Moore Lab Room 116C
MC 136-93 Pasadena CA 91125
I'm now a second year Ph.D student in Electrical Engineering at Caltech, working with Professor Victoria Kostina. Currently I am working on finite length analysis for lossy compression. The goal is to understand the role of memory in data compression. I leverage tools from measure concentration and matrix analysis. I also have broad interest in other areas, such as coding theory and mixing time of Markov chains.
- B.Sc. in Mathematics, B.Engg. in Information Engineering, the Chinese University of Hong Kong, 2011-2016
- M.S. in Electrical Engineeing, California Institute of Technology, 2017
- Exchange student in EECS, Massachusetts Institute of Technology, 2014
- "The dispersion of the Gauss-Markov source", Peida Tian, Victoria Kostina, ISIT'2018,
[ArXiv], submitted to IEEE Transactions on Information Theory, May 2018.
- "Arbitrarily varying networks: capacity-achieving computationally efficient codes", Peida Tian, Sid Jaggi, Mayank Bakshi, Oliver Kosut, ISIT'2016,
- EE/Ma/CS 127 Error-Correcting Codes, fall 2017
- EE 163A Communication Networks, winter 2018
- EE 120 Topics in Information Theory, spring 2018