NAIR Chandra M.

Associate Professor
information engineering
Learning Sciences and Technologies, Centre for (CLST)
Hong Kong

Professor Engineering
Biography

Prof. Nair did his undergraduate studies at the Indian Institute of Technology (IIT), Madras in electrical engineering graduating in 1999. He received the Siemens and Phillips (India) medal for having the best academic record in the department during his undergraduate studies. Concurrently, he also completed the four year nurture programme in Mathematics at the Institute of Mathematical Sciences(IMSc ) under the auspices of the National Board of Higher Mathematics(NBHM). He received a Masters (2002) and PhD (2005) in electrical engineering from Stanford University. He was a Stanford Graduate Fellow (2000-2004) and then a Microsoft Graduate Fellow (2004-2005) during his graduate studies. Then he became a postdoctoral fellow at prestigious theory group in Microsoft Research for two years. Following this he joined the IE department faculty, CUHK, in Fall 2007. His current interests are in basic network information theory problems, in particular the broadcast channel. He has previously worked on problems touching many areas including combinatorial optimization, statistical physics, algorithms, and networks. The title of his dissertation was Proofs of the Parisi and Coppersmith-Sorkin conjectures in the random assignment problem.

Research Intrest

Research Interests Multiuser Information Theory Combinatorial Optimization Probability theory Algorithms

List of Publications
Capacity regions of two new classes of 2-receiver broadcast channels, C. Nair. IEEE Transactions on Information Theory, vol. IT-56, pp. 4207-4214, 2010. Proceedings of the International Symposium on Information Theory, pp. 1839-1843, 2009.
The capacity region of the three receiver less noisy broadcast channel, [pdf] C. Nair and Z. Wang IEEE Transactions on Information Theory, vol. IT-57, no. 7, pp. 4058-4062, July, 2011. Proceedings of the International Symposium on Information Theory, 2010.
The capacity region of the two-receiver vector Gaussian broadcast channel with private and common messages,

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