LI Cheuk Ting

*SHB = Ho Sin Hang Engineering Building, The Chinese University of Hong Kong

Research Interest
  • Finite-blocklength information theory
  • Network information theory
  • Channel simulation
  • Automated theorem proving
  • Undecidable problems
Courses Taught

  • Information Theory
  • Introduction to Stochastic Processes

LI Cheuk Ting 李卓霆教授

Assistant Professor
MIEEE
BSc, BEng (CUHK), MS, PhD (Stanford)
(852) 3943-5156
Room 807, SHB*
ctli [at] ie.cuhk.edu.hk
Website

Cheuk Ting Li received the B.Sc. degree in mathematics and B.Eng. degree in information engineering from The Chinese University of Hong Kong in 2012, and the M.S. and Ph.D. degree in electrical engineering from Stanford University in 2014 and 2018, respectively. He was a postdoctoral scholar at the Department of Electrical Engineering and Computer Sciences, University of California, Berkeley. He joined the Department of Information Engineering, the Chinese University of Hong Kong in January 2020. He was awarded the 2016 IEEE Jack Keil Wolf ISIT Student Paper Award, and the 2023 Information Theory Society Paper Award.

His research interests include simulation of random sources and channels, one-shot and finite-blocklength schemes in information theory, network information theory, and automated theorem proving.

Recent / Selected Publications
  • Cheuk Ting Li, “Channel Simulation: Theory and Applications to Lossy Compression and Differential Privacy,” Foundations and Trends® in Communications and Information Theory: Vol. 21: No. 6, pp 847-1106, 2024.
  • Yanxiao Liu, Wei-Ning Chen, Ayfer Ozgur and Cheuk Ting Li, “Universal Exact Compression of Differentially Private Mechanisms,” The Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS), 2024.
  • Chih Wei Ling and Cheuk Ting Li, “Vector Quantization With Error Uniformly Distributed Over an Arbitrary Set,” IEEE Transactions on Information Theory, vol. 70, no. 7, pp. 5392-5407, July 2024.
  • Cheuk Ting Li, “An Automated Theorem Proving Framework for Information-Theoretic Results,” IEEE Transactions on Information Theory, vol. 69, no. 11, pp. 6857-6877, Nov. 2023.
  • Cheuk Ting Li, “Undecidability of Network Coding, Conditional Information Inequalities, and Conditional Independence Implication,” IEEE Transactions on Information Theory, Feb 2023.
  • Cheuk Ting Li and Venkat Anantharam, “Pairwise Near-maximal Grand Coupling of Brownian Motions,” Annales de l’Institut Henri Poincare, Probabilites et Statistiques, vol. 58, no. 3, 2022.
  • Cheuk Ting Li, “The Undecidability of Conditional Affine Information Inequalities and Conditional Independence Implication with a Binary Constraint,” IEEE Transactions on Information Theory, vol. 68, no. 12, pp. 7685-7701, Dec 2022.
  • Cheuk Ting Li, “Efficient Approximate Minimum Entropy Coupling of Multiple Probability Distributions,” IEEE Transactions on Information Theory, vol. 67, no. 8, pp. 5259 – 5268, May 2021.
  • Cheuk Ting Li, “Infinite divisibility of information,” IEEE Transactions on Information Theory, vol. 68, no. 7, pp. 4257-4271, July 2022.
  • Cheuk Ting Li and Venkat Anantharam, “A Unified Framework for One-shot Achievability via the Poisson Matching Lemma,” IEEE International Symposium on Information Theory 2019. (2023 Information Theory Society Paper Award)
  • Cheuk Ting Li and Abbas El Gamal, “Strong Functional Representation Lemma and Applications to Coding Theorems,” IEEE Transactions on Information Theory, vol. 64, no. 11, pp. 6967-6978, Nov 2018.
  • Cheuk Ting Li and Abbas El Gamal, “Maximal Correlation Secrecy,” IEEE Transactions on Information Theory, vol. 64, no. 5, pp. 3916-3926, May 2018.
  • Cheuk Ting Li and Abbas El Gamal, “A Universal Coding Scheme for Remote Generation of Continuous Random Variables,” IEEE Transactions on Information Theory, vol. 64, no. 4, pp. 2583-2592, Apr 2018.
  • Cheuk Ting Li and Abbas El Gamal, “Distributed Simulation of Continuous Random Variables,” IEEE Transactions on Information Theory, vol. 63, no. 10, pp.6329-6343, Oct 2017.
Research Interest

  • Finite-blocklength information theory
  • Network information theory
  • Channel simulation
  • Automated theorem proving
  • Undecidable problems
Courses Taught

  • Information Theory
  • Introduction to Stochastic Processes