Information and Learning Theory Lab.
Overview
Information and Learning Theory Lab. (ILT Lab.) at DGIST, led by Daewon Seo, explores a broad spectrum of topics in wireless communications and machine learning from a theoretical standpoint. Specifically, our focus is on data communications (5G/6G, storage systems) and inference natures in machine learning and social networks, examined through the perspectives of statistical inference, information theory, and learning theory.
Openings
We are looking for students at all levels, undergrad, M.S., and Ph.D.
Please contact Prof. Daewon Seo (dwseo at dgist.ac.kr) if you are interested in ILT Lab. You can also try applying through the DGIST summer/winter internship program if you are an undergraduate.
News
(04/2024) Paper "On the Fundamental Tradeoff of Joint Communication and Quickest Change Detection" accepted to ISIT 2024
(09/2023) Paper "A context-aware CEO problem" accepted to IEEE Transactions on Communications
(04/2023) Paper "Information and Energy Transmission with Wavelet-Reconstructed Harvesting Functions" accepted to IEEE Transactions on Communications
(12/2022) Paper "Hypergraph-based Source Codes for Function Computation Under Maximal Distortion" accepted to IEEE Journal on Selected Areas in Information Theory
(04/2022) Paper "Information and Energy Transmission with Wavelet-Reconstructed Harvesting Functions" accepted to ISIT 2022
(10/2021) Paper "Decision Making in Star Networks with Incorrect Beliefs" accepted to IEEE Transactions on Signal Processing