Vahid Moosavi
Senior data scientist at Swiss Re, Zurich
Personal Update: I am no longer in academia and I have moved to industry and started a new position at Swiss Re, focusing on building data driven products in the context of risk management.
Academic Interests
Intersection of machine learning and complex urban and spatial systems
Planetary urban modeling: Modeling different urban phenomena at the scale of planet using open source geo-data streams
Data driven urban computing for fast and scalable modeling of urban flows (e.g. flood, wind, heat, etc.)
City as text: Data driven hierarchical representation of urban stocks (e.g. floor plans, buildings, parcels, neighborhoods, etc.)
Health and place (e.g. urban characteristics and urban air pollution)
Urban economy and real estate dynamics
Transportation networks dynamics
Multidimensional geo-visualizations and spatial search
Data driven modeling across disciplines
Structural design and optimization
Dynamical networks and systemic risk
Financial time series forecasting
Manufacturing and supply chain systems
Atmospheric science
Machine learning and deep learning literacy for non-computer scientists
Other computational and modeling concepts (Mainly from 2006-2010)
Agent based modeling
System dynamics
Optimization methods
Multi criteria decision-making