Jingbo Liu is a Wiener postdoc in statistics at the MIT Institute for Data, Systems, and Society (IDSS). He obtained PhD from Princeton University, and BE from Tsinghua University, both in electrical engineering.

As a postdoc at MIT, he worked on several topics in statistical inference, including: fundamental limits and algorithms for data with structures (graphical models); inference under system (memory, communication complexity, privacy) constraints; false discovery rate control for feature selection from large data sets. In particular, the proof of a long-standing conjecture about message passing (huge thanks to the generosity of the MIT people who shared the problem and the previous circle of ideas).

During PhD at Princeton University, he worked on various topics related to information theory, including security, multiuser, interactive, and non-asymptotic information theory. His thesis proposed novel approaches to information-theoretic converses using methods from high dimensional probability and functional analysis, which was awarded the Thomas M. Cover Dissertation Award of the IEEE Information Theory Society, for ``contributing to the mathematical foundations of the information sciences''.

His undergraduate work introduced a topological characterization of the robustness of nonconvex optimization, winning the best undergraduate thesis award of Tsinghua University.