MODE SHIFT BEHAVIOR MODELS
Survey-based project estimating time, cost, and comfort trade-offs in urban mode choice using discrete choice models. Results support scenario testing for sustainable transit.
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Majharul Islam (anmajharul) is a Transportation Engineer from Bangladesh specializing in smart mobility, traffic simulation, travel behavior modeling, and data-driven transportation analytics. With a B.Sc. in Civil Engineering from Bangladesh University of Business and Technology (BUBT), his expertise spans intelligent transportation systems (ITS), GIS-based transportation planning, urban traffic flow optimization, road safety analysis, and sustainable mobility solutions. His research portfolio includes transportation systems analysis using survey-driven data (300+ responses), computational simulation frameworks, and 12+ analytical tools and frameworks. Majharul bridges traditional civil engineering infrastructure design with modern computational approaches — including deep learning and reinforcement learning — to create data-informed solutions for complex urban transportation challenges. He also holds specialized certificates in Geographic Information Systems (GIS) from UC Davis, Deep Learning from DeepLearning.AI, and Reinforcement Learning from the University of Alberta.
Majharul Islam's research focuses on transportation systems analysis through travel behavior modeling, traffic simulation, GIS, and data-driven analytics. He develops and evaluates analytical frameworks to support sustainable mobility and intelligent transportation systems. His work spans 3+ research projects, 300+ survey responses analyzed, and 12+ tools and frameworks applied.








My research focuses on transportation systems analysis through travel behavior modeling, traffic simulation, GIS, and data-driven analytics. I develop and evaluate analytical frameworks to support sustainable mobility and intelligent transportation systems.

