Hey! I’m Mateo, an Associate Partner and Data Scientist at Foster and Partners. I completed my PhD at the Centre for Advanced Spatial Analysis, as part of the Alan Turing Institute doctoral program, where I focused on quantifying urban segregation and human behaviour in cities using advanced network analysis and information theory.

At Foster and Partners, I’ve led data-driven projects that influence urban design and analytics, with my tools and insights featured at international conferences. Previously, I also worked at SignalBox developing algorithms for transport networks.

Currently, my work deals with Complex Networks, Data Science and their application to the study and modeling of social and urban systems.I am deeply interested in leveraging AI to tackle complex urban challenges, aiming to integrate sophisticated data analysis into actionable insights for urban development.

You can find my full resume here.


PROJECTS

Analyzing Transport Networks

Interactive Web tool to explore centrality measures of the metro systems of London, New York, Chicago, and Santiago de Chile. The time-weighted graphs were constructed using publicly available GTFS data and visualized using javascript. Click on the image to view the tool, along with a more indepth description.

placeSpace

placeSpace is an interactive online platform that enables users to visualize and explore amenity location and distribution in London. The platform originates from the need to interpret and assess the complexity of cities in terms of agglomeration economies.


urbanPulse

Our collective activities in the city unfold in time and space in a repeating fashion. These cyclic patterns of actions and interactions create a particular rythm, an urban ‘Pulse’ influenced by socio-cultural and physical aspects of our environment.

Increasingly people use online networks to interact, and even though these interactions are virtual, they take place in physical space. By retreiving the digital traces they leave behind we can visualize these cyclic spatio-temporal patterns in a city.