University of Southern California

Arif Ansari
Associate Professor of Clinical Data Sciences and Operations

USC Marshall School of Business
Los Angeles, CA 90089-0808

Phone: 
213-821-5521
Education: 
PhD, MS, University of Southern California; MTech, IIT- Madras; BEng, Anna University

Overview

Arif Ansari is an expert in the area of data mining, business intelligence, data warehousing, and intelligent systems and technologies, a field in which he has fifteen years of research experience. He has published in IEEE Transactions on Systems and Man and Cybernetics. Professor Ansari received Marshall's Golden Apple Award in 2006.

Research

Partitioning Methods: Exploratory Analysis of Childhood Obesity Intervention Data 2012
Identifying Threshold of Social Influences on Lifetime Smoking Status among Adolescents? A Recursive Partitioning Approach 2012
Combinations of Perceived Built Environmental Factors Differentiating Physically Active vs. Non-Active Adults – A Decision Tree Classification Approach 2012
Business Intelligence in Web Analytics 2011
Building Custom Business Intelligence and Data Mining tool, using Excel and SQL Databases tool. 2010
Implementing Web Content Mining for iPhone App Domain. 2010
Teaching Data Warehousing, Business Intelligence and Data Mining from Business Strategy point of View 2009
Alumni Data Analysis 2009
Data Warehousing and Mining using Oracle Databases 2009
Leveraging Business Intelligence: Using Information for Customer Value Management and Online Security for Banks 2007
A Study on the Convergence of Different Learning Strategies in a Multi-Teacher Environment 2000
A Generalized Learning Algorithm for an Automaton Operating in a Multiteacher Environment 1999
A Pruning Technique to Increases the Rate of Convergence on Learning Algorithms 1999
Learning Behavior of a Stochastic Automaton Operating Under a Multi-input Multi-output Learning Algorithm 1997
Data Mining In Mobile Space
Ensign Health Care Case
Learning Algorithm for Different Strategies in Multi-Teacher Environment
Segmentation and Valuation of ADJACK
The Principles of Data Mining and Web Marketing