Foundations of Sensing and Information [FSI] team

Embedded sensors such as in IoT appliances or industrial robots enhance our ability to monitor and optimize processes in various fields.

Research

Sensors convert physical information into actionable data, used for modeling, estimation, and prediction—in short, they provide us with decision-driving insights. Our team especially studies the mathematical foundations of different kinds of sensing systems:

fundamental limits of sensing systems
distributed estimation and detection over networks
security in distributed sensing
optimization of sensor networks
estimation and detection in the context of machine learning
integrated sensing and communication for future cellular networks and optical fibers
quantum sensing systems

Team members

Michèle Wigger, Professor, team leader
Robert Graczyk, Associate Professor
Mireille Sarkiss, Associate Professor Télécom SudParis

Keywords

Information theory
Statistics
Estimation
Detection
Communications

Team publications

[1] M. Ahmadipour, M. Kobayashi, M. Wigger, and G. Caire, « An Information-Theoretic Approach to Joint Sensing and Communication, » IEEE Trans. on Inf. Theory, Feb. 2024.
[2] M. Hamad, M. Wigger, and M. Sarkiss, « Multi-hop Network with Multiple Decision Centers under Expected-Rate Constraints, » IEEE Trans. on Inf. Theory, July 2023.
[3] M. Ahmadipour and M. Wigger, « An Information-Theoretic Approach to Collaborative Integrated Sensing and Communication for Two-Transmitter Systems, » Journal on Sel. Areas in Inf. Theory, June 2023.
[4] R. Graczyk, A. Lapidoth, and M. Wigger, « Conditional and Relevant Common Information,” Information and Inference: A Journal of the IMA, 2022.
[5] N. Le Gouic, R. Graczyk, and S. Moser, « Approximate Hypothesis Testing, » to be submitted to Int. Symp. Inf. Theory, July 2025.
[6] A. Bounhar, M. Sarkiss, M. Wigger, “Covert Distributed Detection over Discrete Memoryless Channels”, Int. Symp. Inf. Theory 2024, 7-12 July 2024.