# Research

- Research Areas
- Impact Areas

1 News Results matching all criteria

19 Group Results

#### 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.

#### 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.

#### 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.

#### 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.

#### 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.

#### 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.

#### Research Group

## Data Systems Group

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

#### Research Group

## Decentralized Information Group

We are investigating decentralized technologies that affect social change.

#### Research Group

## Geometric Data Processing Group

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

#### Research Group

## Haystack Group

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

#### Research Center

## Internet Policy Research Initiative

Our mission is to work with policy makers and cybersecurity technologists to increase the trustworthiness and effectiveness of interconnected digital systems.

#### 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.

#### Research Group

## Quantum Information Science Group

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

#### Research Group

## Software Design Group

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

#### Research Group

## Supertech Research Group

We investigate the technologies that support scalable high-performance computing, including hardware, software, and theory.

#### Research Group

## Theory of Computation Group

Theory research at CSAIL covers a broad spectrum of topics, including algorithms, complexity theory, cryptography, distributed systems, parallel computing and quantum computing.

#### Research Group

## Theory of Distributed Systems Group

We work on a wide range of problems in distributed computing theory. We study algorithms and lower bounds for typical problems that arise in distributed systems---like resource allocation, implementing shared memory abstractions, and reliable communication.

30 Project Results

#### Project

## Active Learning of Models for Planning

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.

#### Project

## Adversarial Cyber Security

Our goal is to understand the nature of cyber security arms races between malicious and bonafide parties. Our vision is autonomous cyber defenses that anticipate and take measures against counter attacks.

#### Project

## Algorithmic Aspects of Performance Engineering

The project concerns algorithmic solutions for writing fast codes.

#### Project

## Alloy

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.

#### Project

## Automated Attack Tree Generation for Critical Infrastructure

Using AI methods, we are developing an attack tree generator that automatically enumerates cyberattack vectors for industrial control systems in critical infrastructure (electric grids, water networks and transportation systems). The generator can quickly assess cyber risk for a system at scale.

#### Project

## Bayesian Optimization for Global Optimization of Expensive Black-box Functions

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.

#### 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.

#### 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.

#### 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.

#### Project

## Data Civilizer

Data scientists universally report that they spend at least 80% of their time finding data sets of interest, accessing them, cleaning them and assembling them into a unified whole.

#### 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.

#### Project

## Database Design

The conventional wisdom described in all text books for performing database design is never followed in practice.

#### Project

## Denial of Service Mitigation through Protocol Design

We aim to better understand the features of network protocols that facilitate denial of service attacks, in order to design more robust protocols and architectures in the future and evaluate existing designs more accurately.

#### Project

## Diversity-inducing Probability Measures

We aim to understand theory and applications of diversity-inducing probabilities (and, more generally, "negative dependence") in machine learning, and develop fast algorithms based on their mathematical properties.

## Suvrit Sra

#### Project

## Geometry and topology for scientific computing, shape analysis, and computer graphics

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

#### Project

## Keeping America Safe: Toward More Secure Networks for Critical Sectors

Report warns of hacking risk to electric grid, oil pipelines, and other critical infrastructure

#### Project

## Keys Under Doormats

Our report argues that giving the government special access to data poses major security risks

#### Project

## Optimal transport for statistics and machine learning

Linking probability with geometry to improve the theory and practice of machine learning

#### Project

## Poirot: Secure Protocol Implementation by Design

Even formally verified protocols that have been faithfully implemented have been found to have security vulnerabilities. A new framework eliminates such vulnerabilities by design.

#### Project

## Political Geometry: Establishing Fair Mathematical Standards for Political Redistricting

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

#### 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.

#### Project

## PrivacyML - A Privacy Preserving Framework for Machine Learning

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

#### Project

## Programming Abstractions for Dynamic Graph Analytics

We plan to develop a programming abstraction to enable programmers to write efficient parallel programs to process dynamic graphs.

#### Project

## Random Graph with Applications in MPC

To explore how randomness in connectivity can improve the performance of secure multi-party computation (MPC) and the properties of communication graph to support MPC.

35 People Results

## Cenk Baykal

Graduate Student

## R. David Edelman

Director, Project on Technology, Economy & National Security

## Gregory Falco

Postdoctoral Associate

## Siddhartha Jayanti

Graduate Student

## Kenji Kawaguchi

Graduate Student

## David Lazar

Graduate Student

## Ilia Lebedev

Graduate Student

## Lucas Liebenwein

Graduate Student

## Slobodan Mitrovic

Postdoctoral Fellow

## Vaikkunth Mugunthan

Graduate Student

21 News Results

## CSAIL hosts first-ever TEDxMIT

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

## Platform ensures that web services adhere to users' privacy preferences

New MIT/Harvard platform acts as gatekeeper to ensure web services adhere to data restrictions

## MIT CSAIL holds trustworthy AI event with Microsoft

Workshop explores technical directions for making AI safe, fair, and understandable

## MIT hosts workshop on theoretical foundations of deep learning

Last week MIT’s Institute for Foundations of Data Science (MIFODS) held an interdisciplinary workshop aimed at tackling the underlying theory behind deep learning. Led by MIT professor Aleksander Madry, the event focused on a number of research discussions at the intersection of math, statistics, and theoretical computer science.

## Opening up open-source to design better chips

MIT CSAIL system lets users change one part of a processor’s design without impacting the others

## Cryptographic protocol enables greater collaboration in drug discovery

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

## Holding law-enforcement accountable for electronic surveillance

CSAIL system encourages government transparency using cryptography on a public log of wiretap requests.

## 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.

## Building AI systems that make fair decisions

Harini Suresh, a PhD student at MIT CSAIL, studies how to make machine learning algorithms more understandable and less biased.

## MIT engineering students team up with Georgetown lawyers-in-training on internet privacy legislation

Every spring, engineering students from MIT and law students from Georgetown University overcome the distance between their institutions and disciplines in a semester-long flurry of virtual classroom meetings and late-night Google hangout sessions, culminating in presentations to policy experts in DC.

## MIT experts discuss online security and protecting data in a “public-private” Internet age

Last week CSAIL hosted the fourth “Hot Topics in Computing” speaker series, a monthly forum where experts hold discussions with community members on various hot-button tech topics.

## Private browsing gets more private

New system patches security holes left open by web browsers’ private-browsing functions.

## Energy-efficient encryption for the internet of things

Special-purpose chip reduces power consumption of public-key encryption by 99.75 percent, increases speed 500-fold.

## MIT security experts discuss “Spectre” and “Meltdown” processor flaws

Last week CSAIL hosted the second “Hot Topics in Computing” speaker series, a monthly forum where computing experts hold discussions with community members on various topics in the computer science field.

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

## 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.”

## Goldwasser gives briefing on cryptography to Congress

Last week CSAIL principal investigator Shafi Goldwasser spoke about cryptography and privacy as part of the annual congressional briefing of the American Mathematical Society (AMS) and the Mathematical Sciences Research Institute (MSRI).

## Fooling neural networks w/3D-printed objects

Artificial intelligence (AI) in the form of “neural networks” are increasingly used in technologies like self-driving cars to be able to see and recognize objects. Such systems could even help with tasks like identifying explosives in airport security lines.

## Selective memory

In a traditional computer, a microprocessor is mounted on a “package,” a small circuit board with a grid of electrical leads on its bottom. The package snaps into the computer’s motherboard, and data travels between the processor and the computer’s main memory bank through the leads.

## CSAIL's Daniel Jackson receives two ACM awards

This week the Association for Computer Machinery presented CSAIL principal investigator Daniel Jackson with the 2017 ACM SIGSOFT Outstanding Research Award for his pioneering work in software engineering. (This fall he also received the ACM SIGSOFT Impact Paper Award for his research method for finding bugs in code.)An EECS professor and associate director of CSAIL, Jackson was given the Outstanding Research Award for his “foundational contributions to software modeling, the creation of the modeling language Alloy, and the development of a widely used tool supporting model verification.”

## Security for multirobot systems

Distributed planning, communication, and control algorithms for autonomous robots make up a major area of research in computer science.