Sampling on Locally Differentially Private Data Collection”. Proceedings of the 8th Competitive Advantage in the Digital Economy -- Resilience, Sustainability, Responsibility, and Identity (CADE) 2022, pp 64-70, IET Digital Library and IEEE Xplore. Winner of the Best Paper Award. PDF , DOI: 10.1049/icp.2022.2042

  • (2022) Sayan Biswas, Kangsoo Jung, Catuscia Palamidessi: “Tight Differential Privacy Blanket for Shuffle Model”. Proceedings of the 8th Competitive Advantage in the Digital Economy -- Resilience, Sustainability, Responsibility, and Identity (CADE) 2022, pp 61-63, IET Digital Library and IEEE Xplore. PDF , DOI: 10.1049/icp.2022.2041

  • (2021) Sayan Biswas, Kangsoo Jung, Catuscia Palamidessi: “An Incentive Mechanism for Trading Personal Data in Data Markets”. Proceedings of the 18th International Colloquium on Theoretical Aspects of Computing (ICTAC) 2021, pp 197-213, LNCS 12819, Springer. PDF , DOI: 10.1007/978-3-030-85315-0_12

Journals

  • (2024) Ugur Ilker Atmaca, Sayan Biswas, Carsten Maple, Catuscia Palamidessi: “A Privacy-Preserving Querying Mechanism with High Utility for Electric Vehicles”. IEEE Open Journal of Vehicular Technology, Volume 5, pp 262-277. PDF , DOI: 10.1109/OJVT.2024.3360302

  • (2023) Filippo Galli, Kangsoo Jung, Sayan Biswas, Catuscia Palamidessi, Tommaso Cucinotta: “Advancing Personalized Federated Learning: Group Privacy, Fairness, and Beyond”. Springer Nature Computer Science, Volume 4, Issue 6, Article 831 (2023). PDF , DOI: 10.1007/s42979-023-02292-0

Book sections

  • (2021) Kangsoo Jung, Sayan Biswas, Catuscia Palamidessi: “Establishing the Price of Privacy in Federated Data Trading”. Protocols, Strands, and Logic, pp 232-250, LNCS 13066, Springer. PDF , DOI: 10.1007/978-3-030-91631-2_13

Non-archival workshops

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