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8 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

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.

+12

Daniela Rus

Leads

Daniela Rus

Research Areas

Impact Areas

Lead

Daniela Rus

Daniela Rus

Research Group

Geometric Data Processing Group

Our group studies geometric problems in computer graphics, computer vision, machine learning, optimization, and other disciplines.

+6

Justin Solomon

Leads

Justin Solomon

Research Areas

Algorithms & Theory

Graphics & Vision

Impact Areas

Lead

Justin Solomon

Justin Solomon

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

Medical Vision Group

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

+9

Polina Golland

Leads

Polina Golland

Research Areas

Computational Biology

Graphics & Vision

Impact Areas

Lead

Polina Golland

Polina Golland

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

Vertical AI Community of Research

This CoR takes a unified approach to cover the full range of research areas required for success in artificial intelligence, including hardware, foundations, software systems, and applications.

+7

Martin Rinard

Leads

Martin Rinard

Research Areas

Algorithms & Theory

Graphics & Vision

Programming Languages & Software Engineering

Security & Cryptography

Systems & Networking

Impact Areas

Internet of Things

Lead

Martin Rinard

Martin Rinard

Research Group

Vision Group

Our researchers create state-of-the-art systems to better recognize objects, people, scenes, behaviors and more, with applications in health-care, gaming, tagging systems and more.

Leads

Ted Adelson

Fredo Durand

John Fisher

William Freeman

Polina Golland

Berthold Horn

Aude Oliva

Antonio Torralba

Eric Grimson

Research Areas

Graphics & Vision

Impact Areas

Lead

Ted Adelson

Fredo Durand

John Fisher

William Freeman

Polina Golland

Berthold Horn

Aude Oliva

Antonio Torralba

Eric Grimson

21 Project Results

Project

A Counterfactual Simulation Model of Causal Judgment

Computational Cognitive Science Group

Cognitive AI Community of Research

We develop a computational model that explains how people make causal judgments in physical scenes by mentally simulating counterfactual outcomes and comparing those to what actually happened.

Leads

Research Areas

Graphics & Vision

Impact Areas

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

Apprenticeship Scheduling: Learning to Schedule From Human Experts

Interactive Robotics Group

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

Leads

Research Areas

Impact Areas

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

Cardiac MRI analysis

Medical Vision Group

We develop image analysis algorithms for whole-heart cardiac MRI in patients with severe congenital heart disease.

Polina Golland

Leads

Polina Golland

Research Areas

Graphics & Vision

Impact Areas

Polina Golland

Project

Clinical Neuroimaging

Medical Vision Group

We develop novel algorithms for neuroimage segmentation, registration, and joint modeling of brain structure with clinical and genetic data.

+2

Polina Golland

Leads

Polina Golland

Research Areas

Graphics & Vision

Impact Areas

Polina Golland

Project

Crowdsourcing in Graphics and Vision

Computational Design and Fabrication Group

Our goal is to develop new applications and algorithms that leverage the skills of distributed crowdworkers, notably for image and video processing applications.

Alexandre Kaspar

Leads

Alexandre Kaspar

Research Areas

Graphics & Vision

Human-Computer Interaction

Impact Areas

Alexandre Kaspar

Project

Geometry and topology for scientific computing and shape analysis

Geometric Data Processing Group

Computer Graphics Group

Developing state-of-the-art tools that process 3D surfaces and volumes

+1

Justin Solomon

Leads

Justin Solomon

Research Areas

Algorithms & Theory

Graphics & Vision

Impact Areas

Justin Solomon

Project

Geometry in Large-Scale Machine Learning

Machine Learning

Data often has geometric structure which can enable better inference; this project aims to scale up geometry-aware techniques for use in machine learning settings with lots of data, so that this structure may be utilized in practice.

Justin Solomon

Stefanie Jegelka

Leads

Justin Solomon

Stefanie Jegelka

Research Areas

Graphics & Vision

Impact Areas

Internet of Things

Justin Solomon

Stefanie Jegelka

Project

Human-Robot Collaboration in Shared Workspace

Interactive Robotics Group

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

Monitoring Fetal Health

Medical Vision Group

We develop algorithms for fetal MRI interpretation, to enable noninvasive fetal monitoring from MRI.

Polina Golland

Leads

Polina Golland

Research Areas

Graphics & Vision

Impact Areas

Polina Golland

Project

Political Geometry: Establishing Fair Mathematical Standards for Political Redistricting

Geometric Data Processing Group

Gerrymandering is a direct threat to our democracy, undermining founding principles like equal protection under the law and eroding public confidence in elections.

Justin Solomon

Leads

Justin Solomon

Research Areas

Algorithms & Theory

Graphics & Vision

Human-Computer Interaction

Impact Areas

Justin Solomon

Project

Quantification of Pulmonary Edema in Chest Radiographs

Medical Vision Group

We develop machine learning algorithms to automatically and quantitatively assess the severity of pulmonary edema from chest x-ray images.

+1

Polina Golland

Leads

Polina Golland

Research Areas

Graphics & Vision

Impact Areas

Polina Golland

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

Robots Adapting to Human Intent

Model-Based Embedded and Robotics Systems Group

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

Sensible Deep Learning for 3D Data

Geometric Data Processing Group

Machine Learning

Developing state-of-the-art deep learning algorithms for analyzing and modeling 3D geometry

Justin Solomon

Leads

Justin Solomon

Research Areas

Graphics & Vision

Impact Areas

Justin Solomon

Project

Sensorized Soft Electric Hands with Handed Shearing Auxetics

Distributed Robotics Laboratory

Putting a twist on traditional pneumatic soft robots via handed shearing auxetics

Lillian Chin

Leads

Lillian Chin

Research Areas

Impact Areas

Lillian Chin

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

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

Project

Wearable Ultrasonic Echolocation

The goal of this project is to develop and test a wearable ultrasonic echolocation aid for people who are blind and visually impaired. We combine concepts from engineering, acoustic physics, and neuroscience to make echolocation accessible as a research tool and mobility aid.

Santani Teng

Leads

Santani Teng

Research Areas

Human-Computer Interaction

Impact Areas

Santani Teng

Project

Where Are They Looking?

Our goal is to build a system that predicts where people are looking in images. Given an image and the location of a head, our approach follows the gaze of the person and identifies the object being looked at.

Leads

Research Areas

Graphics & Vision

Impact Areas

29 People Results

Mazdak Abulnaga

Graduate Student

medical vision

E abulnaga@mit.edu

RM

Member

Monitoring Fetal Health

Medical Vision Group

Geometric Data Processing Group

Geometry and topology for scientific computing and shape analysis

medical vision

PI
Core/Dual

Ted Adelson

Professor

Vision, touch sensing, robotics

E adelson@csail.mit.edu

T 253-0645

RM

Lead

Blood Pressure Imager

Embodied Intelligence Community of Research

Member

Visual Computing Community of Research

Vision, touch sensing, robotics

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

PI
Core/Dual

Regina Barzilay

Professor

Natural language processing, machine learning

E regina@csail.mit.edu

T 258-5706

RM

Lead

Natural Language Processing Group

Aspect-Augmented Adversarial Networks for Domain Adaptation

Member

Vertical AI Community of Research

Applied Machine Learning Community of Research

Natural language processing, machine learning

Lillian Chin

Graduate Student

E ltchin@mit.edu

RM

Lead

Sensorized Soft Electric Hands with Handed Shearing Auxetics

Member

Distributed Robotics Laboratory

Yu-An Chung

Graduate Student

Speech and language processing, machine learning

E andyyuan@mit.edu

RM

Lead

Unsupervised Speech Processing

Member

Spoken Language Systems Group

Speech and language processing, machine learning

Adrian Dalca

Research Scientist

E adalca@csail.mit.edu

Member

Medical Vision Group

Clinical Neuroimaging

Mustafa Doga Dogan

Graduate Student

E doga@mit.edu

RM

Member

HCI Engineering Group

PI
Core/Dual

Fredo Durand

Professor

Vision, graphics, computational photography

E fredo@csail.mit.edu

T 253-7223

RM

Lead

Computer Graphics Group

Human-Computer Interaction

Computational Understanding of Visualizations and Graphic Designs

Member

Computational Bounce Flash for Indoor Portraits

Visual Computing Community of Research

Vision, graphics, computational photography

PI
Core/Dual

John Fisher

Senior Research Scientist

Vision, machine learning, signal processing

E fisher@csail.mit.edu

T 253-0788

RM

Lead

Sensing, Learning and Inference

Member

Visual Computing Community of Research

Vision, machine learning, signal processing

PI
Core/Dual

Polina Golland

Professor

Vision, medical imaging, statistical inference

E polina@csail.mit.edu

T 253-8005

RM

Lead

Medical Vision Group

Monitoring Fetal Health

Cardiac MRI analysis

Clinical Neuroimaging

Quantification of Pulmonary Edema in Chest Radiographs

Member

Visual Computing Community of Research

Vision, medical imaging, statistical inference

Ramin Hasani

Postdoctoral Associate

Machine learning Scientist

E rhasani@csail.mit.edu

Machine learning Scientist

Evan Hernandez

Graduate Student

Natural language processing, machine learning, interpretability

E dez@mit.edu

Natural language processing, machine learning, interpretability

Fern Keniston

Senior Administrative Assistant

Research and Education Support

E fern@csail.mit.edu

T 253-5860

RM 32/ 32-250A/ 391

Member

Clinical Decision-Making Group

Research and Education Support

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

Ruizhi Liao

Graduate Student

E ruizhi@mit.edu

RM

Member

Monitoring Fetal Health

Medical Vision Group

Quantification of Pulmonary Edema in Chest Radiographs

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

Razvan Marinescu

Postdoctoral Associate

Postdoctoral Associate working with Polina Golland on neuroimaging.

E razvan@csail.mit.edu

RM 32-D475B

Member

Clinical Neuroimaging

Medical Vision Group

Postdoctoral Associate working with Polina Golland on neuroimaging.

Radhen Patel

Postdoctoral Associate

Robotics | Haptics | Vision | Machine Learning

E radhen@csail.mit.edu

RM

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

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

Julie Shah

Associate Professor

Robotics, machine learning, artificial intelligence

E julie_a_shah@csail.mit.edu

T 324-4879

Lead

Interactive Robotics Group

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

Embodied Intelligence Community of Research

Robotics, machine learning, artificial intelligence

Nalini Singh

Graduate Student

E nmsingh@mit.edu

RM 32-D475B

Member

Monitoring Fetal Health

Medical Vision Group

18 News Results

Polina Golland

AI & ML Computational Biology Graphics & Vision Health Care

February 16 '21

Golland named 2021 AIMBE Fellow

Dr. Polina Golland to be inducted into medical and biological engineering elite

Golland named 2021 AIMBE Fellow

Robotic helpers

Robotics Health Care

October 22 '20

What to Expect When You’re Expecting Robots

Book co-authored by Associate Professor Julie Shah and Laura Major SM ’05 explores a future populated with robot helpers.

What to Expect When You’re Expecting Robots

drones/biceps

Robotics Health Care Manufacturing

April 27 '20

Muscle signals can pilot a robot

CSAIL system uses muscle signals to cue a drone’s movement, enabling more natural human-robot communication

Muscle signals can pilot a robot

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

point cloud 1

Algorithms & Theory AI & ML Graphics & Vision Big Data Transportation

October 29 '19

Deep learning with point clouds

Research aims to make it easier for self-driving cars, robotics, and other applications to understand the 3D world.

Deep learning with point clouds

Maz

Algorithms & Theory AI & ML Graphics & Vision Health Care

October 02 '19

Better fetal health - by building a map of the placenta

New technique stretches out MRI scans of placentas so they can be more accurately analyzed, and shows the potential of MRI for pregnancy monitoring.

Better fetal health - by building a map of the placenta

dutch pm1

AI & ML Robotics Health Care

July 22 '19

Prime Minister Mark Rutte of the Netherlands tours MIT

Dutch delegation visits the Institute for a tour focused on computing, robotics, and health care innovation.

Prime Minister Mark Rutte of the Netherlands tours MIT

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

Yunzhu Li 2

AI & ML Graphics & Vision Systems & Networking Health Care Manufacturing

June 18 '19

Teaching artificial intelligence to connect senses like vision and touch

MIT CSAIL system can learn to see by touching and feel by seeing, suggesting future where robots can more easily grasp and recognize objects.

Teaching artificial intelligence to connect senses like vision and touch

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

origami gripper

AI & ML Robotics Health Care Manufacturing

March 14 '19

New robot hand is soft and strong

Gripper inspired by “origami magic ball” can grasp wide array of delicate and heavy objects

New robot hand is soft and strong

high res model

Algorithms & Theory Graphics & Vision Systems & Networking Health Care

November 29 '18

Higher-res models for creating structures with complex features

Computer scientists often develop mathematical models to understand how animals move, enabling breakthroughs in designing things like microrobotic wings and artificial bone structures.

Higher-res models for creating structures with complex features

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

speech & object recognition 1

Algorithms & Theory AI & ML Graphics & Vision Health Care

September 19 '18

Machine-learning system tackles speech and object recognition, all at once

Model learns to pick out objects within an image, using spoken descriptions.

Machine-learning system tackles speech and object recognition, all at once

mingmin

AI & ML Graphics & Vision Health Care

June 12 '18

Artificial intelligence senses people through walls

Wireless smart-home system from the Computer Science and Artificial Intelligence Laboratory could monitor diseases and help the elderly “age in place.”

Artificial intelligence senses people through walls

virtual home1

Algorithms & Theory AI & ML Graphics & Vision Health Care

May 30 '18

Teaching chores to an artificial agent

Activity simulator could eventually teach robots tasks like making coffee or setting the table.

Teaching chores to an artificial agent

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

“It’s really exciting to see our small origami robots doing something with potential important applications to healthcare,” Daniela Rus says. Pictured, an example of a capsule and the unfolded origami device.

Robotics Health Care

May 12 '16

Ingestible origami robot can patch wounds inside your stomach!

In experiments involving a simulation of the human esophagus and stomach, researchers at CSAIL, the University of Sheffield, and the Tokyo Institute of Technology have demonstrated a tiny origami robot that can unfold itself from a swallowed capsule and, steered by external magnetic fields, crawl across the stomach wall to remove a swallowed button battery or patch a wound.The new work, which the researchers are presenting this week at the International Conference on Robotics and Automation, builds on a long sequence of papers on origami robots from the research group of CSAIL Director Daniela Rus, the Andrew and Erna Viterbi Professor in MIT’s Department of Electrical Engineering and Computer Science.

Ingestible origami robot can patch wounds inside your stomach!