Research
Overview
Yuki Amano works in theoretical computer science, with a focus on the design and analysis of algorithms. Research interests include combinatorial optimization, approximation algorithms, online optimization, and competitive analysis.
Topics
Online algorithms and competitive analysis
This area studies algorithms that must make decisions without full knowledge of future inputs. A central goal is to understand how well such algorithms can perform compared with an optimal offline solution.
Approximation algorithms
This topic concerns efficient algorithms for computationally hard optimization problems, especially when exact solutions are impractical and provable approximation guarantees are useful.
Graphs and combinatorial optimization
This line of work studies graph-theoretic optimization problems and related combinatorial structures.
Algorithmic game theory
This topic connects algorithm design with game-theoretic questions, including fairness and strategic decision-making.