LI Cheuk Ting

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 was awarded the 2016 IEEE Jack Keil Wolf ISIT Student Paper Award. He joined the Department of Information Engineering, the Chinese University of Hong Kong in January 2020.

Cheuk Ting Li is interested in developing new information-theoretic techniques to address problems in delay-constrained communications, information security, distributed computing and machine learning.

Selected Publications

• Cheuk Ting Li, Xiugang Wu, Ayfer Ozgur and Abbas El Gamal, “Minimax Learning for Distributed Inference,” IEEE Transactions on Information Theory, vol. 66, no. 12, pp. 7929-7938, Dec. 2020.

• Cheuk Ting Li, “Asymptotically Scale-invariant Multi-resolution Quantization,” IEEE International Symposium on Information Theory 2020.

• 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.

• Cheuk Ting Li and Venkat Anantharam, “One-Shot Variable-Length Secret Key Agreement Approaching Mutual Information,” 56th Annual Allerton Conference on Communication, Control, and Computing, Oct 2018.

• 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, “Extended Gray-Wyner System with Complementary Causal Side Information,” IEEE Transactions on Information Theory, vol. 64, no. 8, pp. 5862-5878, Aug 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.

• Cheuk Ting Li and Ayfer Ozgur, “Channel Diversity Needed for Vector Space Interference Alignment,” IEEE Transactions on Information Theory, vol. 62, no.4, pp.1942-1956, Apr 2016.

• Cheuk Ting Li and Abbas El Gamal, “An Efficient Feedback Coding Scheme with Low Error Probability for Discrete Memoryless Channels,” IEEE Transactions on Information Theory, vol. 61, issue 6, pp. 2953 - 2963, Jun 2015.

• Gowtham Ramani Kumar, Cheuk Ting Li and Abbas El Gamal, “Exact common information,” IEEE International Symposium on Information Theory 2014.

Software

• Python Symbolic Information Theoretic Inequality Prover (PSITIP), a computer algebra system for information theory.