Di Wang
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Email: wangd[@]eecs[DOT]berkeley[DOT]edu |
About me
My research interests are in the design of efficient algorithms, especially for large-scale optimization problems and graph problems that arise broadly in applications from machine learning, data analysis and operations research. My work draws on a broad range of numerical and discrete tools from combinatorics, optimization and graph theory, which leads to not only stronger theoretical guarantees, but also practical improvements for computational challenges arising in practice.
In July 2019, I joined Google research at Mountain View.
From Spring 2018 to Summer 2019, I was a postdoc in the Algorithms & Randomness Center at Georgia Tech with Richard Peng.
In Fall 2017, I was a research fellow at the Simons Institute (for the program Bridging Continuous and Discrete Optimization).
I finished my PhD in Computer Science at UC Berkeley in summer 2017, advised by Satish Rao.
Before attending Berkeley, I received B.S. in Computer Science from Cornell University, advised by Robert Kleinberg.
Links
The Design of Approximation Algorithms by David P. Williamson and David B. Shmoys
Networks, Crowds, and Markets by David Easley and Jon Kleinberg