Seyed Iravani's research and teaching focus on the analytical tools of decision making. Students learn to create mathematical models that can be used in any industry and in every area of business: finance, production, logistics, supply chain, operations, and more.
Whether it is a factory manager making decisions about production schedules or a marketing team forecasting future demand, Iravani demonstrates the difference between ad hoc decision making and scientific decision making. This systematic way of thinking provides a broader perspective of the real problem; business decisions made using a mathematical framework typically create consensus faster.
PhD, Industrial Engineering, University of Toronto, Canada
MS, Industrial and System Engineering, Iran University of Science and Technology, Tehran, Iran
BS, Industrial and System Engineering, Iran University of Science and Technology, Tehran, Iran
Training course in Electronic and Electrical Engines and Relays, Tehran Institute of Technology, Tehran, Iran
Applications of stochastic processes and queuing theory in the design and control of manufacturing; service operations systems and supply chains