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), 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
(09/2025) Paper "On the Fundamental Tradeoff of Joint Communication and QCD: The Monostatic Case," accepted to IEEE Journal on Selected Areas in Communications
(02/2025) Congratulations on graduation, Junkyu, Minseo!
(02/2025) Paper "Deep Minimax Classifiers for Imbalanced Datasets with a Small Number of Minority Samples" accepted to IEEE Journal of Selected Topics in Signal Processing
(01/2025) Paper "Integrated Communication and Binary State Detection Under Unequal Error Constraints" accepted to IEEE Transactions on Communications
(12/2024) Paper "Integrated Communication and Bayesian Estimation of Fixed Channel States" accepted to IEEE Communications Letters
(10/2024) Paper "On the Fundamental Tradeoff of Joint Communication and Quickest Change Detection with State-Independent Data Channels" accepted to IEEE Transactions on Communications
(08/2024) Paper "Integrated Communication and Binary State Detection from Hoeffding's Perspective" accepted to WiOpt 2024
(04/2024) Paper "On the Fundamental Tradeoff of Joint Communication and Quickest Change Detection" accepted to ISIT 2024