Peida Tian


Peida Tian
Email: ptian[at]caltech[dot]edu
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.



  1. "The dispersion of the Gauss-Markov source", Peida Tian, Victoria Kostina, ISIT'2018, [Conference version] [ITA poster] [ArXiv], submitted to IEEE Transactions on Information Theory, May 2018.
  2. "Arbitrarily varying networks: capacity-achieving computationally efficient codes", Peida Tian, Sid Jaggi, Mayank Bakshi, Oliver Kosut, ISIT'2016, [IEEE Xplore]

Teaching assistant

  1. EE/Ma/CS 127 Error-Correcting Codes, fall 2017
  2. EE 163A Communication Networks, winter 2018
  3. EE 120 Topics in Information Theory, spring 2018