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Syed A. M. Shihab is an Assistant Professor of Aeronautics and Engineering at ����ֱ�� State University, where he leads the Green and Advanced Mobility Engineering (GAME) lab. He holds a Ph.D. in Aerospace Engineering from Iowa State University and a B.S. in Electrical and Electronic Engineering from American International University Bangladesh. He currently teaches Modeling and Forecasting for Aviation Logistics Planning (AERN 65230) and Introduction to Aerospace Engineering (ENGR 15500).

Driven by an interest in operations planning for traditional and advanced air mobility, Dr. Shihab’s research focuses on developing data-driven, optimal decision-making systems for aviation based on artificial intelligence/machine learning, optimization, and operations research techniques. Research applications include air traffic management for manned and unmanned aircraft systems (ATM and UTM), UAV strategic and tactical deconfliction, UAV contingency management, and airline pricing and revenue management, scheduling/dispatching, and route/network planning. His research aims to: 1) maximize the performance of air transport systems operating in high dimension, dynamic and uncertain environments, with respect to attributes such as accessibility, efficiency, robustness, resilience, safety, scalability, passenger welfare, societal benefits and profitability; and 2) overcome the technical gaps and barriers needed to safely integrate the anticipated autonomous, high density, diverse operations of advanced air mobility (such as point-to-point passenger and cargo transportation, emergency medical services, search and rescue, and disaster relief using electric/hybrid, manned/human-in-the-loop/unmanned aircraft) in a modern National Airspace System.

Dr. Syed Shihab is administrator for the Green and Advanced Mobility Engineering (GAME) lab.

Research Areas

Operations Management for Traditional Aviation and Advanced Air Mobility, Air Traffic Management, UAS Emergency Landing, Multi-UAV Control, Decision Making under Uncertainty; Reinforcement Learning; Deep Learning; Value-based Systems Engineering

For more information about his research, visit the GAME lab website at . 

There are multiple funded openings available in his lab for motivated and hardworking Ph.D., M.S. and undergraduate students (future “GAMErs”) with strong programming and mathematical skills and a keen interest in developing intelligent decision-making and learning systems for aviation and transportation. Interested students should email him their CV, transcript(s), GRE score, TOEFL/IELTS score (for international applicants only), and publications if any. The email should also state their research interests, the motivation fueling their research interests, and why they are interested to join his research group.