劉智弘 Chih-Hung Liu

Associate Professor, Department of Electrical Engineering, National Taiwan University

Major Research Areas:

Computational Geometry, Algorithms, Algorithmic Aspects of Machine Learning

Research Summary:

--- Computational Geometry.

Computational Geometry is a fundamental area in Theoretical Computer Science, where we investigate the combinatorial properties of geometric problems and develop efficient algorithms. I am focused on proximity problems, involving distances between geometric objects. For example, I have published many results for Voronoi diagrams. Voronoi diagrams lie at the heart of computational geometry and serve as an extremely important tools for proximity problems. Furthermore, I am also studying the k nearest neighbors problem, which have many applications in diverse areas including data science.  

 

 

--- Algorithmic Aspects of Machine Learning

Algorithmic Aspects of Machine Learning are a brand-new area in Theoretical Computer Science and Machine Learning. In the last two decades, machine learning has induced a technological revolution in diverse scientific and industrial disciplines. However, the behind-the-scene reasoning about its incredible success is still not completely clear from a theoretical perspective. Under these circumstances, Algorithmic Aspects of Machine Learning aim to study fundamental problems in Machine Learning from a theoretical perspective and develop efficient algorithms with theoretical guarantees. My main topics in Algorithmic Aspects of Machine Learning are Tensor Problem, Robust Statistics and Clustering.