Research

Impact Areas

Cybersecurity

Lead

Una-May O'Reilly

Research Group

Center for Brains, Minds and Machines

Our main goal is developing a computationally based understanding of human intelligence and establishing an engineering practice based on that understanding.

Tomaso Poggio

Leads

Tomaso Poggio

Research Areas

Impact Areas

Lead

Tomaso Poggio

Research Group

Clinical Decision-Making Group

We focus on furthering the application of technology and artificial intelligence in medicine and health-care.

+10

Peter Szolovits

Leads

Peter Szolovits

Research Areas

Impact Areas

Cybersecurity

Lead

Peter Szolovits

+10

Peter Szolovits

Research Group

Computation and Biology

Our lab focuses on designing algorithms to gain biological insights from advances in automated data collection and the subsequent large data sets drawn from them.

Bonnie Berger

Leads

Bonnie Berger

Research Areas

Impact Areas

Lead

Bonnie Berger

Research Group

Computational Biology Group

We seek to understand the mechanistic basis of human disease, using a combination of computational and experimental techniques.

Manolis Kellis

Leads

Manolis Kellis

Research Areas

Impact Areas

Lead

Manolis Kellis

Research Group

Computational Cognitive Science Group

We study the computational basis of human learning and inference.

Joshua Tenenbaum

Leads

Joshua Tenenbaum

Research Areas

Impact Areas

Lead

Joshua Tenenbaum

Research Group

Computational Connectomics Group

Our group’s goal is to create, based on such microscopic connectivity and functional data, new mathematical models explaining how neural tissue computes.

Nir Shavit

Leads

Nir Shavit

Research Areas

Impact Areas

Lead

Nir Shavit

Research Group

Computational Design and Fabrication Group

Our research centers on digital manufacturing, 3D printing and computer graphics, as well as computational photography and displays, and virtual humans and robotics.

Wojciech Matusik

Leads

Wojciech Matusik

Research Areas

Impact Areas

Lead

Wojciech Matusik

Research Group

Computational Genomics Group

We develop new machine learning techniques and algorithms to model the transcriptional regulatory networks that control gene expression programs in living cells.

Dave Gifford

Leads

Dave Gifford

Research Areas

Impact Areas

Lead

Dave Gifford

Research Group

Computational Perception & Cognition

We combine methods from computer science, neuroscience and cognitive science to explain and model how perception and cognition are realized in human and machine.

Aude Oliva

Leads

Aude Oliva

Research Areas

Impact Areas

Lead

Aude Oliva

Research Group

Decentralized Information Group

We are investigating decentralized technologies that affect social change.

Lalana Kagal

Tim Berners-Lee

Leads

Lalana Kagal

Tim Berners-Lee

Research Areas

Impact Areas

Lead

Lalana Kagal

Tim Berners-Lee

Lalana Kagal

Tim Berners-Lee

Research Group

Distributed Robotics Laboratory

We aim to develop the science of autonomy toward a future with robots and AI systems integrated into everyday life, supporting people with cognitive and physical tasks.

+13

Daniela Rus

Leads

Daniela Rus

Research Areas

Impact Areas

Lead

Daniela Rus

+13

Daniela Rus

Research Group

Haystack Group

We are an interdisciplinary group of researchers blending approaches from human-computer interaction, social computing, databases, information management, and databases.

Lea Verou

David Karger

Leads

David Karger

Research Areas

Impact Areas

Lead

David Karger

Lea Verou

David Karger

Community of Research

Human-Computer Interaction Community of Research

The focus of the HCI CoR is inventing new systems and technology that lie at the interface between people and computation, and understanding their design, implementation, and societal impact.

Stefanie Mueller

Leads

Stefanie Mueller

Research Areas

Impact Areas

Entertainment

Lead

Stefanie Mueller

Research Group

Interactive Robotics Group

The Interactive Robotics Group aims to imagine the future of work by designing collaborative robot teammates that enhance human capability.

Julie Shah

Leads

Julie Shah

Research Areas

Impact Areas

Lead

Julie Shah

Research Group

Learning and Intelligent Systems

We conduct interdisciplinary research aimed at discovering the principles underlying the design of artificially intelligent robots.

Leslie Kaelbling

Tomas Lozano-Perez

Leads

Leslie Kaelbling

Tomas Lozano-Perez

Research Areas

Impact Areas

Lead

Leslie Kaelbling

Tomas Lozano-Perez

Leslie Kaelbling

Tomas Lozano-Perez

Research Group

Medical Vision Group

We develop new algorithms for medical image analysis and visualization of medical imagery.

Polina Golland

Leads

Polina Golland

Research Areas

Impact Areas

Lead

Polina Golland

Research Group

MIT App Inventor

MIT App Inventor is an intuitive, visual programming environment that allows everyone – even children – to build fully functional apps for smartphones and tablets.

Hal Abelson

Leads

Hal Abelson

Research Areas

Impact Areas

Lead

Hal Abelson

Research Group

Model-Based Embedded and Robotics Systems Group

We are working to elevate robots from mechanical creations controlled by low-level scripts with a considerable amount of human guidance to truly cognitive robots.

Brian Williams

Leads

Brian Williams

Research Areas

Impact Areas

Lead

Brian Williams

Research Group

Robot Locomotion Group

We research building machines which exploit their natural dynamics to achieve extraordinary agility and efficiency.

Russ Tedrake

Leads

Russ Tedrake

Research Areas

Impact Areas

Lead

Russ Tedrake

Research Group

Robust Robotics Group

We build unmanned vehicles that can fly and drive without maps or GPS.

Nicholas Roy

Leads

Nicholas Roy

Research Areas

Impact Areas

Lead

Nicholas Roy

Research Group

Sensing, Learning and Inference

We develop scalable algorithms for analysis of complex, high-dimensional data.

John Fisher

Leads

John Fisher

Research Areas

Impact Areas

Energy

Lead

John Fisher

Research Group

Sussman Lab

We focus on understanding the problem-solving strategies used by scientists and engineers, with the goals of automating parts of the process and formalizing educational methods.

Gerald Sussman

Leads

Gerald Sussman

Research Areas

Impact Areas

Lead

Gerald Sussman

Community of Research

Systems Community of Research

The Systems CoR is focused on building and investigating large-scale software systems that power modern computers, phones, data centers, and networks, including operating systems, the Internet, wireless networks, databases, and other software infrastructure.

+21

Sam Madden

Leads

Sam Madden

Research Areas

Computer Architecture

Security & Cryptography

Computational Design and Fabrication Group

Impact Areas

Lead

Sam Madden

+21

Sam Madden

36 Project Results

Project

3D-Printed Organic Solar Cells

Using our inkjet printer system, the goal of this project is to produce a light sensor / solar cell that is composed entirely of 3D printed materials.

James Minor

Leads

James Minor

Research Areas

Impact Areas

James Minor

Project

Apprenticeship Scheduling: Learning to Schedule From Human Experts

Robot scheduling via learning from demonstration for tasks in medicine and more

Leads

Research Areas

Impact Areas

Computation Structures Group

Project

Artificial Social Intelligence for Successful Teams (ASIST)

Computational Cognitive Science Group

Model-Based Embedded and Robotics Systems Group

Our goal is to develop a socially intelligent team coacher agent that helps humans communicate, strategize, and work together efficiently.

Leads

Howard Shrobe

Brian Williams

Boris Katz

Zhutian Yang

Research Areas

Computer Architecture

Impact Areas

Weiss Laboratory for Synthetic Biology

Wireless

Project

Artificial tissue homeostasis

In order to be able to design synthetic organs that function autonomously, we will need to engineer artificial tissue homeostasis. To control the size of these artificial tissues, two major mechanisms will have to be engineered.

Leads

Research Areas

Impact Areas

Cognitive AI Community of Research

Project

Clinical Intervention Prediction with Neural Networks

Applied Machine Learning Community of Research

Integrating multi-modal clinical data and using recurrent and convolution neural networks to predict when patients will need important interventions.

Leads

Research Areas

Impact Areas

Project

Computational Multicopter Design

Computer Graphics Group

A system that can help you to design our own drone!

Tao Du

Leads

Tao Du

Research Areas

Impact Areas

Energy

Tao Du

Project

Deterministic Algorithms for Robotic Task and Motion Planning

Our goal is to investigate deterministic algorithms for robotic task and motion planning.

Leads

Research Areas

Impact Areas

Project

Drug Target Identification Via Computational Modeling

Tidor Lab

We use computational models of biological pathways in disease to estimate the range of possible responses to various hypothetical drugs, given patient variability and limited pathway-relevant data.

Leads

Research Areas

Impact Areas

Project

Efficient Communication for Human-Machine Teams

Our goal is to develop collaborative agents (software or robots) that can efficiently communicate with their human teammates. Key threads involve designing algorithms for inferring human behavior and for decision-making under uncertainty.

X. Jessie Yang

Julie Shah

Leads

Julie Shah

Research Areas

Impact Areas

Weiss Laboratory for Synthetic Biology

X. Jessie Yang

Julie Shah

Project

Flexible cellular platforms for reconfigurable biocircuits

Existing methods for cloning and recombination of DNA enable construction of arbitrary sequences. However, the sequential nature of these techniques makes them time-consuming and expensive. Furthermore, while the transformation of an existing plasmid into a host strain can be reliable when a selection marker is used, there are many current limitations: the number of different plasmids that can be co-transformed is limited by the choice of markers and compatible origins of replication; plasmids are less stable than chromosomal DNA and are difficult to maintain indefinitely without mutation; and cistronic interactions cannot be designed since each new nucleotide sequence added is on an unconnected DNA molecule. To overcome these limitations, we are designing reconfigurable chromosomes consisting of both fixed and variable regions. While the fixed region is carefully optimized and tuned ahead of time, the variable region can be modified in the field, at the point-of-use, leading to rapid and on-demand realization of novel biocircuits with many different phenotypes.

Leads

Research Areas

Impact Areas

Project

Helping robots learn using demonstrations

Help robots learn faster by providing demonstrations when they need help

Joseph DelPreto

Leads

Joseph DelPreto

Research Areas

Impact Areas

Joseph DelPreto

Project

Human-Guided Transfer for Robot Learning

Our goal is to develop computational learning models for agents that intelligently use various types of human feedback to help an agent adapt and transfer knowledge to new situations.

Julie Shah

Leads

Julie Shah

Research Areas

Impact Areas

Julie Shah

Project

Human-Robot Collaboration in Shared Workspace

Models and algorithms to predict in real time the next actions of a human working together with a robot

Leads

Research Areas

Impact Areas

Project

Inferring 3D Shape Distributions for Robot Perception and Planning

Robust Robotics Group

Our goal is to develop methods for a mobile robot to reason about volumetric spatial uncertainty of objects in its environment.

Nicholas Roy

Leads

Nicholas Roy

Research Areas

Impact Areas

Nicholas Roy

Project

Learning complex task structures from demonstrations

Our goal is to learn the structure of complex multi-step tasks from demonstration of human experts.

Ankit Shah

Leads

Ankit Shah

Research Areas

Impact Areas

Ankit Shah

Project

Metagenomic Binning Through Low-Density Hashing

Our goal is to develop better metagenomic binning by origin species of fragments of sequenced environmental DNA.

Bonnie Berger

Leads

Bonnie Berger

Research Areas

Impact Areas

Bonnie Berger

Project

Population-level Tumor Growth Inhibition Modeling

Tidor Lab

We develop, parameterize, and validate a model for tumor growth inhibition using in vivo mouse data and study the effects of modeling uncertainty and inter-individual variability on drug candidate efficacy predictions.

Leads

Research Areas

Impact Areas

Project

Printable Hydraulics

Printable Hydraulics allows fluid-actuated robots to be automatically fabricated using 3D printers.

Youbin Kim

Leads

Research Areas

Impact Areas

Energy

Computational Connectomics Group

Youbin Kim

Project

Reconstructing Neural Circuits from Mammalian Brain

Theory of Computation Community of Research

We develop algorithms, systems and software architectures for automating reconstruction of accurate representations of neural tissue structures, such as nanometer-scale neurons' morphology and synaptic connections in the mammalian cortex.

Yaron Meirovitch

Nir Shavit

Leads

Yaron Meirovitch

Nir Shavit

Research Areas

Impact Areas

Yaron Meirovitch

Nir Shavit

Project

Robot Compiler

The Robot Compiler allows non-engineering users to rapidly fabricate customized robots, facilitating the proliferation of robots in everyday life. It thereby marks an important step towards the realization of personal robots that have captured imaginations for decades.

Leads

Joseph DelPreto

Andrew Spielberg

Daniela Rus

Research Areas

Impact Areas

Project

Robotic Planning and Manipulation with Force Information

Our goal is to allow planners to exploit the forces and contacts between objects so as to carry out complex manipulation tasks in the presence of uncertainty.

Leads

Gustavo N. Goretkin

Leslie Kaelbling

Tomas Lozano-Perez

Research Areas

Impact Areas

Model-Based Embedded and Robotics Systems Group

Project

Robots Adapting to Human Intent

Cognitive AI Community of Research

Our goal is to develop algorithms for allowing robots to adapt intelligently to humans when they are working together as a team.

Brian Williams

Leads

Brian Williams

Research Areas

Impact Areas

Brian Williams

Project

Robots that collaborate with humans to form team plans

People, including doctors, nurses, and military personnel, often learn their roles in complex organizations through a training and apprenticeship process.

Julie Shah

Leads

Julie Shah

Research Areas

Impact Areas

Julie Shah

Project

Robots that Quickly Adjust Team Plans to Disturbance

Once a human-machine team has formed a high-quality, flexible plan for working together, the robot must execute its part of the plan and work with its teammate.

Julie Shah

Leads

Julie Shah

Research Areas

Impact Areas

Covering All K-mers Using Joker Characters

Julie Shah

29 People Results

Leandro Agudelo

Research Scientist

Systems Genomics, CompBio, Topological Integrative Biology, Biology

E lagudelo@csail.mit.edu

Systems Genomics, CompBio, Topological Integrative Biology, Biology

PI
Core/Dual

Bonnie Berger

Professor

Computational biology, genomics

E bab@csail.mit.edu

T 253-1827

Lead

Towards Context-Aware Functional Genomics

Metagenomic Binning Through Low-Density Hashing

Computation and Biology

Member

Computation Structures Group

Theory of Computation Community of Research

Applied Machine Learning Community of Research

Computational biology, genomics

Richard Camilli

Research Affiliate

E romeo@mit.edu

Member

Model-Based Embedded and Robotics Systems Group

Lillian Chin

Graduate Student

E ltchin@mit.edu

Lead

Sensorized Soft Electric Hands with Handed Shearing Auxetics

Member

Computational Multicopter Design

Azim Dehghani Amirabad

Postdoctoral Associate

Machine learning, Bioinformatics

E azimd@csail.mit.edu

Machine learning, Bioinformatics

Mustafa Doga Dogan

Graduate Student

E doga@mit.edu

Member

HCI Engineering Group

Tao Du

Graduate Student

CS PhD student

E taodu@csail.mit.edu

Lead

CS PhD student

PI
Core/Dual

Fredo Durand

Professor

Vision, graphics, computational photography

E fredo@csail.mit.edu

T 253-7223

Lead

Computer Graphics Group

Computational Understanding of Visualizations and Graphic Designs

Vision Group

Member

Computational Bounce Flash for Indoor Portraits

Halide

Visual Computing Community of Research

Vision, graphics, computational photography

Barış Ekim

Graduate Student

E ekim@csail.mit.edu

Michael Foshey

Mechanical Engineer/Project Manager

Additive Manufacturing, Robotics, Digital Fabrication

E mfoshey@mit.edu

Additive Manufacturing, Robotics, Digital Fabrication

PI
Core/Dual

John Guttag

Professor

Machine learning, medicine, data-driven inference

E guttag@csail.mit.edu

T 253-6022

Lead

Data-Driven Inference Group

Hidden Influencers, Risk and Causes of Infection

Predicting Adverse Events Across Changing Electronic Health Record Systems

Machine Learning for Insights in Basketball Strategy

Detecting Voice Misuse to Diagnose Disorders

Member

Systems Community of Research

Machine learning, medicine, data-driven inference

Ramin Hasani

Postdoctoral Associate

Machine learning Scientist

E rhasani@csail.mit.edu

Machine learning Scientist

Jamey Hicks

Research Affiliate

E jamey.hicks@accelerated.tech

Member

Computation Structures Group

PI
Core/Dual

Daniel Jackson

Professor

Software design, programming, systems

E dnj@csail.mit.edu

T 258-8471

Lead

Rethinking Software Design

Software Design Group

Gitless: a simple version control system built on top of Git

Déjà Vu: Constructing Apps from Concepts

Security by Design for Cyberphysical Systems

Poirot: Secure Protocol Implementation by Design

An Interlock for Self Driving Cars

Alloy

Wildcard

Member

Espalier

Human-Computer Interaction Community of Research

Systems Community of Research

Wildcard

Software design, programming, systems

PI
Core/Dual

Leslie Kaelbling

Professor

Robotics, machine learning, motion planning

E lpk@csail.mit.edu

T 258-9695

Lead

Learning and Optimization

Machine Learning

Robotic Planning and Manipulation with Force Information

Reliable Robotic Construction of Multi-object Arrangements

Learning and Planning with Compressed Linear Expectation Models

Active Learning of Models for Planning

Task and Motion Planning for Autonomous Robots

Member

Computational Genomics Group

Robotics, machine learning, motion planning

Konstantin Krismer

Graduate Student

E krismer@mit.edu

Member

Henry Lieberman

Research Scientist

Henry Lieberman is a Research Scientist at MIT CSAIL, in AI and HCI.

E lieber@MEDIA.MIT.EDU

Henry Lieberman is a Research Scientist at MIT CSAIL, in AI and HCI.

PI
Core/Dual

Tomas Lozano-Perez

Professor

Robotics, artificial intelligence

E tlp@csail.mit.edu

T 253-7889

Lead

Learning and Optimization

Robotic Planning and Manipulation with Force Information

Reliable Robotic Construction of Multi-object Arrangements

Learning and Planning with Compressed Linear Expectation Models

Active Learning of Models for Planning

Task and Motion Planning for Autonomous Robots

Member

Computational Design and Fabrication Group

Robotics, artificial intelligence

PI
Core/Dual

Wojciech Matusik

Professor

Graphics, vision, fabrication, robotics, hci

E wojciech@csail.mit.edu

T 324-8432

Lead

Computer Graphics Group

Member

Computational Multicopter Design

Simit: A Language for Computing on Sparse Systems

InstantCAD: Interactive Design Exploration/Optimization for CAD Models

Visual Computing Community of Research

Graphics, vision, fabrication, robotics, hci

Radhen Patel

Postdoctoral Associate

Robotics | Haptics | Vision | Machine Learning

E radhen@csail.mit.edu

Robotics | Haptics | Vision | Machine Learning

PI
Core/Dual

Daniela Rus

Director

CSAIL director, robotics, AI, data science, privacy

E rus@csail.mit.edu

T 258-7567

RM 32/ 32-368/ 374

Lead

Social Network Extraction from GPS Datasets with Coresets

Safety Standards for Autonomous Vehicles

Soft Contact Modeling

Practical Secure Computation

Self-Driving Vehicles

Robust Learning for Autonomous Vehicles

Brain-Controlled Robots

Planning in Congestion for Autonomous Vehicles

Socially-Compliant Behavior for Autonomous Driving

Coresets for Machine Learning Algorithms

M-Blocks Modular Robotics

Robot Compiler

Distributed Robot Garden

Route and Motion Planning for Mobility-on-Demand with Rules of the Road

Member

Social Network Extraction from GPS Datasets with Coresets

Task-Driven Co-Optimization Of Articulated Robots

Wearable Blind Navigation

Drones that Drive

Better Models for Ride-Sharing

SoFi - The Soft Robotic Fish

Controlling drones and other robots with gestures

Using Muscle Signals to Lift Objects with Robots

Helping robots learn using demonstrations

CSAIL director, robotics, AI, data science, privacy

PI
Core/Dual

Julie Shah

Associate Professor

Robotics, machine learning, artificial intelligence

E julie_a_shah@csail.mit.edu

T 324-4879

Lead

Robots that collaborate with humans to form team plans

Robots that Quickly Adjust Team Plans to Disturbance

Human-Guided Transfer for Robot Learning

Efficient Communication for Human-Machine Teams

Member

Apprenticeship Scheduling: Learning to Schedule From Human Experts