Hussein Issa

Hussein Issa is an Associate Professor of Accounting Information Systems at Rutgers Business School. He received his PhD in Accounting Information Systems from Rutgers University in 2013. He led numerous research projects with banks, large multinational consumer products companies, a telecommunication company, one of the Big Ten university’s internal audit department, among others. His research focuses on the applications of artificial intelligence and machine learning to Auditing and Accounting. He developed different methodologies to identify and prioritize exceptions (which was the topic of his dissertation "Exceptional Exceptions"). In these projects, Hussein developed various statistical and machine learning models to address business problems, such as fraud detection, outlier identification, pattern recognition, operational efficiency, customer profiling, continuous control monitoring of procurement systems, among others. Hussein has also recently taken interest in Robotic Process Automation (RPA), generative AI, and the application of AIS methodologies to Government Reporting. Hussein also serves on the dissertation committees of several PhD students.

Hussein teaches/taught Data Mining and Business Intelligence (Doctorate of Business Administration), Advanced Design and Development of Information System (Masters in Accountancy in Governmental Accounting), Design and Development of Information System (Masters in Accountancy in Governmental Accounting), Information Technology in the Digital Era (Professional Accounting MBA), Audit Analytics (Undergraduate), and Introduction to Financial Accounting (Undergraduate). He also co-teaches a PhD level course discussing current topics in AIS Research.