Bin Yang received Sapere Aude Grant from Danmarks Frie Forskningsfond (Independent Research Fund Denmark). Sapere Aude grants aim at providing excellent young researchers, i.e. researchers who have already carried out top-class research in their field, with the opportunity to develop and strengthen their research ideas.
Bin’s project titled “A Data-Intensive Paradigm for Dynamic, Uncertain Networks” focuses on Data analytics and machine learning on massive trajectory data for greener and more efficient transportation. More specifically, his project will establish a dynamic and uncertain network model by analyzing massive trajectory data, which enables highly accurate, efficient, and scalable travel cost (e.g., travel time and greenhouse gas emission) modeling and pathfinding.
The project will have a remarkable impact as this project is well aligned with that ambition of making transportation green. Bin’s project will also bring solutions relating to dynamic, uncertain networks into the open domain and due to the data-driven nature of the project, it will also support emerging data science education activities. Read more here
Read more here: DFF Grant Page
