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Sidharth (sid) Jaggi

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

Biography

Sidharth Jaggi received his Bachelor of Technology degree from the Indian Institute of Technology in 2000, and his Master of Science and Ph.D. degrees from the California institute of Technology in 2001 and 2006 respectively, all in electrical engineering. He was awarded the Caltech Division of Engineering Fellowship 2001-'02, and the Microsoft Research Fellowship for the years 2002-'04. He interned at Microsoft Research, (Redmond, WA, USA) in the summers of 2002-'03 and engaged in research on network coding. He spent 2006 as a Postdoctoral Associate at the Laboratory of Information and Decision Systems at the Massachusetts Institute of Technology. He joined the Department of Information Engineering, the Chinese University of Hong Kong in 2007. Sidharth's research interests lie at the intersection of information theory, algorithms, and networking. He is currently particularly interested in the field of network coding http://www.ifp.uiuc.edu/~koetter/NWC/index.html which neatly merges practice and theory in all three of these fields. However, his interests are eclectic (above all, he likes a good challenge) and he has dabbled in communication complexity, quantum computation, coding theory, random matrix theory, and signal.

Research Interest

Network coding Network information theory Coding theory Algorithm design for networks

Publications

  • 2012. A.-H. Mohsenian-Rad, J. Huang, V.W.S. Wong, S. Jaggi, R. Schober, “Inter-Session Network Coding with Strategic Users: A Game-Theoretic Analysis of the Butterfly Network,” accepted for publication in the IEEE Transactions on Communications.

  • B. K. Dey, S. Jaggi, M. Langberg, “Codes against Online Adversaries, part I: Large Alphabets,”accepted for publication in the IEEE Transactions on Information Theory

  • C. L. Chan, S. Jaggi, V. Saligrama, and S. Agnihotri, "Non-adaptive Group Testing: Explicit bounds and novel algorithms", accepted for publication in the IEEE Transactions on Information Theory.

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