Welcome to visit Dr. Chung-Shou Liao’s lab! Our research mainly focuses on designing efficient algorithms that can be used to solve difficult combinatorial optimization problems from real applications. Our lab has developed approximation algorithms with theoretical analysis for well-known hard problems such as online shortest path, facility location, domination, and scheduling and packing problems. Other areas of interest include computational geometry, graph theory, and machine learning. In particular, we have also extended our study to systems biology: we have proposed graph-theoretic algorithms for global alignment between multiple biological networks and conducted comparative analysis across species, which can find real applications to social networking and recommendation systems. In recent years, we put more attention on dynamic and online algorithms for the fundamental problems such as data clustering and classification, as well as their applications to AI manufacturing.