• Cotutela con mondo esterno

This course tries to bridge the gap between urban planning and the most recent advances in physical and computational sciences. Integrating knowledge across these apparently diverse fields is key to the emerging field of the built environnement, which attempts to analyze and understand cities through the eyes of both quantitative results rooted in the experimental method, and the rich knowledge acquired in centuries of social and human studies of cities.

Specific questions this course will try to address are:

What brings us together or tears us apart in cities?

How do we move, socialize and behave in cities?

How does data science help us uncover these hidden patterns, and inform the design of better cities?

By the end of the course, students should have developed:

- An understanding of  the spatial scale of urban analysis and data;

- An ability to interpret big data trough technical approaches 

- An ability to critically evaluate the results and findings 

- A knowledge of artificial intelligence applied to urban sciences

- A critical approach to mobility and urban design to avoid segregation

Since their emergence around 10,000 years ago, cities have evolved into the most magnificent and consequential artifacts in human history. Today, Big Data and new computational methods and tools are empowering us to study these forces quantitatively for the first time in history. This course studies the fundamental tensions of urban development, uncovering the laws of our cities explored through new methods, borrowed from experimental physics and computational sciences. The resulting equations and models hold the keys to our cities — and to our common urban future.

The course meets once a week for lectures and class work and discussions. There are no formal prerequisites for the course. Students are expected to come to class having read the required readings for the week.

Projects will be graded on presentation quality, innovation, potential feasibility, and appropriateness to the site and its brief. Late submissions for all assignments will be penalized, except in cases of documented disabilities or arrangements with the instructor.