Research — MIT Media Lab

We are an interdisciplinary research lab working to invent the future of

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climate change
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collective intelligence
wiesner
makers
internet of things
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performance
fabrication
neural interfacing and control
bionics
interactive
ecology
autonomous vehicles
women
cognitive science
perception
nonverbal behavior
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long-term interaction
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marginalized communities
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autism research
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orthotic design
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electrical engineering
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water
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The Power of Without

The Power of WITHOUT is a research theme in the City Science group. The theme proposes that heavy infrastructure solutions are not financ...

Research

Personal Robots

Building intelligent personified technologies that collaborate with people to help them learn, thrive, and flourish.

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City Science

Looking beyond smart cities

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Social Machines

Promoting deeper learning and understanding in human networks

Post Research

Ariel Noyman's work on CityScope selected for the Young Talent exhibition at Hebei International Industrial Design Week (HIDW)

The “HIDW Young Talent” exhibition addressed three topics: Manufacturing of Tomorrow, Future Craft, and City Catalyst.

Project Research

Theme | Mobility On-Demand

Urban populations around the world are rapidly growing. To improve livability, urban residents must reduce dependency on fossil fuels and...

Project Research

[bike] swarm

As bikes navigate city streets after dark, they are often equipped with lights. The lights make the bikes visible to cars or other bikers...

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Camera Culture

Making the invisible visible–inside our bodies, around us, and beyond–for health, work, and connection

Publication Research

CityScopeAR: Urban Design and Crowdsourced Engagement Platform

Noyman, Sakai, Larson 2018. CityScopeAR: Urban Design and Crowdsourced Engagement Platform. CHI 2018, 4,2007

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Poetic Justice

Exploring new forms of social justice through art

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Human Dynamics

Exploring how social networks can influence our lives in business, health, governance, and technology adoption and diffusion

Archived

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Collective Learning

Transforming data into knowledge

Archived

Project Research

Streetchange

Computer vision uncovers predictors of physical urban change

Archived

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Sculpting Evolution

Cultivating wisdom through evolutionary and ecological engineering

Post Research

City Science team wins Best Student Paper Award at Computing Conference 2020

Congratulations to City Science researchers Alex Berke, Jason Nawyn, Thomas Sanchez Lengeling, and group head Kent Larson!

Archived

Research

Scalable Cooperation

Reimagining human cooperation in the age of social media and artificial intelligence

Project Research

Reversed Urbanism

Predicting Urban Performance through Behavioral Patterns in Temporal Telecom DataThis study explores a novel method to analyze diverse be...

Archived

Project Research

AI, Automation, Labor, and Cities: How to map the future of work

Should workers worry about automation and AI?Many workers, policy makers, and researchers are asking themselves exactly this question. Bu...

Archived

Project Research

Moral Machine

The Moral Machine is a platform for gathering a human perspective on moral decisions made by machine intelligence, such as self-driving c...

Archived

Project Research

Theme | CityScope

City Science researchers are developing a slew of tangible and digital platforms dedicated to solving spatial design and urban planning c...

Project Research

ChampScope

Virtual CityScope Champs-Élysées is an interactive and immersive platform that explores the future of Paris’ most important street.

Archived

Research

Open Agriculture (OpenAg)

Open Agriculture Initiative (OpenAg)

Project Research

CityScope Champs-Élysées

An interactive platform to improve decision-making related to the revitalization of the Champs ÉlyséesCityScope Champs-Élysée is a ...

Publication Research

Urban Swarms: A new approach for autonomous waste management

A. L. Alfeo et al., "Urban Swarms: A new approach for autonomous waste management," 2019 International Conference on Robotics and Automation (ICRA), Montreal, QC, Canada, 2019, pp. 4233-4240.

Project Research

The Deep Image of the City

How do you image a city that doesn't exist? DeepScope is a novel platform for interactive, real-time, and setup-less urban design vi...

Project Research

City Science Network

MIT City Science has developed an international network of cooperative City Science LabsWe are developing concepts and key technology tha...

Project Research

CityScope Volpe

CityScope Volpe is demonstrating most of the urban planning, analysis, and prediction features developed for the CityScope project. The s...

Project Research

City Science Lab Hamburg

MIT City Science is working with HafenCity University to develop CityScope for the neighborhood of Rothenburgsort in Hamburg, Germany. Th...

Project Research

Aalto Campus-as-a-Service Simulations

How can we get more value from the same buildings? Cities contain many different resources and spaces and typically, these resources...

Publication Research

Reversed urbanism: Inferring urban performance through behavioral patterns in temporal telecom data

Noyman, A., Doorley, R., Xiong, Z., Alonso, L., Grignard, A., & Larson, K. (2019). Reversed urbanism: Inferring urban performance through behavioral patterns in temporal telecom data. Environment and Planning B: Urban Analytics and City Science, 46(8), 1480–1498. https://doi.org/10.1177/2399808319840668

Project Research

City Science Lab Andorra

Andorra and the City Science research group at the MIT Media Lab are taking on the challenge of turning Andorra into an “Internationally ...

Project Research

BASIC: Blockchained Agent-based Simulator for Cities

Autonomous vehicles (AVs), drones, and other types of robots will revolutionize our way of traveling and understanding urban space. In or...

Project Research

MoCho: Mobility choices and societal impacts

MoCho (short for "Mobility Choices") is a CityScope module focused on mobility choices and societal impacts. This tool helps pr...

Publication Research

What's your MoCho? Real-time Mode Choice Prediction Using Discrete Choice Models and a HCI Platform

Doorley, Ronan & Noyman, Ariel & Sakai, Yasushi & Larson, Kent. (2019). What's your MoCho? Real-time Mode Choice Prediction Using Discrete Choice Models and a HCI Platform. UrbComp SIGKDD 2019

Project Research

City as Classroom, City as Laboratory

Often, we neglect to see the city as living, complex, and dynamic. However, shrouded by its masses of concrete and steel lie unique ecosy...

Project Research

City Science Lab Aalto

Aalto University, Finland, and the MIT Media Lab’s City Science group are co-developing a version of the MIT CityScope platform for urban...

Archived

Project Research

Field Experimentation in Boston's Intertidal Zone

The Intertidal Experimentation Workshop will take place September 29 and 30 (9am to 2pm) at the MIT Media Lab, open to students ages 8-14...

Archived

Article Research

Home

How the home will be disrupted and transformed by radical technological change.

Project Research

Measuring and reducing social segregation in cities

We use high-resolution geospatial data collected from mobile phones to measure social segregation at an unprecedented resolution in citie...

Project Research

CityScope PlayGround: MIT East Campus

This project depicts the design, deployment and operation of a Tangible Regulation Platform, a physical-technological apparatus made for ...

Publication Research

Finding Places: HCI Platform for Public Participation in Refugees’ Accommodation Process

Finding Places: HCI Platform for Public Participation in Refugees’ Accommodation Process. Ariel Noyman , Tobias Holtz, Johannes Kröger, Jörg Rainer Noennig, Kent Larson. a Massachusetts Institute of Technology, Media Lab, Changing Places Group, Cambridge MA, b HafenCity University Hamburg, CityScienceLab, c HafenCity University Hamburg, Lab for Geoinformatics & Geovisualization

Article Research

City Science Lab Taipei

NTUT, MIT sign ‘smart’ development agreement

Publication Research

Toward understanding the impact of artificial intelligence on labor

Frank, Morgan R., David Autor, James E. Bessen, Erik Brynjolfsson, Manuel Cebrian, David J. Deming, Maryann Feldman, et al. “Toward Understanding the Impact of Artificial Intelligence on Labor.” Proceedings of the National Academy of Sciences, March 25, 2019, 201900949. https://doi.org/10.1073/pnas.1900949116.