Qualifications: Master of Information Technology (Honours) Bachelor of Commerce Bachelor of Information Technology Adrian Gepp’s primary research interest is in the area of business failure prediction. He has also undertaken research in cross-border river system management, semidefinite optimisation in finance, quantum computing and more recently fraud detection. Adrian attained first class honours for his postgraduate studies after receiving university medals as the most outstanding graduand for both his undergraduate degrees. Since then, he has taught finance, economics and statistics at undergraduate and postgraduate levels. He has also completed work with the ASX Schools Sharemarket Game and led a commercial software development project.
Articles
A Comparative Analysis of Decision Trees Vis-à-vis Other Computational Data Mining Techniques in Automotive Insurance Fraud Detection (with Kuldeep Kumar, J Holton Wilson, and Sukanto Bhattacharya), Journal of Data Science (2012)
A review of procedures to evolve quantum algorithms (with Phil Stocks), Genetic programming and evolvable machines (2009)
There exist quantum algorithms that are more efficient than their classical counterparts; such algorithms were...
Business failure prediction using decision trees (with Kumar Kuldeep and Sukanto Bhattacharya), Journal of forecasting (2009)
Accurate business failure prediction models would be extremely valuable to many industry sectors, particularly financial...
The role of survival analysis in financial distress prediction (with Kuldeep Kumar), International research journal of finance and economics (2008)
Accurate business failure prediction models would be extremely valuable to many industry sectors, particularly in...
Book Chapters
Business Failure Prediction Using Statistical Techniques: A Review (with Kuldeep Kumar), Some Recent Developments in Statistical Theory and Applications (2012)
Conference Papers
Business Failure Prediction using Survival Analysis (with Kuldeep Kumar), International Conference of business, economics and management disciplines (2006)
Accurate business failure prediction models would be extremely valuable to many industry sectors, particularly in...
Dissertation
An evaluation of decision tree and survival analysis techniques for business failure prediction (2005)
Accurate business failure prediction models would be extremely valuable to many industry sectors, particularly in...