Better Understanding of Efficient Dynamic Data Structures

Data structures have applications and connections to algorithm design, database systems, streaming algorithms and other areas of computer science. Understanding what efficient data structures can do (and what they cannot do) is crucial to these applications. In this talk, I will present my work in analyzing efficient data structures and proving what they cannot accomplish. I will focus on the recent development in building new connections between dynamic data structures and communication complexity, as well as a new approach to analyzing dynamic data structures with Boolean outputs and super-logarithmic time.

Bio:
Huacheng Yu is a postdoctoral researcher in the Theory of Computing group at Harvard University. He obtained his PhD from Stanford University in 2017 under the supervision of Ryan Williams and Omer Reingold. He also holds a Bachelor's degree from Tsinghua University (2012). His primary research interests are data structure lower bounds. He also works in algorithm design and communication complexity.