Guojun Gan

Assistant Professor

Department of Mathematics

University of Connecticut

At a broad level, my research interests lie in data mining and actuarial science. Data mining is an analytic process designed to explore large amounts of data (also known as “big data”) in search of consistent patterns and/or systematic relationships between variables, and then to validate the findings by applying the detected patterns to new subsets of data. Actuarial science is the discipline that applies mathematical and statistical methods to assess risk in insurance, finance and other industries and professions. In the area of data mining, I am especially interested in developing efficient algorithms for data clustering, which is the most basic form of unsupervised learning that aims to divide a collection of data items into homogeneous groups or clusters. I am also interested in applying data clustering and other data mining techniques to solve problems in bioinformatics, actuarial science, computational finance, etc. In the area of actuarial science, I am especially interested in developing efficient algorithms and models to solve the problems related to variable annuity valuation.

Papers

A list of my publications can be found at Google Scholar or this page.

Books

Data Clustering
Guojun Gan, Chaoqun Ma and Jianhong Wu
Data Clustering: Theory, Algorithms, and Applications (Second Edition)
SIAM, 2020
Metamodeling for Variable Annuities
Guojun Gan and Emiliano A. Valdez
Metamodeling for Variable Annuities
Chapman & Hall/CRC Press, 2019
Actuarial Statistics with R: Theory and Case Studies
Guojun Gan and Emiliano A. Valdez
Actuarial Statistics with R: Theory and Case Studies
ACTEX, 2018
An Introduction to Excel VBA Programming
Measure, Probability, and Mathematical Finance
Guojun Gan, Chaoqun Ma and Hong Xie
Measure, Probability, and Mathematical Finance: A Problem-Oriented Approach
Wiley, 2014
Data Clustering in C++
Guojun Gan
Data Clustering in C++: An Object-Oriented Approach
Chapman & Hall/CRC Press, 2011
Data Clustering
Guojun Gan, Chaoqun Ma and Jianhong Wu
Data Clustering: Theory, Algorithms, and Applications
SIAM, 2007

Edited Volume

Proceedings of ADMA 2018
Guojun Gan, Bohan Li, Xue Li, and Shuliang Wang
Proceedings of the 14th International Conference on Advanced Data Mining and Applications (ADMA 2018), Nanjing, China, November 16 - 18, 2018