Professor Li Cheuk Ting from the Department of Industrial Engineering at the Chinese University of Hong Kong and Professor Venkat Anantharam from UC Berkeley co-authored a paper titled "A Unified Framework for One-Shot Achievability via the Poisson Matching Lemma," which has been awarded the prestigious IT Society Best Paper Award in 2023. This is the third time that the IE Department has won this award, with previous wins in 2005 by Prof. Raymond Yeung for Network Coding and in 2016 by Prof. Nair for developing a new technique for Gaussian optimality.

The paper introduces a fundamental lemma called the Poisson matching lemma and applies it to prove one-shot achievability results for various settings, including channels with state information at the encoder, lossy source coding with side information at the decoder, joint source-channel coding, broadcast channels, distributed lossy source coding, multiple access channels, and channel resolvability. The paper extends the work of Li and El Gamal on Poisson functional representation, which mainly considered variable-length source coding settings, whereas this paper studies fixed-length settings and is not limited to source coding, showing that the Poisson matching lemma replaces both the packing and covering lemmas, greatly simplifying the error analysis.