Santhanakrishnan Narayanan

Santhanakrishnan Narayanan is a postdoctoral researcher and senior mobility scientist at the Technical University of Munich (TUM). He completed his undergraduate studies in Civil Engineering at SASTRA University in India, before joining Larsen & Toubro Construction, an Indian multinational conglomerate, where he contributed to the Chennai Metro project as a Graduate Engineer Trainee and later as a Senior Engineer. He then pursued an M.Sc. in Transportation Systems at TUM. Following his master's degree, he joined our Chair as a Mobility Scientist, undertaking a doctorate alongside his work.

During his tenure, he has collaborated with institutes across multiple countries and engaged with a wide range of stakeholders. He played a pivotal role in managing the EU Horizon 2020 project MOMENTUM, overseeing both technical and administrative tasks. He was also involved in the TUM IGSSE project MO3 and and served as a guest researcher in the Machine Learning for Smart Mobility (MLSM) group at the Technical University of Denmark (DTU). In addition, he collaborated with DLR Institute of Transport Research on Europe's largest cargo cycle testing project Ich entlaste städte. His work in this area, specifically on analyzing travel time differences between cargo cycles and cars, earned him the Best Research Paper award from the TRB Urban Freight Transportation Committee. Currently, he manages the EU Horizon Europe project PHOEBE.

Santhanakrishnan's research primarily focuses on developing modeling frameworks for emerging mobility solutions, combining traditional statistical modeling with advanced data-driven methodologies. His work spans conventional and automated shared mobility services in passenger transport, as well as cargo cycles in commercial transport. His publications reflect both theoretical and applied research, including comprehensive review articles, all aimed at enhancing system performance, efficiency, and safety. He also serves as a reviewer for top transportation journals, such as Transportation Research Part C : Emerging Technologies, Transportation and European Transport Research Review.

His pioneering research on graph neural networks at our Chair has led to multiple publications and new project funding within a short span. Recently, he has initiated research on transformer and large language model (LLM)-based solutions to address various transportation challenges.