I am broadly interested in the power of parameterization
in the context of algorithm design
. In particular, I like understanding the mathematical structure of parameterized input instances, and how they can be exploited in the search for faster algorithms. Examples include, but are not limited to:
- Parameterized algorithms: fast, polynomial-time algorithms for difficult problems under the promise that a certain parameter in the input instance is small. This includes fixed-parameter tractable (FPT) algorithms and approximation algorithms under a parameterized setting.
- Algorithmic graph theory: graph algorithms on parameterized graph families, e.g., bounded genus, bounded treewidth, or excluded minor graphs.
- Distributed algorithms: fast distributed algorithms that depend on extra parameters of the network graph, such as the diameter or the maximum degree.
- Spectral graph theory: fast algorithms on graphs with nice spectral properties, such as graphs with large expansion.
On the mathematics side, my main interests are probabilistic and extremal combinatorics, and structural graph theory.
I am a third-year PhD student in the School of Computer Science at Carnegie Mellon University and am part of the Algorithms and Combinatorial Optimization (ACO) group
. I am fortunate to be co-advised by Prof. Anupam Gupta
and Prof. Bernhard Haeupler
. I also obtained my bachelor's degree in computer science at CMU, with a double major in math.