The Grainger College of Engineering
Electrical & Computer Engineering

Jingbo Liu

Jingbo Liu
Jingbo Liu
Assistant Professor, Statistics
228 Computing Applications Bldg

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Education

  • Electrical Engineering, Doctor of Philosophy, Princeton University, 2018
  • Electrical Engineering, Master of Arts, Princeton University, 2014
  • Electronic Engineering, Bachelor of Engineering, Tsinghua University, 2012

Biography

Jingbo Liu received the B.E. degree from Tsinghua University, Beijing, China in 2012, and the M.A. and Ph.D. degrees from Princeton University, Princeton, NJ, USA, in 2014 and 2018, all in electrical engineering. After two years of postdoc at MIT IDSS, he joined the Department of Statistics at the University of Illinois, Urbana-Champaign as an assistant professor.

His research interests include signal processing, information theory, coding theory, high dimensional statistics, and the related fields. His undergraduate thesis received the best undergraduate thesis award at Tsinghua University (2012). He gave a semi-plenary presentation at the 2015 IEEE Int. Symposium on Information Theory, Hong-Kong, China. He was a recipient of the Princeton University Wallace Memorial Honorific Fellowship in 2016. His Ph.D. thesis received the Bede Liu Best Dissertation Award of Princeton and the Thomas M. Cover Dissertation Award of the IEEE Information Theory Society (2018).

Academic Positions

  • Assistant Professor, Department of Electrical and Computer Engineering, 0% (affiliate), 2020
  • Assistant Professor, Department of Statistics, 100%, 2020

Course Development

  • STAT 578: topics: high dimensional statistics
  • STAT 430: topics in statistics: nonparametric statistics

Research Interests

  • Statistical inference (high-dimensional statistics, inference under systems constraints, graphical models); information theory (information-theoretic inequalities, converse techniques, multiuser, security); signal processing; applications of high-dimensional probability and functional analysis to information sciences.

Research Areas

  • Information theory

Research Topics

  • Machine learning

Selected Articles in Journals

  • J. Liu, Minorization via Mixed Volumes and Cover's Problem for General Channels, Probability Theory and Related Fields, vol.183, 1-2, 315--357, Jan. 2022.
  • J. Liu, “Dispersion Bound for the Wyner-Ahlswede-Korner Network via Reverse Hypercontractivity on Types,” IEEE Transactions on Information Theory, Vol. 67, Issue: 2, pp. 869–885, Feb. 2021.
  • J. Liu, A. Ozgur, Capacity Upper Bounds for the Relay Channel via Reverse Hypercontractivity, IEEE Transactions on Information Theory, Vol. 66, Issue: 9, pp. 5448–5455, Sept. 2020.
  • T. A. Courtade, J. Liu, Euclidean Forward-Reverse Brascamp-Lieb Inequalities: Finiteness, Structure and Extremals, Journal of Geometric Analysis, Journal of Geometric Analysis, Vol. 31, pp. 3300–3350, 2021
  • J. Liu, M. Yassaee, S. Verdu, Sharp Bounds for Mutual Covering, IEEE Transactions on Information Theory, Vol. 65, Issue 12, pp. 8067–8083, Dec. 2019.
  • J. Liu, R. van Handel, S. Verdu, Second-order Converses via Reverse Hypercontractivity, Mathematical Statistics and Learning, Vol. 2, Issue 2, pp. 103–163, 2020-07-16.
  • J. Liu, T. A. Courtade, P. Cuff, S. Verdu, Smoothing Brascamp-Lieb Inequalities and Strong Converses of Coding Theorems, IEEE Transactions on Information Theory, Vol. 66, Issue 2, pp. 704–721, Feb. 2020.
  • J. Liu, T. A. Courtade, P. Cuff, S. Verdu, A Forward-Reverse Brascamp-Lieb Inequality: Entropic Duality and Gaussian Optimality, Entropy, Special Issue Entropy and Information Inequalities, vol. 20, issue 6, May 2018
  • J. Liu, P. Cuff, S. Verdu, Common Randomness and Key Generation with Limited Interaction, IEEE Transactions on Information Theory, vol. 63, no. 11, pp. 7358-7381, Nov. 2017.
  • J. Liu, P. Cuff, S. Verdu, E_gamma-Resolvability, IEEE Transactions on Information Theory, vol. 63, no. 5, pp. 2629-2658, May 2017.
  • J. Liu, P. Cuff, S. Verdu, Key Capacity for Product Sources with Application to Stationary Gaussian Processes, IEEE Transactions on Information Theory, vol. 62, no. 2, pp. 984-1005, Feb. 2016.
  • J. Liu, J. Jin, Y. Gu, Robustness of Sparse Recovery via F -minimization: A Topological Viewpoint, IEEE Transactions on Information Theory, vol. 61, no. 7, pp. 3996-4014, July 2015.
  • F. Liu, J. Liu, Anisotropic Diffusion for Image Denoising Based on Diffusion Tensors, Journal of Visual Communication and Image Representation, Volume 23, Issue 3, April 2012.

Other Scholarly Activities

  • International Symposium on Information Theory (ISIT) 2021 technical program committee

Honors

  • Thomas Cover Dissertation Award (2018)

Research Honors

  • Thomas Cover Dissertation Award (2018)

Recent Courses Taught

  • STAT 410 (MATH 464) - Statistics and Probability II
  • STAT 430 - Nonparametric Statistics
  • STAT 527 - Advanced Regression Analysis
  • STAT 542 (CSE 542, ASRM 551) - Statistical Learning
  • STAT 578 - High-Dimensional Statistics