At the center of my research are data‐driven analytical models, which are indispensable tools for studying complex decision making problems in Business. I believe that only a careful analysis of data accompanied with meticulous decision analytical modeling can deliver solutions that are both insightful and practically relevant. Generally speaking, I am interested in exploring the innovative combinations of Data Sciences and Operations Research methodologies and their applications to managerial decision making problems.
The methodological scope of my research is quite broad, ranging from Mathematical Modelling and Optimization, Simulation, Queueing Theory to Data Analysis techniques. In terms of application, my research so far has explored different areas of Healthcare Operations, Services and Policy Management. I have been developing decision analytical models that support health policy makers, healthcare managers, health professionals, and patients in making better decisions that lead to better health outcomes and lower costs. Even though most of my research has been in the area of healthcare, the methodologies I have used and developed have the potential to be applied to other areas of Operations Management.
Fostering analytical thinking skills is my ultimate goal as an instructor in Operations Management and Business Analytics. I find it very rewarding to see how studentsʹ thinking framework, problem-solving approach, and analytical capabilities are enhanced when they learn new concepts. In every course that I teach, I would like my students to create a deep understanding of different analytical tools in that area, as well as, their strengths and limitations. This will help them identify the existing managerial trade‐offs, choose the proper tool to solve the problem, interpret the results, and design effective solutions.
A problem-solving course which introduces the student to deterministic and stochastic models which are useful for production planning and operations management in business and government. Note: Students are expected to have basic familiarity with microcomputer applications. Prerequisite: MATH 114 or equivalent and STAT 151 or equivalent.Fall Term 2022