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13 Group Results

Research Center

Center for Deployable Machine Learning (CDML)

The MIT Center for Deployable Machine Learning (CDML) works towards creating AI systems that are robust, reliable and safe for real-world deployment.

+5

Aleksander Madry

Leads

Aleksander Madry

Research Areas

Algorithms & Theory

Graphics & Vision

Human-Computer Interaction

Programming Languages & Software Engineering

Security & Cryptography

Impact Areas

Lead

Aleksander Madry

Aleksander Madry

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

Algorithms & Theory

Computational Biology

Impact Areas

Lead

Bonnie Berger

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

Computational Biology

Impact Areas

Lead

Manolis Kellis

Manolis Kellis

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

Algorithms & Theory

Computational Biology

Impact Areas

Lead

Nir Shavit

Nir Shavit

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

Computational Biology

Impact Areas

Lead

Aude Oliva

Aude Oliva

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

Daniela Rus

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

Julie Shah

Research Group

Learning and Intelligent Systems

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

+5

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

Marine Robotics Group

Our projects are centered around the problems of navigation and mapping for autonomous mobile robots operating in underwater and terrestrial environments.

John Leonard

Leads

John Leonard

Research Areas

Impact Areas

Lead

John Leonard

John Leonard

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

Russ Tedrake

Research Group

Robust Robotics Group

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

+2

Nicholas Roy

Leads

Nicholas Roy

Research Areas

Impact Areas

Lead

Nicholas Roy

Nicholas Roy

Research Group

Sensing, Learning and Inference

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

+6

John Fisher

Leads

John Fisher

Research Areas

Graphics & Vision

Impact Areas

Internet of Things

Lead

John Fisher

John Fisher

Community of Research

Theory of Computation Community of Research

The goal of the Theory of Computation CoR is to study the fundamental strengths and limits of computation as well as how these interact with mathematics, computer science, and other disciplines.

+20

Costis Daskalakis

Leads

Costis Daskalakis

Research Areas

Algorithms & Theory

Computational Biology

Programming Languages & Software Engineering

Security & Cryptography

Impact Areas

Lead

Costis Daskalakis

Costis Daskalakis

22 Project Results

Project

Active Learning of Models for Planning

Learning and Intelligent Systems

Machine Learning

We aim to develop a systematic framework for robots to build models of the world and to use these to make effective and safe choices of actions to take in complex scenarios.

Leslie Kaelbling

Tomas Lozano-Perez

Leads

Leslie Kaelbling

Tomas Lozano-Perez

Research Areas

Algorithms & Theory

Human-Computer Interaction

Impact Areas

Leslie Kaelbling

Tomas Lozano-Perez

Project

An Interlock for Self Driving Cars

Software Design Group

Computer-Aided Programming

Vertical AI Community of Research

Human-Computer Interaction Community of Research

Self-driving cars are likely to be safer, on average, than human-driven cars. But they may fail in new and catastrophic ways that a human driver could prevent. This project is designing a new architecture for a highly dependable self-driving car.

Daniel Jackson

Armando Solar-Lezama

Leads

Daniel Jackson

Armando Solar-Lezama

Research Areas

Human-Computer Interaction

Programming Languages & Software Engineering

Systems & Networking

Impact Areas

Daniel Jackson

Armando Solar-Lezama

Project

Artificial Social Intelligence for Successful Teams (ASIST)

Computation Structures Group

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

Human-Computer Interaction

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

Graphics & Vision

Impact Areas

Tao Du

Project

Deterministic Algorithms for Robotic Task and Motion Planning

Learning and Intelligent Systems

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

Leads

Research Areas

Algorithms & Theory

Impact Areas

Project

Driver-Friendly Bilateral Control for Suppressing Traffic Instabilities

We are studying how best to implement bilateral control and make it acceptable to drivers

Berthold Horn

Leads

Berthold Horn

Research Areas

Graphics & Vision

Systems & Networking

Impact Areas

Berthold Horn

Project

Drones that Drive

Distributed Robotics Laboratory

Multi-robot path planning for robot swarms that can both fly and drive

Leads

Research Areas

Algorithms & Theory

Impact Areas

Project

Geordi: A Driver's Assistant for Risk-bounded Maneuvering

Model-Based Embedded and Robotics Systems Group

Cognitive AI Community of Research

Our goal is to create an online risk-aware planner for vehicle maneuvers that can make driving safer and less stressful through a “parallel” autonomous system that assists the driver by watching for risky situations, and by helping the driver take proactive, compensating actions before they become crises.

Brian Williams

Leads

Brian Williams

Research Areas

Impact Areas

Brian Williams

Project

Planning in Congestion for Autonomous Vehicles

Distributed Robotics Laboratory

Our goal is to develop an autonomous vehicle control strategy that adapts on-line to varying levels of congestion in the environment.

Leads

Alyssa Pierson

Wilko Schwarting

Sertac Karaman

Daniela Rus

Research Areas

Impact Areas

Project

Printable Hydraulics

Distributed Robotics Laboratory

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

Youbin Kim

Leads

Research Areas

Impact Areas

Youbin Kim

Project

Robot Compiler

Distributed Robotics Laboratory

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

Algorithms & Theory

Human-Computer Interaction

Impact Areas

Internet of Things

Project

Robotic Planning and Manipulation with Force Information

Learning and Intelligent Systems

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

Project

Robust Intelligent Robots

Learning and Intelligent Systems

How can a mobile-manipulation robot operate robustly and flexibly in complicated uncertain environments, such as households and disaster zones.

Leslie Kaelbling

Tomas Lozano-Perez

Leads

Leslie Kaelbling

Tomas Lozano-Perez

Research Areas

Impact Areas

Leslie Kaelbling

Tomas Lozano-Perez

Project

Robust Learning for Autonomous Vehicles

Distributed Robotics Laboratory

Our goal is to create a theoretical framework and effective machine learning algorithms for robust, reliable control of autonomous vehicles. Key threads include developing metrics of confidence; and designing deep learning algorithms for parallel autonomy.

Daniela Rus

Alexander Amini

Leads

Daniela Rus

Alexander Amini

Research Areas

Impact Areas

Daniela Rus

Alexander Amini

Project

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

Distributed Robotics Laboratory

Ensuring correct behavior of autonomous vehicles with respect to rules of the road

Sertac Karaman

Daniela Rus

Leads

Sertac Karaman

Daniela Rus

Research Areas

Impact Areas

Sertac Karaman

Daniela Rus

Project

Safety Standards for Autonomous Vehicles

Distributed Robotics Laboratory

In this project, we aim to develop a framework that can ensure and certify the safety of an autonomous vehicle. By leveraging research from the area of formal verification, this framework aims to assess the safety, i.e., free of collisions, of a broad class of autonomous car controllers/planners for a given traffic model.

Leads

Lucas Liebenwein

Wilko Schwarting

Daniela Rus

Research Areas

Algorithms & Theory

Impact Areas

Project

Self-Driving Vehicles

Distributed Robotics Laboratory

We want to help to make driving more comfortable, environmentally friendly and above all safer!

+10

Leads

Russ Tedrake

John Leonard

Daniela Rus

Sertac Karaman

Research Areas

Programming Languages & Software Engineering

Impact Areas

Project

Socially-Compliant Behavior for Autonomous Driving

Distributed Robotics Laboratory

Bringing human-like decision making to autonomous driving.

Leads

Wilko Schwarting

Alyssa Pierson

Sertac Karaman

Javier Alonso-Mora

Daniela Rus

Research Areas

Impact Areas

Project

SoFi - The Soft Robotic Fish

Distributed Robotics Laboratory

Exploration of underwater life with an acoustically controlled soft robotic fish

Joseph DelPreto

Leads

Joseph DelPreto

Research Areas

Human-Computer Interaction

Impact Areas

Joseph DelPreto

Project

Supervising Robots with Muscle and Brain Signals

Distributed Robotics Laboratory

What if we could control robots more intuitively, using just hand gestures and brainwaves?

Joseph DelPreto

Leads

Joseph DelPreto

Research Areas

Human-Computer Interaction

Impact Areas

Joseph DelPreto

Project

Task and Motion Planning for Autonomous Robots

Learning and Intelligent Systems

Our goal is to design algorithms that enable robots to operate in human environments by simultaneously reasoning about high-level task actions as well as low-level motions.

Leads

Caelan Garrett

Leslie Kaelbling

Tomas Lozano-Perez

Research Areas

Impact Areas

Project

Wearable Blind Navigation

Distributed Robotics Laboratory

We enable independent navigation for visually impaired users through a wearable feedback system using time-of-light sensors or depth cameras.

Leads

Research Areas

Graphics & Vision

Human-Computer Interaction

Impact Areas

23 People Results

Alexander Amini

Graduate Student

PhD Candidate. Deep Learning; Robotics

E Amini@mit.edu

RM

Lead

Robust Learning for Autonomous Vehicles

Member

Self-Driving Vehicles

Distributed Robotics Laboratory

PhD Candidate. Deep Learning; Robotics

Brandon Araki

Graduate Student

E araki@csail.mit.edu

Noam Buckman

Graduate Student

PhD Candidate. Autonomous vehicles. Multi-robot systems.

E nbuckman@mit.edu

RM

Member

Distributed Robotics Laboratory

Self-Driving Vehicles

PhD Candidate. Autonomous vehicles. Multi-robot systems.

Lillian Chin

Graduate Student

E ltchin@mit.edu

RM

Lead

Sensorized Soft Electric Hands with Handed Shearing Auxetics

Member

Distributed Robotics Laboratory

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

RM

Member

HCI Engineering Group

Barış Ekim

Graduate Student

E ekim@csail.mit.edu

Michael Foshey

Mechanical Engineer/Project Manager

Additive Manufacturing, Robotics, Digital Fabrication

E mfoshey@mit.edu

RM

Additive Manufacturing, Robotics, Digital Fabrication

Igor Gilitschenski

Research Scientist

E igilitschenski@mit.edu

Member

Distributed Robotics Laboratory

Self-Driving Vehicles

PI
Core/Dual

John Guttag

Professor

Machine learning, medicine, data-driven inference

E guttag@csail.mit.edu

T 253-6022

RM

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

PI
Core/Dual

Berthold Horn

Professor

Vision, computational imaging

E bkph@csail.mit.edu

T 253-5863

RM

Lead

Driver-Friendly Bilateral Control for Suppressing Traffic Instabilities

Member

Visual Computing Community of Research

Vision, computational imaging

Konstantin Krismer

Graduate Student

E krismer@mit.edu

RM

Member

Computational Genomics Group

PI
Core/Dual

John Leonard

Professor

Robotics, navigation/mapping, self-driving cars

E jleonard@csail.mit.edu

T 253-5305

RM

Lead

Marine Robotics Group

Self-Driving Vehicles

Member

Embodied Intelligence Community of Research

Robotics, navigation/mapping, self-driving cars

Lucas Liebenwein

Graduate Student

Student and Researcher | Robotics, AI | Advanced Autonomy

E lucasl@mit.edu

RM 32-376C

Lead

Safety Standards for Autonomous Vehicles

Member

Self-Driving Vehicles

Distributed Robotics Laboratory

Coresets for Machine Learning Algorithms

Student and Researcher | Robotics, AI | Advanced Autonomy

Alyssa Pierson

Research Scientist

E apierson@csail.mit.edu

RM

Lead

Planning in Congestion for Autonomous Vehicles

Socially-Compliant Behavior for Autonomous Driving

Member

Distributed Robotics Laboratory

Self-Driving Vehicles

PI
Core/Dual

Nicholas Roy

Professor

Robotics, autonomy, artificial intelligence, motion planning

E nickroy@csail.mit.edu

T 253-2517

RM

Lead

Robust Robotics Group

Inferring 3D Shape Distributions for Robot Perception and Planning

Member

Enabling Semantic Understanding for Autonomous Marine Robots

Embodied Intelligence Community of Research

Robotics, autonomy, artificial intelligence, motion planning

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

Distributed Robotics Laboratory

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

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

Embodied Intelligence Community of Research

Helping robots learn using demonstrations

CSAIL director, robotics, AI, data science, privacy

Wilko Schwarting

Graduate Student

E wilkos@mit.edu

Lead

Safety Standards for Autonomous Vehicles

Planning in Congestion for Autonomous Vehicles

Socially-Compliant Behavior for Autonomous Driving

Member

Self-Driving Vehicles

Distributed Robotics Laboratory

PI
Core/Dual

Russ Tedrake

Professor

Robotics, machine learning, motion planning and control

E russt@csail.mit.edu

T 253-1778

RM 32-380B

Lead

Robot Locomotion Group

Localizing External Contact Using Proprioceptive Sensors

Tactile and Physical Perception

Soft Contact Modeling

Self-Driving Vehicles

Member

Tactile and Physical Perception

Task-Driven Co-Optimization Of Articulated Robots

Center for Deployable Machine Learning (CDML)

Embodied Intelligence Community of Research

Robotics, machine learning, motion planning and control

Joshua Tenenbaum

Professor

Computational cognitive science, machine learning

E jbt@csail.mit.edu

T 452-2010

RM 46-4015

Lead

Computational Cognitive Science Group

Member

Center for Brains, Minds and Machines

Single-Image 3D Interpreter Network

3D Generative Adversarial Networks

Embodied Intelligence Community of Research

Cognitive AI Community of Research

Visual Computing Community of Research

Computational cognitive science, machine learning

Neil Thompson

Research Scientist

I'm an innovation scholar studying computer science and economics.

E neil_t@mit.edu

RM

Lead

Supertech Research Group

Determining Wikipedia's Influence on Science

I'm an innovation scholar studying computer science and economics.

PI
Core/Dual

Brian Williams

Professor

Robotics, autonomy, artificial intelligence, machine learning

E williams@csail.mit.edu

T 253-2739

RM

Lead

Model-Based Embedded and Robotics Systems Group

Geordi: A Driver's Assistant for Risk-bounded Maneuvering

Robots Adapting to Human Intent

Risk-aware Network Resource Allocation

Uhura: Personal Assistant that Manages Risk

Artificial Social Intelligence for Successful Teams (ASIST)

Member

Cognitive AI Community of Research

Robotics, autonomy, artificial intelligence, machine learning

18 News Results

A neural network learns when it should not be trusted

AI & ML Robotics Transportation

November 24 '20

A neural network learns when it should not be trusted

A faster way to estimate uncertainty in AI-assisted decision-making could lead to safer outcomes.

A neural network learns when it should not be trusted

Autonomous boats

Algorithms & Theory Robotics Transportation

October 26 '20

Autonomous boats could be your next ride

Five years in the making, MIT’s autonomous floating vessels get a size upgrade and learn a new way to communicate aboard the waters.

Autonomous boats could be your next ride

AI & ML Robotics Cybersecurity Internet of Things Transportation

January 13 '20

WaPo op-ed: how to regulate AI properly

In a Washington Post op-ed, CSAIL's R. David Edelman outlines how to regulate AI properly

WaPo op-ed: how to regulate AI properly

m-blocks

AI & ML Robotics Manufacturing Transportation

October 30 '19

Self-transforming robot blocks jump, spin, flip, and identify each other

Developed at MIT’s Computer Science and Artificial Intelligence Laboratory, a team of robots can self-assemble to form different structures with applications in inspection, disaster response, and manufacturing

Self-transforming robot blocks jump, spin, flip, and identify each other

Pool

Algorithms & Theory AI & ML Robotics Transportation

August 29 '19

MIT’s fleet of autonomous boats can now shapeshift

New capabilities allow “roboats” to change configurations to form pop-up bridges, stages, and other structures.

MIT’s fleet of autonomous boats can now shapeshift

Roboat2

Algorithms & Theory Robotics Transportation

June 27 '19

Autonomous boats can target and latch onto each other

Fleet of “roboats” could collect garbage or self-assemble into floating structures in Amsterdam’s many canals.

Autonomous boats can target and latch onto each other

Barbara Liskov 2

Algorithms & Theory AI & ML Computational Biology Computer Architecture Graphics & Vision Human-Computer Interaction Programming Languages & Software Engineering Robotics Security & Cryptography Systems & Networking Cybersecurity Education Energy Entertainment Health Care Manufacturing Transportation Wireless

June 27 '19

CSAIL hosts first-ever TEDxMIT

Speakers — all women — discuss everything from gravitational waves to robot nurses

CSAIL hosts first-ever TEDxMIT

recycle

AI & ML Robotics Energy Health Care

April 18 '19

Robots that can sort recycling

CSAIL’s "RoCycle" system uses in-hand sensors to detect if an object is paper, metal or plastic.

Robots that can sort recycling

Underwater_stock1

Algorithms & Theory AI & ML Robotics Transportation

February 01 '19

Engineers program marine robots to take calculated risks

Algorithm could help autonomous underwater vehicles explore risky but scientifically-rewarding environments.

Engineers program marine robots to take calculated risks

AI blind spot

Algorithms & Theory AI & ML Robotics Transportation

January 25 '19

Identifying artificial intelligence “blind spots”

Model identifies instances when autonomous systems have learned from examples that may cause dangerous errors in the real world.

Identifying artificial intelligence “blind spots”

Drone (image by Melanie Gonick, MIT)

AI & ML Robotics Health Care Transportation

November 01 '18

Fleets of drones could aid searches for lost hikers

System allows drones to cooperatively explore terrain under thick forest canopies where GPS signals are unreliable.

Fleets of drones could aid searches for lost hikers

model helps robots naviagte like humans 1

Algorithms & Theory AI & ML Robotics Transportation

October 04 '18

Model helps robots navigate more like humans do

In simulations, robots move through new environments by exploring, observing, and drawing from learned experiences.

Model helps robots navigate more like humans do

driverless cars 2

Algorithms & Theory AI & ML Robotics Transportation

May 23 '18

Making driverless cars change lanes more like human drivers do

Algorithm computes “buffer zones” around autonomous vehicles and reassess them on the fly.

Making driverless cars change lanes more like human drivers do

self driving

AI & ML Graphics & Vision Robotics Transportation

May 07 '18

Self-driving cars for country roads

For all the progress made in self-driving technologies, there still aren’t many places where they can actually drive. Companies like Google only test their fleets in major cities where they’ve spent countless hours meticulously labeling the exact 3-D positions of lanes, curbs, off-ramps, and stop signs.

Self-driving cars for country roads

Robotic fish

AI & ML Robotics Manufacturing Transportation

March 21 '18

Soft robotic fish swims alongside real ones in coral reefs

Made of silicone rubber, CSAIL’s “SoFi” could enable a closer study of aquatic life.

Soft robotic fish swims alongside real ones in coral reefs

drone1

Algorithms & Theory Robotics Energy Manufacturing Transportation

February 12 '18

Programming drones to fly in the face of uncertainty

CSAIL's NanoMap system enables drones to avoid obstacles while flying at 20 miles per hour, by more deeply integrating sensing and control.

Programming drones to fly in the face of uncertainty

ACM Fellows

Algorithms & Theory Robotics Security & Cryptography Cybersecurity Internet of Things Manufacturing

December 11 '17

Four from MIT named 2017 Association for Computer Machinery Fellows

Today four MIT faculty were named among the Association for Computer Machinery's 2017 Fellows for making “landmark contributions to computing.”

Four from MIT named 2017 Association for Computer Machinery Fellows

System directs camera-equipped drones to maintain framing of an aerial shot.

Algorithms & Theory AI & ML Graphics & Vision Robotics Entertainment Transportation

May 17 '17

Cinematography on the fly

In recent years, a host of Hollywood blockbusters — including “The Fast and the Furious 7,” “Jurassic World,” and “The Wolf of Wall Street” — have included aerial tracking shots provided by drone helicopters outfitted with cameras. Those shots required separate operators for the drones and the cameras, and careful planning to avoid collisions. But a team of researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and ETH Zurich hope to make drone cinematography more accessible, simple, and reliable.

Cinematography on the fly