about
In the years to come, solutions to the complex global problems, which are increasingly urban, will require an understanding of large amounts of data and a facility with analysis, visualization, sensors, and even the integration of artificial intelligence into planning and policy-making contexts in a democratic and ethical manner. At the same time, the fields of computer science and machine learning can benefit from the urgency and “hands-on” nature of the sorts of challenges presented in policy-making and urban planning contexts and can lead to democratic and ethical innovations of technology. In short: urban planners have excellent problems, and computer scientists have excellent tools.
The 11-6 degree aims to help undergraduates use their computer science skills to make positive social impacts. Students will learn the theory and practice of (1) urban planning and policy-making including ethics and justice; (2) statistics, data science, geospatial analysis, and visualization, and (3) computer science, robotics, and machine learning.
To accomplish these ends, the required subjects include core courses in both computer science and urban planning fundamentals, as well as lab and project-based courses that will help students synthesize and integrate across the two departments. On the Urban Studies and Planning side, students will also receive a grounding in the political, sociological, legal, and ethical aspects of collecting and using new information flows. On the Computer Science side, they will enhance their skills in programming, statistics, data visualization, applied spatial analysis and machine learning.
For the predominantly technically-minded undergraduates at MIT, working within real urban contexts and environments will expose them to:
- Fundamental and socially-relevant questions of equity, fairness, diversity, and implementation in a global context;
- Specific applications of technology and systems in environmental management, transportation, infrastructure financing, cybersecurity, provision of housing, and job creation.
- Diverse contexts in which technology is tested and used, especially at the critical intersections between government and industry; policy-making and implementation; and in both the developed and developing world.
UPCOMING EVENTS
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Degree Requirements
| COMPUTER SCIENCE REQUIREMENT | URBAN PLANNING REQUIREMENT |
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6.100A Introduction to Computer Science and Programming in Python
6.100B Introduction to Computational Thinking and Data Science
6.1010 Fundamentals of Programming
6.1200[J] Mathematics for Computer Science
6.1210 Introduction to Algorithm
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11.001[J] Introduction to Urban Design and Development
11.188 Urban Planning and Social Science Laboratory (CI-M)
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Select one of the following options:
Option 1 (12 units) 6.3800 Introduction to Inference
Option 2 (24 units) 18.06 Linear Algebra
OR 18.C06 Linear Algebra and Optimization AND
6.3900 Introduction to Machine Learning
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Select one of the following subjects:
6.4590[J] Foundations of Information Policy
11.002[J] Making Public Policy
11.011 The Art and Science of Negotiation
11.165 Urban Energy Systems and Policy
*6.4590[J] and 11.165 can count towards either the Urban Planning Requirements or the Urban Science Electives, but not both.
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URBAN TECHNOLOGY WORKSHOP |
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| Select One of the Following Options | |
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11.007 Urban and Environmental Technology Implementation Lab
11.138 Crowd Sourced City: Civic Tech Prototyping
11.154 Big Data, Visualization, and Society
*11.007, 11.138, and 11.154 can count towards the Urban Technology Workshop or the Urban Science Electives, but not both.
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ELECTIVES |
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Advanced Computer Science Electives | a minimum of 27 units
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Three Urban Science Electives | a minimum of 30 units |
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6.1020 Elements of Software Construction
6.1040 Software Studio
6.1060 Software Performance Engineering
6.1100 Computer Language Engineering
6.1120 Dynamic Computer Language Engineering
6.1220[J] Design and Analysis of Algorithms
6.1800 Computer Systems Engineering
6.1820[J] Mobile and Sensor Computing
6.1920 Constructive Computer Architecture
6.2040 Analog Electronics Laboratory
6.2050 Digital Systems Laboratory
6.2060 Microcomputer Project Laboratory
6.2061 Microcomputer Project Laboratory - Independent Inquiry
6.2090 Solid-State Circuits
6.2200 Introduction to Electric Power Systems
6.2220 Power Electronics Laboratory
6.2221 Power Electronics Laboratory - Independent Inquiry
6.2530 Introduction to Nanoelectronics
6.3100 Dynamical System Modeling and Control Design
6.3260[J] Networks
6.3720 Introduction to Statistical Data Analysis
6.3730[J] Statistics, Computation and Applications
6.4130[J] Principles of Autonomy and Decision Making
6.4210 Robotic Manipulation
6.4400 Computer Graphics
6.4510 Engineering Interactive Technologies
6.4830[J] Fields, Forces and Flows in Biological Systems
6.4860[J] Medical Device Design
6.5081 Multicore Programming
6.5151 Large-scale Symbolic Systems
6.5831 Database Systems
6.5931 Hardware Architecture for Deep Learning
6.6331 Fundamentals of Photonics
6.7201 Optimization Methods
6.8301 Advances in Computer Vision
6.8371 Digital and Computational Photography
6.8611 Quantitative Methods for Natural Language Processing
6.8701 Computational Biology: Genomes, Networks, Evolution
6.8711[J] Computational Systems Biology: Deep Learning in the Life Sciences
6.8721[J] Principles of Synthetic Biology
6.8801[J] Biomedical Signal and Image Processing
6.C01 Modeling with Machine Learning: from Algorithms to Applications
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2.00A Fundamentals of Engineering Design: Explore Space, Sea and Earth
4.032 Design Studio: Information Design and Visualization
4.432 Modeling Urban Energy Flows for Sustainable Cities and Neighborhoods
6.4590[J] Foundations of Information Policy
11.007 Urban and Environmental Technology Implementation Lab
11.024 Modeling Pedestrian Activity in Cities
11.074 Cybersecurity Clinic
11.113 The Economic Approach to Cities and Environmental Sustainability
11.123 Big Plans and Mega-Urban Landscapes
11.137 Financing Economic Development and Housing
11.138 Crowd Sourced City: Civic Tech Prototyping
11.148 Environmental Justice: Law and Policy
11.154 Big Data, Visualization, and Society
11.155[J] Data and Society
11.156 Healthy Cities: Assessing Health Impacts of Policies and Plans
11.158 Behavioral Science and Urban Mobility
11.165 Urban Energy Systems and Policy
11.169 Global Climate Policy and Sustainability
12.010 Computational Methods of Scientific Programming
15.276 Communicating with Data
IDS.012[J] Statistics, Computation and Applications
IDS.060[J] Environmental Law, Policy, and Economics: Pollution Prevention and Control
*6.4590[J] and 11.165 can count towards either the Urban Planning Requirements or the Urban Science Electives, but not both.
*11.007, 11.138, and 11.154 can count towards the Urban Technology Workshop or the Urban Science Electives, but not both. |
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SENIOR THESIS / PROJECT Select one of the following options:
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| Option 1 | Option 2 |
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MIT UROP (No more than 6 units)
AND 6.UAR Seminar in Undergraduate Advanced Research (CI-M)
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11.THT[J] Thesis Research Design Seminar (CI-M)
AND 11.THU Undergraduate Thesis
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COURSE PETITION PROCESS
Students who apply for a course petition should first submit a petition form and contact their advisor for a brief consultation. Students need to explain why the petition is necessary and how it fits into their curriculum. Advisor will evaluate the feasibility of each case and endorse a petition request to DUSP undergraduate administrator. For more specific questions, students should contact DUSP undergraduate administrator Sandra M. Elliott (sandrame@mit.edu).
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faculty
FACULTY
Do you have questions about the major, classes, or on-going research? Want to get involved with the new major or discuss how 11-6 would prepare you for future endeavors? Listed below are volunteer faculty and staff who are eager to answer your questions, please reach out to them directly via the provided email address.
Eran Ben-Joseph
Professor of Landscape Architecture and Urban Planning
Eran Ben-Joseph is the Class of 1922 Professor of Landscape Architecture and Urban Planning in the Department of Urban Studies and Planning at the Massachusetts Institute of Technology. Eran served as Head of the Department of Urban Studies and Planning at MIT from 2013 to 2020.
Sarah Williams
Associate Professor of Technology and Urban Planning
Sarah Williams is an Associate Professor of Technology and Urban Planning. She also is Director of the Civic Data Design Lab at MIT's School of Architecture and Planning. The Civic Data Design Lab works with data, maps, and mobile technologies to develop interactive design and communication strategies that expose urban policy issues to broader audiences. Trained as a Geographer (Clark University), Landscape Architect (University of Pennsylvania), and Urban Planner (MIT), Williams's work combines geographic analysis and design. Williams is most well known for her work as part of the Million Dollar Blocks team which highlighted the cost of incarceration, Digital Matatus which developed the first data set on a informal transit system searchable in Google Maps, and a more a recent project that uses social media data to understand housing vacancy and Ghost Cities in China.
David Hsu
Associate Professor of Urban and Environmental Planning
David is an Associate Professor in the Department of Urban Studies and Planning at the Massachusetts Institute of Technology. His research and teaching areas focus on how to use environmental policy and planning to shape cities to become more efficient in their use of resources, more livable, and healthier. Much of his work seeks to assist local policymakers and environmental advocates directly in the stages of policy design and implementation.
Joe Ferreira
Professor, Post-Tenure
Professor Ferreira was the founding director of the Planning Department's Computer Resource Lab and is now head of Urban Information Systems. He teaches analytical methods and computer-based modeling for planning and urban management including courses involving extensive use of geographic information systems (GIS) and database management. Both Prof. Ferreira's undergraduate degree (in electrical engineering) and his PhD degree (in operations research) are from MIT. His research uses GIS and interactive spatial analysis tools to model land use, transportation, and environmental interactions and to build sustainable information infrastructures for supporting urban and regional planning. He is a past-president of the Urban and Regional Information Systems Association (URISA) and has been principal investigator of numerous research projects studying job‐housing balance, urban performance measures, and urban information infrastructure. His current research includes the Future Urban Mobility project within the Singapore/MIT Alliance for Research and Technology where he is the SMART Research Professor of Urban Information Systems.
Andres Sevtsuk
Associate Professor of Urban Science and Planning
Andres Sevtsuk is a Charles and Ann Spaulding Career Development Associate Professor of Urban Science and Planning at the Department of Urban Studies and Planning, where he also leads the City Form Lab. His work bridges urban design with spatial analysis and urban technology. He has led various international research projects; exhibited his research at TEDx, the World Cities Summit and the Venice Biennale; and received the President’s Design Award in Singapore, International Buckminster Fuller Prize and Ron Brown/Fulbright Fellowship. Before joining MIT, Andres was an Associate Professor of Urban Planning and Design at the Harvard Graduate School of Design. He holds a PhD from the Department of Urban Studies and Planning and an SMArchs in Architecture and Urbanism from MIT.
Catherine D'Ignazio
Associate Professor of Urban Science and Planning
Catherine D'Ignazio is an Assistant Professor of Urban Science and Planning in the Department of Urban Studies and Planning at MIT. She is also Director of the Data + Feminism Lab which uses data and computational methods to work towards gender and racial equity, particularly as they relate to space and place. D'Ignazio is a scholar, artist/designer and hacker mama who focuses on feminist technology, data literacy and civic engagement. Prior to joining DUSP, D'Ignazio was an Assistant Professor of Data Visualization and Civic Media at Emerson College in the Journalism Department, taught for seven years in the Digital + Media graduate program at Rhode Island School of Design and did freelance software development for more than ten years. She holds an MS from the MIT Media Lab, an MFA from Maine College of Art, and a BA in International Relations (Summa Cum Laude, Phi Beta Kappa) from Tufts University.
Cong Cong
Lecturer of Urban Science and Planning
Cong Cong is a Lecturer of Urban Science and Planning at the Department of Urban Studies and Planning at MIT. Her research focuses on using data, computing and informatic tools to inform more effective decision-making. She explores the intersection of computer science and urban planning and uses large-scale urban modeling, spatial big data analysis, and mapping and visualization as exploratory techniques. Her recent work highlights ways for open data and open-source tools to better support planning tasks.
Eric Huntley
Lecturer of Urban Science and Planning
Eric Huntley joined DUSP in August 2017 as a Technical Instructor of GIS, Data Visualization and Graphics. Huntley's work combines methods and forms of representation in novel ways to produce compelling and visually-rich narratives that draw from geography, data science, and design. He has years of GIS teaching experience and an expansive skillset that includes data visualization, GIS and spatial analysis, web mapping, urban design representation, and media production. His design work has been exhibited at the Harvard Graduate School of Design and the University of Michigan's Taubman College of Architecture & Urban Planning.
CONTACT US
Do you have general questions about the 11-6 major such as: is this the right major for me? How can I be involved as a faculty advisor? Feel free to reach out to any of the individual faculty or staff members above or contact Sandra M. Elliott (sandrame@mit.edu).