Majid Rostami Shahrbabaki Email & Phone Number

Postdoctoral Researcher with a demonstrated history of working in the academic and industry. Skilled in Computer Science, Control Systems Design, Traffic modeling and estimation, Neural Networks, Matlab and Python programming. Traffic congestion is a widespread time-consuming phenomenon that significantly affects many aspects of the quality of the life. An efficient use of the existing infrastructure, using advanced traffic control strategies and technologies, can lead to reduced congestion, reduced emissions, reduced fuel consumption and improved safety.With a sophisticated background in control theory, machine learning, and simulation tools, I work in the area of Intelligent Transportation Systems (ITSs) in various aspects such as traffic state estimation, optimal speed and advisory system, smart managing of electric vehicles charging, etc.With the development of in-vehicle and communication technologies, Connected and Automated Vehicles (CAVs) have emerged as a new data source and controlling measure for traffic management and control. Over the past years, I have continuously published several paper in the area of VACs in international journals and conferences proceedings.I am honored to serve the external collaborator of TrafficFluid (2019-2024), i.e., a European Research Council (ERC) Advanced Grant. In this project, we develop lane-free vehicular traffic modeling and explore the use cases for future fully automated road traffic control.I am open for collaboration with researchers in academy and industry over the related topics. You may contact me via LinkedIn message or email (majid.rostaim@tum.de).

Listed skills include Simulations, Matlab, Microsoft Office, Control Systems Design, and 29 others.