Guojun Gan, PhD

Assistant Professor, Mathematics (Affiliate)

Research Overview

At a broad level, my research interests lie in variable annuity hedging and pricing, data clustering, and applications of data mining techniques in industry. In the area of variable annuity hedging and pricing, I am interested in developing methods that can price a huge portfolio of variable annuity contracts efficiently in terms of accuracy and speed. Data clustering is the most basic form of unsupervised learning that aims to divide a collection of data items into groups or clusters, such that items within a cluster are more similar to each other than they are to items in other clusters. From the technical perspective, I am interested in developing efficient algorithms to cluster high-dimensional data and large data sets. From the application perspective, I am interested in applying data clustering and other data mining techniques to industry, especially the Financial industry and the health care industry.

Education

PhD, 2007, Applied Mathematics, York University, Canada
MSc, 2004, Applied Mathematics, York University, Canada
BS, 2001, Computational Mathematics, Jilin University, China

Recent Publications