Subhrasankha Dey, a postdoctoral researcher, focuses on the fields of spatial data science and sustainable mobility. He is an affiliate of the research group of the GIScience for Sustainability Transitions (GIST) Lab, located at Aalto University in Finland. During his doctoral studies, Subhrasankha focused on spatial network analysis, particularly stochastic modelling of mobility data to estimate traffic states in low- and mid-income cities. His research journey epitomises an interdisciplinary approach, blending statistical machine learning with sustainable solutions for Intelligent Transportation Systems (ITS). Delving into areas such as network flow and optimization, Bayesian statistics, geospatial computation, and sensor networks, his focus in mobility data-driven research is developing practical findings with positive environmental and socio-economic impacts.

At Aalto University, he actively engages in the MAPICO project. Here, he plays a role in developing novel methodologies to quantify carbon emissions in urban areas, with a specific emphasis on commuting-related footprints. Collaborating with colleagues, the aim is to map these footprints monthly in various cities across Finland, Sweden, and Norway. The practical applications of this research are rooted in informing transport planning strategies for more sustainable and eco-friendly outcomes.