Vahid Moosavi

Senior researcher at ETH Zurich

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