The MIT Election Data and Science Lab (MEDSL) supports advances in election science by collecting, analyzing, and sharing core data and findings. The lab also aims to build relationships with election officials and others to help apply new scientific research to the practice of democracy in the United States.
By applying scientific principles to how elections are studied and administered, MEDSL aims to improve the democratic experience for all U.S. voters.
The MIT Election Lab is a founding partner in the Stanford-MIT Healthy Elections Project, which was developed to ensure that the 2020 election can proceed with integrity, safety, and equal access. The project aims to do this by bringing together academics, civic organizations, election administrators, and election administration experts to assess and promote best practices.

The MIT Governance Lab (MIT GOV/LAB) is an applied research group and ideas incubator that aims to improve democracy and governance by changing practice around corruption, government accountability, and citizen voice. Our model combines behavioral political science, experimental social science, design thinking, and evaluation to iterate on governance solutions that support people’s ability to hold the government to account. 
We partner with in-country practitioners, including government, civil society, and social enterprises, at every stage of the research and learning process, from theory building to theory testing, to critical reflections and adaptations in real time, with the goal of contributing to a solid evidence base to strengthen the overall field of practice for participatory governance. 
To learn more about our work, check out our latest updates, tools, guides, and other resources, as well as published research, or be in touch mitgovlab@mit.edu.

The mission of the MIT-Haiti Initiative is to promote active learning in Kreyòl so that Haitians can have universal access to quality education in the language that most of them speak at home. 
Platfòm MIT-Ayiti, launched in 2019, offers a wealth of freely accessible educational resources in Kreyòl, including downloadable lesson plans and picture books categorized by topic, alongside official curricula from Haiti’s Ministry of National Education. The target audience for these resources includes students at all levels from pre-kindergarten through high school, and we offer materials in all disciplines. We also host and invite contributions from all educators who are willing to submit their own materials in Kreyòl. We work with these contributions, in konbit (collaborative) mode, to improve these submissions before publication. Men anpil, chay pa lou! (That is, many hands make light work!)
The Initiative’s original website, launched in 2010, includes software tools for math, physics, genetics, and biochemistry education, as well as a preliminary (work-in-progress) glossary of Kreyòl equivalents for English words commonly used in the STEM disciplines.

At the MIT Haystack Observatory, researchers use several basic science concepts every day. Electromagnetic waves, optics, and molecular chemistry are just a few of the core topics that can be incorporated into the high school science curriculum by exploring the atmosphere and the universe with lessons focused around the research specialties at Haystack.
The original material presented here was developed by teachers, with the assistance of the staff at Haystack. All lesson plans have been successfully used in high school classrooms. These lessons have been prepared with specific attention to the goals and objectives of current science curricula. The object is to create lessons that will enhance your class, not require you to add substantial material.
The development of these educational materials at the Haystack Observatory was funded by the National Science Foundation under the Research Experiences for Teachers (RET) program.

The MIT Little Devices Lab collaborates with healthcare professionals in developing countries to create affordable health and medical technologies. A large number of these healthcare professionals are nurses, and have been described as “stealth innovators,” “NurseMakers,” and “MacGyver Nurses.” (Rice, S. “Nurses Devise Their Own Innovations.” Modern Healthcare, 17 Oct., 2015).
The Little Devices Lab helps support these inventors by sending them kits with the modular parts and materials to invent and build their own customized, cost-effective medical devices. They can then solve challenges specific to their patients and work environments, for a range of applications from diagnostics to microfluidics to drug delivery.
Similar to how breadboards enabled people to more easily build their own electronics, one of the lab’s projects involved creating a biochemical breadboard with plug-and-play sets of blocks for building paper analytical devices, which healthcare workers can use to make diagnostic tests that meet their needs.
On the Little Devices Lab’s site, users will find more details about the lab’s ongoing projects and research, video presentations about its work, and several of its members’ publications.

The MIT Prison Education Initiative (PEI) hosted this non-credit January IAP course to give the MIT community an opportunity to engage in discussions about mass incarceration and criminal justice reform. The Independent Activities Period (IAP) is a special four week term at MIT that runs from the first week of January until the end of the month.

The MIT Project on Embodied Education aims to close the gap between the growing body of research on movement and the learning process and the pedagogical strategies that educators use, finding ways to integrate physical activity and academic instruction at all levels—for example, teaching elementary school math through yoga, middle school physics through martial arts, high school science through swimming, and college history through dance.

Sloan’s Teaching Resources Library provides open access to case studies and management simulations for management educators and students worldwide. This collection of teaching materials and games focuses on areas in which Sloan’s innovative research and teaching are on the cutting edge, including action learning, entrepreneurship, leadership and ethics, operations management, strategy, sustainability, and system dynamics.
Formerly known as LearningEdge, and MIT Sloan Teaching Innovation Resources (MSTIR).
Online Publication

6.867 is an introductory course on machine learning which gives an overview of many concepts, techniques, and algorithms in machine learning, beginning with topics such as classification and linear regression and ending up with more recent topics such as boosting, support vector machines, hidden Markov models, and Bayesian networks. The course will give the student the basic ideas and intuition behind modern machine learning methods as well as a bit more formal understanding of how, why, and when they work. The underlying theme in the course is statistical inference as it provides the foundation for most of the methods covered.

This course introduces students to machine learning in healthcare, including the nature of clinical data and the use of machine learning for risk stratification, disease progression modeling, precision medicine, diagnosis, subtype discovery, and improving clinical workflows.

This course covers fundamental and advanced techniques in this field at the intersection of computer vision, computer graphics, and geometric deep learning. It will lay the foundations of how cameras see the world, how we can represent 3D scenes for artificial intelligence, how we can learn to reconstruct these representations from only a single image, how we can guarantee certain kinds of generalizations, and how we can train these models in a self-supervised way.

This course is an introduction to the process of generating a symbolic description of the environment from an image. It covers the physics of image formation, image analysis, binary image processing, and filtering. Machine vision has applications in robotics and the intelligent interaction of machines with their environment. Students taking the graduate version complete additional assignments.

Machine Vision provides an intensive introduction to the process of generating a symbolic description of an environment from an image. Lectures describe the physics of image formation, motion vision, and recovering shapes from shading. Binary image processing and filtering are presented as preprocessing steps. Further topics include photogrammetry, object representation alignment, analog VLSI and computational vision. Applications to robotics and intelligent machine interaction are discussed.

15.015 Macro and International Economics focuses on the policy and economic environment of firms. This subject divided in three parts. The first part of the course is a study of the closed economy and how monetary and fiscal policy interacts with employment, GNP, inflation, and interest rates. Next, the course provides an examination of national economic strategies for development and growth and recent financial and currency crises in emerging markets. Finally, the course addresses the problems faced by transition economies and the role of institutions both as the engine of growth, and as the constraints for policy.

Introduction to the theories of economic growth. Topics will include basic facts of economic growth and long-run economic development; brief overview of optimal control theory and dynamic programming; basic neoclassical growth model under a variety of market structures; human capital and economic growth; endogenous growth models; models with endogenous technology; models of directed technical change; competition, market structure and growth; financial and economic development; international trade and economic growth; institutions and economic development. This is a half-term subject. The class size is limited.

This is the second course in the four-quarter graduate sequence in macroeconomics. Its purpose is to introduce the basic models macroeconomists use to study fluctuations. Topics include the basic model or the consumption/saving choice, the RBC model or the labor/leisure choice, non-trivial investment decisions, two-good analysis, money, price setting, the “new Keynesian” model, monetary policy, and fiscal policy.

This course covers issues in the theory of consumption, investment and asset prices. We lay out the basic models first, and then examine the empirical facts that motivate extensions to these models.

This course presents a challenging multi-dimensional perspective on the causes of human disease and mortality. The course focuses on analyses of major causes of mortality in the US since 1900: cancer, cardiovascular and cerebrovascular diseases, diabetes, and infectious diseases. Students create analytical models to derive estimates for historically variant population risk factors and physiological rate parameters, and conduct analyses of familial data to separately estimate inherited and environmental risks. The course evaluates the basic population genetics of dominant, recessive and non-deleterious inherited risk factors.

The topics cover physical phenomena in polymeric liquids undergoing deformation and flow; kinematics and material functions for complex fluids; techniques of viscometry, rheometry; and linear viscoelastic measurements for polymeric fluids. Also, generalized Newtonian fluids; continuum mechnanics, frame invariance, and convected derivatives for finite strain viscoelasticity; differential and integral constitutive equations for viscoelastic fluids; analytical solutions to isothermal and non-isothermal flow problems; the roles of non-Newtonian viscosity, linear viscoelasticity, normal stresses, elastic recoil, stress relaxation in processing flows; and introduction to molecular theories for dynamics of polymeric fluids. (Extensive class project and presentation required instead of a final exam).

This course explores the origins of magic, science, and religion as forms of belief within and across cultures. It addresses the place of rationality and belief in competing sociocultural theories, with a focus on analyzing modern perspectives. It also examines how cases of overlap between magic, science, and religion raise new questions about modernity and human nature.