Rajesh Ganesan

Operations research deals with the application of advanced mathematics and computational methods to help make better decisions involving large and complex systems. There are many uses for operations research, but one of the most difficult problems that Rajesh Ganesan investigates is the sequential decision-making problems under uncertainty. His operations research applications include decision-making in cybersecurity, defense, health care, and air traffic management. Ganesan focuses his research at the Center for Secure Information Systems on the dynamic allocation of cybersecurity analyst resources to detect intrusions and maintain a desirable level of operational effectiveness. In one of his recent papers, he provided a framework for establishing and maintaining an effective cybersecurity analyst workforce to minimize cybersecurity risk.  His healthcare research work addresses a very important public policy and ethical problem: who, among those waiting, should be selected for a liver transplant, not only minimizing geographical disparity in access to livers but also extending organ life.  

In a recent paper, Ganesan explored the use of a fundamental reinforcement learning (RL) model for determining convoy schedules and route clearance assignments in light of attack dangers faced by transportation networks where improvised explosive device (IED) attacks are common. There is an exigent need for a timely solution to this dangerous and enduring problem faced by US military personnel. Ganesan’s research has offered opportunities for meaningful improvements to the safety of convoys using RL algorithms; the same research could one day be applied to other safety and risk management processes in the civilian environment. At the Center for Air Transportation Systems Research (CATSR), Ganesan’s research is focused on air traffic management issues such as minimizing taxi waiting time in busy airports. This work is very important due to the huge economic impact of delayed and canceled flights on all stakeholders of the air transportation industry. Mason’s CATSR was founded in 2003. Its Air Transportation Laboratory provides a program of cutting-edge research, development, and education in the area of modern air transportation management.

Research

2012 - 2015: Stochastic Simulation Optimization: An Optimized Approach. Funded by National Science Foundation.

2007 - 2014: NSF New GK-12 SUNRISE: Schools, University 'N' (and) Resources In the Sciences and Engineering- A NSF GMU GK-12 Fellows Project. Funded by National Science Foundation.

2007 - 2009: NSFNew GK-12 SUNRCS: School, University 'N' (and) Resources in the Sciences and Engineering - A NSFGMU GK-12 Fellow Project. Funded by National Science Foundation.

Research Interests

Air Transportation, Decision Support Systems, Optimization, Probabilistic Modeling, Simulation, Stochastic Processes

Honors and Awards

• Teacher of Distinction Award, Center for Teaching Excellence
• INFORMS QSR Council member- elected position, INFORMS

Degrees

• PhD, Industrial and Management Systems Engineering, University of South Florida
• MA, Mathematics, University of South Florida
• MS, Industrial and Management Systems Engineering, University of South Florida
• BS, Mechanical Engineering, National Institute of Technology, Calicut, India