Better Understandings of Efficient 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.
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. 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.