Chandra Nair is a 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 optimisation 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. He received the 2016 Information Theory Society paper award for developing a novel way to establish the optimality of Gaussian distributions for a class of non-convex optimisation problems arising in multiuser information theory. A proof of the Parisi and Coppersmith-Sorkin conjectures in the Random Assignment Problem was his doctoral dissertation; and he resolved some conjectures related to Random Energy model approximation of the Number Partition Problem during his post-doctoral years.

Nair got his Bachelor's degree, BTech(EE), from IIT Madras (India) where he received the Philips (India) and Siemens (India) award 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 a distinguished lecturer of the IEEE Information theory society (2017-2018). He is a Fellow of the IEEE.

He serves as the Programme Director of the undergraduate program on Mathematics and Information Engineering.