Prof. NAIR Chandra

Associate Professor (FIEEE)
Education: B.Tech (IIT-Madras), MS and PhD (Stanford)
Research Area: Non-convex and Combinatorial Optimization,
Information Theory, High Dimensional Probability Theory
Tel: (852) 3943-8467
Fax: (852) 2603-5032
Address: Rm 811, Ho Sin Hang Engineering Building, CUHK
Email: chandra [@] ie.cuhk.edu.hk


Research Interests

  • Multiuser Information Theory
  • Combinatorial Optimization
  • Probability theory
  • Algorithms

Courses Taught

  • Basic Circuit Theory
  • Signals and Systems
  • Advanced Engineering Mathematics
  • Random Processes
  • Theory of Probability
  • Multiuser Information Theory


Chandra Nair is an Associate Professor with the Information Engineering department at The Chinese University of Hong Kong. His research interests and contributions have been in developing ideas, tools, and techniques to tackle families of combinatorial and non-convex optimization problems arising primarily in the information sciences.

His recent research focus has been on studying the optimality of certain inner and outer bounds to capacity regions for fundamental problems in multiuser information theory. In a broader sense these problems are concerned with establishing tensorization/sub-additivity properties of certain functionals over high-dimensional probability spaces. One of his papers in this area, devising a novel technique for proving the extremality of Gaussian distributions for certain families of non-convex functionals, received the 2016 Information Theory Society paper award. A proof of the Parisi and Coppersmith-Sorkin conjectures in the Random Assignment Problem formed his doctoral dissertation; and he resolved some conjectures related to Random Energy model approximation of the Number Partition Problem during his post-doctoral years.

Chandra Nair got his Bachelor’s degree, B.Tech(EE), from IIT Madras (India) where he was the Philips (India) and Siemens (India) award winner for the best academic performance. Subsequently he was a Stanford graduate fellow (00-04) and a Microsoft graduate fellow (04-05) during his graduate studies at the EE department of Stanford university. Later, he became a post-doctoral researcher (05-07) with the theory group at Microsoft Research, Redmond. He has been a faculty member of the Information Engineering department at The Chinese University of Hong Kong since Fall 2007. He was an Associate Editor for the IEEE Transactions on Information Theory (2014-2016) and is currently a Distinguished Lecturer of the IEEE Information Theory society. He was elected a fellow of the IEEE (class of 2018).

He serves as the Programme Director of the undergraduate program on Mathematics and Information Engineering and as the Director of the Institute of Theoretical Computer Science and Communications.

Recent Selected Publications

  • Nair, C. & Wang, Y. N.
    Reverse hypercontractivity region for the binary erasure channel [ pdf ]
    • 2017 IEEE International Symposium on Information Theory (ISIT), 2017, 938-942
  • Nair, C. & Yazdanpanah, M.
    Sub-optimality of superposition coding region for three receiver broadcast channel with two degraded message sets [ pdf ]
    • 2017 IEEE International Symposium on Information Theory (ISIT), 2017, 1038-1042
  • Beigi, S. & Nair, C.
    Equivalent characterization of reverse Brascamp-Lieb-type inequalities using information measures [ pdf ]
    • 2016 IEEE International Symposium on Information Theory (ISIT), 2016, 1038-1042
  • Nair, C.; Xia, L. & Yazdanpanah, M.
    Sub-optimality of Han-Kobayashi achievable region for interference channels [ pdf ]
    • 2015 IEEE International Symposium on Information Theory (ISIT), 2015, 2416-2420
  • Geng, Y. & Nair, C.
    The Capacity Region of the Two-Receiver Gaussian Vector Broadcast Channel With Private and Common Messages [ pdf ]
    • IEEE Transactions on Information Theory, 2014, 60, 2087-2104
      (Received the 2016 Information Theory Society paper award)