Research

Impact Areas

Entertainment

Leslie Kaelbling

Tomas Lozano-Perez

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

Safety Standards for Autonomous Vehicles

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

Impact Areas

Project

Drones that Drive

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

Leads

Research Areas

Impact Areas

Project

Planning under uncertainty with complex dynamics

We focus on learning to compute near-optimal plans which leverage environmental contact to mitigate action uncertainty, in hopes of enabling inexpensive robotic manipulators to perform precise assembly tasks.

Leads

Research Areas

Project

Theoretical Analysis of Robotic Planning

We are investigating various theoretical properties of robotic planning frameworks such as decidability and optimality.

Leads

Research Areas

Project

Fast Lightweight Autonomy

The goal of the FLA program is to explore non-traditional perception and autonomy methods that could enable a new class of algorithms for minimalistic high-speed navigation in cluttered environments.

Nick Villanueva

Jake Ware

Leads

Jake Ware

Research Areas

Nick Villanueva

Jake Ware

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

Internet of Things

Project

Distributed Robot Garden

The robot garden provides an aesthetically pleasing educational platform that can visualize computer science concepts and encourage young students to pursue programming and robotics.

Leads

Joseph DelPreto

Lindsay Sanneman

Daniela Rus

Research Areas

Impact Areas

Entertainment

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

Safety Standards for Autonomous Vehicles

Joseph DelPreto

4 People Results matching all criteria

Lucas Liebenwein

Graduate Student

Student and Researcher | Robotics, AI | Advanced Autonomy

E lucasl@mit.edu

RM 32-376C

Lead

Member

Coresets for Machine Learning Algorithms

Student and Researcher | Robotics, AI | Advanced Autonomy

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

Localizing External Contact Using Proprioceptive Sensors

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

Tactile and Physical Perception

Soft Contact Modeling

Tactile and Physical Perception

Member

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

PI
Core/Dual

Brian Williams

Professor

Robotics, autonomy, artificial intelligence, machine learning

E williams@csail.mit.edu

T 253-2739

Lead

Model-Based Embedded and Robotics Systems Group

RADMAX

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

20 News Results matching all criteria

Algorithms & Theory Robotics

November 30 '20

Computer-aided creativity in robot design

MIT researchers’ new system optimizes the shape of robots for traversing various terrain types.

Computer-aided creativity in robot design

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

Algorithms & Theory Robotics

June 02 '20

New glove lets you incorporate real-life objects into virtual worlds

Algorithms & Theory Robotics Manufacturing

June 01 '20

Giving soft robots senses

In a pair of papers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), two teams enable better sense and perception for soft robotic grippers.

Giving soft robots senses

Algorithms & Theory AI & ML Robotics

March 05 '20

Showing robots how to do your chores

By observing humans, robots learn to perform complex tasks, such as setting a table.

Showing robots how to do your chores

Algorithms & Theory AI & ML Robotics

February 12 '20

“Sensorized” skin helps soft robots find their bearings

Flexible sensors and an artificial intelligence model tell deformable robots how their bodies are positioned in a 3D environment.

“Sensorized” skin helps soft robots find their bearings

Algorithms & Theory AI & ML Robotics

November 13 '19

Autonomous system improves environmental sampling at sea

Robotic boats could more rapidly locate the most valuable sampling spots in uncharted waters.

Autonomous system improves environmental sampling at sea

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

Algorithms & Theory Graphics & Vision Robotics Manufacturing

July 22 '19

Automated system generates robotic parts for novel tasks

When designing actuators involves too many variables for humans to test by hand, this system can step in.

Automated system generates robotic parts for novel tasks

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

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

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

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”

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

Algorithms & Theory AI & ML Graphics & Vision Robotics

September 17 '18

Helping computers fill in the gaps between video frames

Machine learning system efficiently recognizes activities by observing how objects change in only a few key frames.

Helping computers fill in the gaps between video frames

Algorithms & Theory Graphics & Vision Robotics Manufacturing

September 10 '18

Robots can now pick up any object after inspecting it

Breakthrough CSAIL system suggests robots could one day be able to see well enough to be useful in people’s homes and offices.

Robots can now pick up any object after inspecting it

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

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

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

31 Group Results

Research Group

Algorithms Group

We devise new mathematical tools to tackle the increasing difficulty and importance of problems we pose to computers.

Leads

Costis Daskalakis

Erik Demaine

Michael Goemans

Piotr Indyk

David Karger

Jonathan Kelner

Tom Leighton

Charles E. Leiserson

Aleksander Madry

Ankur Moitra

Ronitt Rubinfeld

Nir Shavit

Ryan Williams

Virginia Vassilevska Williams

Research Areas

Impact Areas

Lead

Costis Daskalakis

Erik Demaine

Michael Goemans

Piotr Indyk

David Karger

Jonathan Kelner

Tom Leighton

Charles E. Leiserson

Aleksander Madry

Ankur Moitra

Ronitt Rubinfeld

Nir Shavit

Ryan Williams

Virginia Vassilevska Williams

Research Group

Applied Computing Group

We design software for high performance computing, develop algorithms for numerical linear algebra, and research random matrix theory and its applications.

Leads

Research Areas

Impact Areas

Research Group

Broderick Lab

We work in the areas of statistics and machine learning.

Tamara Broderick

Leads

Tamara Broderick

Research Areas

Impact Areas

Lead

Tamara Broderick

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.

Aleksander Madry

Leads

Aleksander Madry

Research Areas

Impact Areas

Lead

Aleksander Madry

Community of Research

Cognitive AI Community of Research

This CoR aims to develop AI technology that synthesizes symbolic reasoning, probabilistic reasoning for dealing with uncertainty in the world, and statistical methods for extracting and exploiting regularities in the world, into an integrated picture of intelligence that is informed by computational insights and by cognitive science.

Howard Shrobe

Leads

Howard Shrobe

Research Areas

Impact Areas

Lead

Howard Shrobe

Research Group

Complexity Theory Group

Our interests span quantum complexity theory, barriers to solving P versus NP, theoretical computer science with a focus on probabilistically checkable proofs (PCP), pseudo-randomness, coding theory, and algorithms.

Leads

Shafi Goldwasser

Ronitt Rubinfeld

Michael Sipser

Ryan Williams

Virginia Vassilevska Williams

Research Areas

Impact Areas

Lead

Shafi Goldwasser

Ronitt Rubinfeld

Michael Sipser

Ryan Williams

Virginia Vassilevska Williams

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

Computational Biology

Impact Areas

Lead

Bonnie Berger

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

Computational Biology

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

Community of Research

Computing & Society Community of Research

This community is interested in understanding and affecting the interaction between computing systems and society through engineering, computer science and public policy research, education, and public engagement.

Daniel Weitzner

Leads

Daniel Weitzner

Research Areas

Impact Areas

Lead

Daniel Weitzner

Research Group

Cryptography and Information Security Group

We seek to develop techniques for securing tomorrow's global information infrastructure by exploring theoretical foundations, near-term practical applications, and long-range speculative research.

Leads

Shafi Goldwasser

Silvio Micali

Ronald Rivest

Vinod Vaikuntanathan

Butler Lampson

Research Areas

Impact Areas

Lead

Shafi Goldwasser

Silvio Micali

Ronald Rivest

Vinod Vaikuntanathan

Butler Lampson

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

Community of Research

Embodied Intelligence Community of Research

Our goal is to understand the nature of intelligent behavior in the physical world, through the study of human intelligence and the design and implementation of intelligent robots.

+12

Leslie Kaelbling

Leads

Leslie Kaelbling

Research Areas

Lead

Leslie Kaelbling

+12

Leslie Kaelbling

Research Group

Geometric Data Processing Group

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

Justin Solomon

Leads

Justin Solomon

Research Areas

Impact Areas

Lead

Justin Solomon

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

Internet of Things

Lead

David Karger

Lea Verou

David Karger

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

Lecturers

Lecturers in CSAIL

Leads

Research Areas

Impact Areas

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

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

Multicore Algorithmics

We develop techniques for designing, implementing, and reasoning about multiprocessor algorithms, in particular concurrent data structures for multicore machines and the mathematical foundations of the computation models that govern their behavior.

Nir Shavit

Leads

Nir Shavit

Research Areas

Impact Areas

Lead

Nir Shavit

Research Group

Multimodal Understanding Group

Our objective is to build techniques, software, and hardware that enable natural interaction with
computation.

Randall Davis

Leads

Randall Davis

Research Areas

Impact Areas

Lead

Randall Davis

Research Group

Quantum Information Science Group

Our research interests center around the capabilities and limits of quantum computers, and computational complexity theory more generally.

Peter Shor

Leads

Peter Shor

Research Areas

Impact Areas

Computational Design and Fabrication Group

Lead

Peter Shor

109 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

Computation Structures Group

James Minor

Project

A new way of handling all-to-all broadcast

We design a new all-to-all broadcasts scheme with significantly less communication cost using aggregate signatures.

Alin Tomescu

Jun Wan

Leads

Jun Wan

Research Areas

Alin Tomescu

Jun Wan

Project

A Simplified and Extensible Cilk Runtime for Research

CilkS is a new runtime system for the Cilk multithreaded programming environment which makes it easy to experiment with new algorithms, data structures, and programming linguistics.

Charles E. Leiserson

Tao Schardl

Leads

Charles E. Leiserson

Tao Schardl

Research Areas

Charles E. Leiserson

Tao Schardl

Project

Active Learning of Models for Planning

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

Impact Areas

Entertainment

Leslie Kaelbling

Tomas Lozano-Perez

Project

Algebraic Techniques for Algorithm Design

We work on improving the algorithms for algebraic problems like matrix multiplication, and using these to design algorithms for fundamental non-algebraic problems.

Virginia Vassilevska Williams

Leads

Virginia Vassilevska Williams

Research Areas

Virginia Vassilevska Williams

Project

Algorithmic Aspects of Performance Engineering

Supertech Research Group

The project concerns algorithmic solutions for writing fast codes.

Leads

Research Areas

Impact Areas

Theory of Distributed Systems Group

Project

An Algorithmic Theory of Brain Networks

We are developing an algorithmic theory for brain networks, based on simple synchronized stochastic graph-based neural network models.

Nancy Lynch

Leads

Nancy Lynch

Research Areas

Computer-Aided Programming

Nancy Lynch

Project

An Interlock for Self Driving Cars

Software Design Group

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

Impact Areas

Interactive Robotics Group

Daniel Jackson

Armando Solar-Lezama

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

Project

Approximating the diameter of a directed graph

There is a family of approximation algorithms for computing the diameter of an undirected graph that give a time/accuracy trade-off and our goal is to extend these results to directed graphs.

Virginia Vassilevska Williams

Leads

Virginia Vassilevska Williams

Research Areas

Computation Structures Group

Virginia Vassilevska Williams

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

Natural Language Processing Group

Project

Aspect-Augmented Adversarial Networks for Domain Adaptation

Vertical AI Community of Research

We propose a novel aspect-augmented adversarial network for cross-aspect and cross-domain adaptation tasks. The effectiveness of our approach suggests the potential application of adversarial networks to a broader range of NLP tasks for improved representation learning, such as machine translation and language generation.

Regina Barzilay

Tommi Jaakkola

Leads

Regina Barzilay

Tommi Jaakkola

Research Areas

Cryptography and Information Security Group

Regina Barzilay

Tommi Jaakkola

Project

Basing Cryptography on Structured Hardness

We aim to base a variety of cryptographic primitives on complexity theoretic assumptions. We focus on the assumption that there exist highly structured problems --- admitting so called "zero-knowledge" protocols --- that are nevertheless hard to compute

Leads

Research Areas

Project

Bayesian Optimization for Global Optimization of Expensive Black-box Functions

Machine Learning

We study the fundamentals of Bayesian optimization and develop efficient Bayesian optimization methods for global optimization of expensive black-box functions originated from a range of different applications.

Leads

Research Areas

Impact Areas

Project

Better Models for Ride-Sharing

Traffic is not just a nuisance for drivers: It’s also a public health hazard and bad news for the economy.

Leads

Research Areas

Impact Areas

Project

Blood Pressure Imager

Vision Group

Development of affordable wearable continuous blood pressure monitor based on radial arterial pulse imaged from the skin surface of human wrist

Mumin Jin

Aya G. Halawi

Jianhua Li

Leads

Abhijit Biswas

Ted Adelson

Mandayam A. Srinivasan

Mohan Thanikachalam

Research Areas

Computational Biology

Mumin Jin

Aya G. Halawi

Jianhua Li

Project

Brain-Controlled Robots

This project aims to let people correct robot mistakes with nothing more than their brain signals - to allow robots to adapt to humans rather than the other way around

Frank H. Guenther

Daniela Rus

Joseph DelPreto

Leads

Daniela Rus

Joseph DelPreto

Research Areas

Frank H. Guenther

Daniela Rus

Joseph DelPreto

Project

Bridging Theory and Practice in Shared-Memory Parallel Algorithm Design

This project aims to design parallel algorithms for shared-memory machines that are efficient both in theory and also in practice.

Julian Shun

Leads

Julian Shun

Research Areas

Impact Areas

Julian Shun

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

Tao Du

Project

Controlling drones and other robots with gestures

Interact with robots and other devices by gesturing, using wearable muscle and motion sensors

Joseph DelPreto

Leads

Joseph DelPreto

Research Areas

Joseph DelPreto

Project

Coresets for Machine Learning Algorithms

Our goal is to design novel data compression techniques to accelerate popular machine learning algorithms in Big Data and streaming settings.

Daniela Rus

Leads

Daniela Rus

Research Areas

Impact Areas

Cryptography and Information Security Group

Daniela Rus

Project

Data Garbling: Computing on Encrypted Data

We are investigating the limits of computing on encrypted data, with a focus on the private outsourcing of computation over sensitive data.

Leads

Research Areas

Impact Areas

Project

Deep Inverse Planning

Vision Group

Deep inverse planning for learning from high-dimensional demonstrations

Leads

Research Areas

Project

Determining Wikipedia's Influence on Science

Supertech Research Group

Wikipedia is one of the most widely accessed encyclopedia sites in the world, including by scientists. Our project aims to investigate just how far Wikipedia’s influence goes in shaping science.

Neil Thompson

Charles E. Leiserson

Leads

Neil Thompson

Charles E. Leiserson

Research Areas

Impact Areas

Robust Learning for Autonomous Vehicles

Neil Thompson

Charles E. Leiserson

72 People Results

Murad Abu-Khalaf

Program Manager, Toyota-CSAIL Joint Research Center

E murad@mit.edu

T 452-2859

Leandro Agudelo

Research Scientist

Systems Genomics, CompBio, Topological Integrative Biology, Biology

E lagudelo@csail.mit.edu

Systems Genomics, CompBio, Topological Integrative Biology, Biology

Alexander Amini

Graduate Student

PhD Candidate. Deep Learning; Robotics

E Amini@mit.edu

Lead

Member

Natural Language Processing Group

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

Lead

Aspect-Augmented Adversarial Networks for Domain Adaptation

Member

Vertical AI Community of Research

Applied Machine Learning Community of Research

Natural language processing, machine learning

Cenk Baykal

Graduate Student

E baykal@mit.edu

RM 32-376C

Member

Coresets for Machine Learning Algorithms

Noam Buckman

Graduate Student

PhD Candidate. Autonomous vehicles. Multi-robot systems.

E nbuckman@mit.edu

Member

Model-Based Embedded and Robotics Systems Group

PhD Candidate. Autonomous vehicles. Multi-robot systems.

Richard Camilli

Research Affiliate

E romeo@mit.edu

Member

Lillian Chin

Graduate Student

E ltchin@mit.edu

Lead

Sensorized Soft Electric Hands with Handed Shearing Auxetics

Member

Is the Casino using a Riffle Shuffle?

PI
Core/Dual

Costis Daskalakis

Associate Professor

Algorithms, Economics, Game Theory, Statistics, Machine Learning

E costis@csail.mit.edu

T 253-9643

Lead

Algorithms Group

Understanding Convergence of Iterative Algorithms

Center for Deployable Machine Learning (CDML)

Member

Algorithms, Economics, Game Theory, Statistics, Machine Learning

Joseph DelPreto

Graduate Student

Works on human-robot interaction using muscle and brain signals.

E delpreto@csail.mit.edu

RM 32-376A

Lead

Supervising Robots with Muscle and Brain Signals

Brain-Controlled Robots

Distributed Robot Garden

Robot Compiler

SoFi - The Soft Robotic Fish

Soft Robotic Hand

Using Muscle Signals to Lift Objects with Robots

Controlling drones and other robots with gestures

Helping robots learn using demonstrations

Member

Works on human-robot interaction using muscle and brain signals.

PI
Core/Dual

Erik Demaine

Professor

Algorithms, theory, computational geometry, complexity

E edemaine@mit.edu

T 253-6871

Lead

Algorithms Group

Member

Computational Multicopter Design

Algorithms, theory, computational geometry, complexity

Martin Demaine

Robotics Engineer

E mdemaine@mit.edu

T 253-7953

Mustafa Doga Dogan

Graduate Student

E doga@mit.edu

Member

HCI Engineering Group

Kevin Doherty

Graduate Student

E KDoherty@mit.edu

RM 32-235B

Tao Du

Graduate Student

CS PhD student

E taodu@csail.mit.edu

Lead

CS PhD student

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

Clement Gehring

Graduate Student

E gehring@csail.mit.edu

Lead

Learning and Planning with Compressed Linear Expectation Models

Member

Igor Gilitschenski

Research Scientist

E igilitschenski@mit.edu

Member

Cryptography and Information Security Group

PI
Core/Dual

Shafi Goldwasser

Professor

Theory, cryptography, cybersecurity, complexity

E shafi@csail.mit.edu

T 253-5914

Lead

Complexity Theory Group

Member

Computation Structures Group

Computational Connectomics Group