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1 News Results matching all criteria

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

23 Group Results

Research Group

Advanced Network Architecture Group

The challenge that motivates the ANA group is to foster a healthy future for the Internet. The interplay of private sector investment, public sector regulation and public interest advocacy, as well as the global diversity in drivers and aspirations, makes for an uncertain future.

+4

David Clark

Karen Sollins

Leads

David Clark

Karen Sollins

Research Areas

Security & Cryptography

Systems & Networking

Impact Areas

Lead

David Clark

Karen Sollins

David Clark

Karen Sollins

Research Group

Anyscale Learning for All ALFA

Our vision is data-driven machine learning systems that advance the quality of healthcare, the understanding of cyber arms races and the delivery of online education.

+1

Una-May O'Reilly

Leads

Una-May O'Reilly

Research Areas

Security & Cryptography

Impact Areas

Lead

Una-May O'Reilly

Una-May O'Reilly

Community of Research

Applied Machine Learning Community of Research

This CoR brings together researchers at CSAIL working across a broad swath of application domains. Within these lie novel and challenging machine learning problems serving science, social science and computer science.

+6

Una-May O'Reilly

Leads

Una-May O'Reilly

Research Areas

Computational Biology

Programming Languages & Software Engineering

Impact Areas

Lead

Una-May O'Reilly

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

Computational Biology

Impact Areas

Lead

Tomaso Poggio

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

Computational Biology

Impact Areas

Lead

Peter Szolovits

Peter Szolovits

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.

+6

Howard Shrobe

Leads

Howard Shrobe

Research Areas

Human-Computer Interaction

Security & Cryptography

Systems & Networking

Impact Areas

Lead

Howard Shrobe

Howard Shrobe

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

Computation Structures Group

Our mission is fostering the creation and development of high-performance, reliable and secure computing systems that are easy to interact with.

+21

Leads

Srini Devadas

Daniel Sanchez

Armando Solar-Lezama

Arvind

Research Areas

Computer Architecture

Programming Languages & Software Engineering

Security & Cryptography

Systems & Networking

Impact Areas

Lead

Srini Devadas

Daniel Sanchez

Armando Solar-Lezama

Arvind

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 Cognitive Science Group

We study the computational basis of human learning and inference.

Joshua Tenenbaum

Leads

Joshua Tenenbaum

Research Areas

Computational Biology

Impact Areas

Lead

Joshua Tenenbaum

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

Algorithms & Theory

Computational Biology

Impact Areas

Lead

Nir Shavit

Nir Shavit

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

Computational Biology

Impact Areas

Lead

Dave Gifford

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

Computational Biology

Impact Areas

Lead

Aude Oliva

Aude Oliva

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.

+8

Daniel Weitzner

Leads

Daniel Weitzner

Research Areas

Algorithms & Theory

Human-Computer Interaction

Security & Cryptography

Systems & Networking

Impact Areas

Internet of Things

Lead

Daniel Weitzner

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

Algorithms & Theory

Security & Cryptography

Impact Areas

Lead

Shafi Goldwasser

Silvio Micali

Ronald Rivest

Vinod Vaikuntanathan

Butler Lampson

Research Group

Data Systems Group

We conduct research on all areas of database systems and information management.

+15

Leads

Sam Madden

Michael Stonebraker

Tim Kraska

Research Areas

Programming Languages & Software Engineering

Security & Cryptography

Systems & Networking

Impact Areas

Lead

Sam Madden

Michael Stonebraker

Tim Kraska

Research Group

Lecturers

Lecturers in CSAIL

Leads

Research Areas

Algorithms & Theory

Security & Cryptography

Systems & Networking

Impact Areas

Research Group

Medical Vision Group

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

+8

Polina Golland

Leads

Polina Golland

Research Areas

Computational Biology

Graphics & Vision

Impact Areas

Lead

Polina Golland

Polina Golland

Research Group

Software Design Group

Our goal is to find better ways to make software, and ways to make software better.

Daniel Jackson

Leads

Daniel Jackson

Research Areas

Human-Computer Interaction

Programming Languages & Software Engineering

Security & Cryptography

Impact Areas

Lead

Daniel Jackson

Daniel Jackson

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

Programming Languages & Software Engineering

Security & Cryptography

Systems & Networking

Impact Areas

Internet of Things

Lead

Sam Madden

Sam Madden

Research Group

Tidor Lab

We focus on the analysis of complex biological systems at both the molecular level and the systems level.

Bruce Tidor

Leads

Bruce Tidor

Research Areas

Computational Biology

Systems & Networking

Impact Areas

Lead

Bruce Tidor

Bruce Tidor

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

Weiss Laboratory for Synthetic Biology

The Weiss Lab seeks to create integrated biological systems capable of autonomously performing useful tasks, and to elucidate the design principles underlying complex phenotypes.

Leads

Research Areas

Computational Biology

Systems & Networking

Impact Areas

14 Project Results

Project

Alloy

Software Design Group

Human-Computer Interaction Community of Research

Alloy is a language for describing structures and a tool for exploring them. It has been used in a wide range of applications from finding holes in security mechanisms to designing telephone switching networks. Hundreds of projects have used Alloy for design analysis, for verification, for simulation, and as a backend for many other kinds of analysis and synthesis tools, and Alloy is currently being taught in courses worldwide.

Daniel Jackson

Leads

Daniel Jackson

Research Areas

Human-Computer Interaction

Programming Languages & Software Engineering

Security & Cryptography

Impact Areas

Daniel Jackson

Project

Artificial tissue homeostasis

Weiss Laboratory for Synthetic Biology

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

Computational Biology

Impact Areas

Project

Clinical Intervention Prediction with Neural Networks

Cognitive AI Community of Research

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

Computational Biology

Impact Areas

Project

Drug Target Identification Via Computational Modeling

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

Computational Biology

Impact Areas

Project

Flexible cellular platforms for reconfigurable biocircuits

Weiss Laboratory for Synthetic Biology

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

Computational Biology

Impact Areas

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

Computational Biology

Impact Areas

Bonnie Berger

Project

Population-level Tumor Growth Inhibition Modeling

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

Computational Biology

Impact Areas

Project

Privacy-Preserving Decentralized Optimization

To enable privacy preservation in decentralized optimization, differential privacy is the most commonly used approach. However, under such scenario, the trade-off between accuracy (even efficiency) and privacy is inevitable. In this project, distributed numerical optimization scheme incorporated with lightweight cryptographic information sharing are explored. The affect on the convergence rate from network topology is considered.

Hanshen Xiao

Leads

Hanshen Xiao

Research Areas

Algorithms & Theory

Security & Cryptography

Impact Areas

Hanshen Xiao

Project

PrivacyML - A Privacy Preserving Framework for Machine Learning

Decentralized Information Group

Cognitive AI Community of Research

Computing & Society Community of Research

We are developing a general framework that enforces privacy transparently enabling different kinds of machine learning to be developed that are automatically privacy preserving.

Lalana Kagal

Vaikkunth Mugunthan

Leads

Lalana Kagal

Vaikkunth Mugunthan

Research Areas

Security & Cryptography

Impact Areas

Internet of Things

Lalana Kagal

Vaikkunth Mugunthan

Project

Reconstructing Neural Circuits from Mammalian Brain

Computational Connectomics Group

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

Algorithms & Theory

Computational Biology

Systems & Networking

Impact Areas

Yaron Meirovitch

Nir Shavit

Project

Semi-Supervised Regression with Cycle Wasserstein Regression GANs

Clinical Decision-Making Group

Cognitive AI Community of Research

Using adversarial signals and a cycle-consistency based regularization, we can supplement paired regression tasks with unpaired data to improve regression performance.

Leads

Research Areas

Computational Biology

Impact Areas

Project

Structure-based Inhibitor Design Against ZIKV Protease

This project uses computational biology and chemistry tools to design a pharmaceutical to combat the Zika Virus.

Leads

Research Areas

Computational Biology

Impact Areas

Project

Towards Context-Aware Functional Genomics

Computation and Biology

Theory of Computation Community of Research

We aim to develop a context-aware data-driven functional genomics framework that can characterize tissue-specific gene representations, provide context-aware genotype to phenotype mapping, and enable network-based exploration of disease genetics.

Bonnie Berger

Leads

Bonnie Berger

Research Areas

Computational Biology

Impact Areas

Bonnie Berger

Project

Using Clinical Domain Knowledge for Processing Physiological Data

Clinical Decision-Making Group

Cognitive AI Community of Research

Using medical knowledge to improve learned representations of patient health trajectories.

Leads

Research Areas

Computational Biology

Impact Areas

12 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

RM

Lead

Covering All K-mers Using Joker Characters

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

R. David Edelman

Director, Project on Technology, Economy & National Security

Machine learning, cybersecurity, governance

E rde@mit.edu

T 258-6389

Machine learning, cybersecurity, governance

Barış Ekim

Graduate Student

E ekim@csail.mit.edu

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

Konstantin Krismer

Graduate Student

E krismer@mit.edu

RM

Member

Computational Genomics Group

PI
Core/Dual

Una-May O'Reilly

Principal Research Scientist

Applied AI and ML in cybersecurity, healthcare, education

E unamay@csail.mit.edu

T 253-6437

RM

Lead

Anyscale Learning for All ALFA

Applied Machine Learning Community of Research

Adversarial Cyber Security

GIGABEATS: Data science for medical sensor data

MOOC Learner Project: Data science for e-learning

Member

Cognitive AI Community of Research

Applied AI and ML in cybersecurity, healthcare, education

PI
Core/Dual

Ronald Rivest

Institute Professor

Cryptography, cybersecurity, RSA public-key encryption

E rivest@mit.edu

T 253-5880

RM

Lead

Cryptography and Information Security Group

Member

Theory of Computation Community of Research

Computing & Society Community of Research

Cryptography, cybersecurity, RSA public-key encryption

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

Samuel Sledzieski

Graduate Student

E samsl@csail.mit.edu

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

Hanshen Xiao

Graduate Student

E hsxiao@MIT.EDU

RM

Lead

Distributed Co-prime Sampling Algorithms

Privacy-Preserving Decentralized Optimization

13 News Results

Proteins

AI & ML Computational Biology Health Care

January 21 '21

Model analyzes how viruses escape the immune system

Using this computational system, researchers can identify viral protein sequences that could make better vaccine targets.

Model analyzes how viruses escape the immune system

UTI 1

Algorithms & Theory AI & ML Computational Biology Health Care

November 04 '20

Algorithm reduces unnecessary use of antibiotics for UTIs

Machine learning model predicts probability that a patient’s UTI can be treated by various antibiotics

Algorithm reduces unnecessary use of antibiotics for UTIs

Bluetooth sharing

AI & ML Security & Cryptography Systems & Networking Health Care

April 09 '20

Automated Covid-19 contact tracing - while preserving privacy

New system uses Bluetooth signals from your smartphone, with the goal of automating Covid-19 contact tracing while preserving privacy

Automated Covid-19 contact tracing - while preserving privacy

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

regina ai

AI & ML Computational Biology Health Care

May 07 '19

Using AI to predict breast cancer and personalize care

Image-based AI model can predict breast cancer years in advance

Using AI to predict breast cancer and personalize care

Bio2

Computational Biology Health Care

May 06 '19

Merging cell datasets, panorama style

Algorithm stitches multiple datasets into a single “panorama,” which could provide new insights for medical and biological studies.

Merging cell datasets, panorama style

protein

Algorithms & Theory Computational Biology Health Care

March 26 '19

Model learns how individual amino acids determine protein function

Technique could improve machine-learning tasks in protein design, drug testing, and other applications.

Model learns how individual amino acids determine protein function

mit pharma

AI & ML Computational Biology Security & Cryptography Cybersecurity Health Care

October 18 '18

Cryptographic protocol enables greater collaboration in drug discovery

Neural network that securely finds potential drugs could encourage large-scale pooling of sensitive data.

Cryptographic protocol enables greater collaboration in drug discovery

RB1

AI & ML Computational Biology Health Care

October 04 '18

Regina Barzilay joins leadership of new effort on machine learning in health

MacArthur “geniuses” in machine learning and synthetic biology to serve as faculty co-leads; Nobel laureate to chair advisory board of new research center.

Regina Barzilay joins leadership of new effort on machine learning in health

Eye movement

Computational Biology Health Care

May 22 '18

Gauging language proficiency through eye movement

Study tracks eye movement to determine how well people understand English as a foreign language.

Gauging language proficiency through eye movement

Privacy and genomic studies1

Computational Biology Security & Cryptography Cybersecurity Health Care

May 10 '18

Protecting confidentiality in genomic studies

Genome-wide association studies, which look for links between particular genetic variants and incidence of disease, are the basis of much modern biomedical research.

Protecting confidentiality in genomic studies

bbva1

Algorithms & Theory Security & Cryptography Big Data Cybersecurity Education Entertainment Health Care Internet of Things Manufacturing

January 16 '18

Goldwasser, Micali, and Rivest win BBVA Foundation Frontiers of Knowledge Awards

This week it was announced that MIT professors and CSAIL principal investigators Shafi Goldwasser, Silvio Micali, Ronald Rivest, and former MIT professor Adi Shamir won this year’s BBVA Foundation Frontiers of Knowledge Awards in the Information and Communication Technologies category for their work in cryptography.

Goldwasser, Micali, and Rivest win BBVA Foundation Frontiers of Knowledge Awards

Machine learning approach could aid the design of industrial processes for drug manufacturing.

AI & ML Computational Biology Health Care

June 27 '17

Computer system predicts products of chemical reactions

When organic chemists identify a useful chemical compound — a new drug, for instance — it’s up to chemical engineers to determine how to mass-produce it. There could be 100 different sequences of reactions that yield the same end product. But some of them use cheaper reagents and lower temperatures than others, and perhaps most importantly, some are much easier to run continuously, with technicians occasionally topping up reagents in different reaction chambers.

Computer system predicts products of chemical reactions