# Research

- Impact Areas
- Research Areas

3 Group Results matching all criteria

#### 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.

#### Community of Research

## Theory of Computation Community of Research

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

2 Project Results matching all criteria

#### Project

## Reconstructing Neural Circuits from Mammalian Brain

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.

#### Project

## Understanding neural networks in the brain

We aim to develop fully automated algorithms for mapping networks within biological brains.

5 People Results matching all criteria

## Leandro Agudelo

Research Scientist

## Barış Ekim

Graduate Student

## Samuel Sledzieski

Graduate Student

## Joshua Tenenbaum

Professor

## Neil Thompson

Research Scientist

6 News Results matching all criteria

## Forum examines promises and limits of AI in clinical medicine

The confluence of medicine and artificial intelligence stands to create truly high-performance, specialized care for patients, with enhanced precision diagnosis and personalized disease management. But to supercharge these systems we need massive amounts of personal health data, coupled with a delicate balance of privacy, transparency, and trust.

## Robust AI tools to predict future cancer

Researchers created a risk-assessment algorithm that shows consistent performance across datasets from US, Europe and Asia.

## Algorithm reduces unnecessary use of antibiotics for UTIs

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

## CSAIL hosts first-ever TEDxMIT

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

## CSAIL's Daskalakis wins ACM Grace Murray Hopper Award

Constantinos (“Costis”) Daskalakis, an MIT professor and CSAIL principal investigator, has won the 2018 ACM Grace Murray Hopper Award.

## Model learns how individual amino acids determine protein function

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

29 Group Results

#### Research Group

## Algorithms Group

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

#### 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.

#### 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.

#### 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.

#### 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.

#### Research Group

## Clinical Decision-Making Group

We focus on furthering the application of technology and artificial intelligence in medicine and health-care.

#### 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

## Computational Biology Group

We seek to understand the mechanistic basis of human disease, using a combination of computational and experimental techniques.

#### Research Group

## Computational Cognitive Science Group

We study the computational basis of human learning and inference.

#### Research Group

## Computational Connectomics Group

#### 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.

#### 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.

#### 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.

#### 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

## 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 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

## Multimodal Understanding Group

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

computation.

computation.

#### 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

## Supertech Research Group

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

80 Project Results

#### 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.

#### 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.

#### 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

## 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.

#### Project

## Algorithmic Aspects of Performance Engineering

The project concerns algorithmic solutions for writing fast codes.

#### 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.

#### 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.

#### Project

## Artificial tissue homeostasis

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.

#### Project

## Aspect-Augmented Adversarial Networks for Domain Adaptation

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.

#### 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

#### 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

## Blood Pressure Imager

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

#### 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

## Clinical Intervention Prediction with Neural Networks

Integrating multi-modal clinical data and using recurrent and convolution neural networks to predict when patients will need important interventions.

#### 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

## Covering All K-mers Using Joker Characters

We developed a new algorithm to generate compact sequence sets covering all k-mers using joker characters.

#### 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

## Deep Inverse Planning

Deep inverse planning for learning from high-dimensional demonstrations

#### Project

## Determining Wikipedia's Influence on Science

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.

#### Project

## Deterministic Algorithms for Robotic Task and Motion Planning

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

#### Project

## Distributed Algorithms for Dynamic and Noisy Platforms

Distributed systems are now everywhere, for example, in wireless communication networks, distributed data-management systems, coordinated robots, transportation systems, and modern multiprocessors.

#### Project

## Distributed Co-prime Sampling Algorithms

To further parallelize co-prime sampling based sparse sensing, we introduce Diophantine Equation in different algebraic structures to build generalized lattice arrays.

With strong relationship to generalized Chinese Remainder Theorem, the geometry properties in the remainder code space, a special lattice space, are explored.

With strong relationship to generalized Chinese Remainder Theorem, the geometry properties in the remainder code space, a special lattice space, are explored.

#### Project

## Distributed Computation in Ant Colonies

We are interested in applying insights from distributed computing theory to understand how ants and other social insects work together to perform complex tasks such as foraging for food, allocating tasks to workers, and choosing high quality nest sites.

44 People Results

## Leandro Agudelo

Research Scientist

## Peter Ahrens

Graduate Student

## Cenk Baykal

Postdoc Associate

## Martin Demaine

Robotics Engineer

## Barış Ekim

Graduate Student

## Noah Golowich

Graduate Student

## Joanne Hanley

Administrative Assistant II

## Dhiraj Holden

Graduate Student

## Siddhartha Jayanti

Graduate Student

## William Kuszmaul

Graduate Student

## Alexander Lenail

Graduate Student

102 News Results

## How fast do algorithms improve?

MIT scientists show how fast algorithms are improving across a broad range of examples, demonstrating their critical importance in advancing computing.

## Deep learning helps predict new drug combinations to fight COVID-19

Neural network identifies synergistic drug blends for treating viruses like SARS-CoV-2

## Who can bend light for cheaper Internet?

MIT and Facebook’s reconfigurable fiber optics network to battle the end of Moore’s law.

## A language for bioinformatics

With the vast growth of next-generation sequencing data, it’s hard to remember that in 1869 Friedrich Miescher isolated DNA for the first time using cells from nearby hospital bandages. Computational genomics has now ushered in a new era of precision medicine, helping find clinically relevant mutations, potential diagnostics for asthma, and precision-based, personalized medicine.

## A comprehensive map of the SARS-CoV-2 genome

MIT researchers have determined the virus’ protein-coding gene set and analyzed new mutations’ likelihood of helping the virus adapt.

## Forum examines promises and limits of AI in clinical medicine

The confluence of medicine and artificial intelligence stands to create truly high-performance, specialized care for patients, with enhanced precision diagnosis and personalized disease management. But to supercharge these systems we need massive amounts of personal health data, coupled with a delicate balance of privacy, transparency, and trust.

## System detects errors when medication is self-administered

Wireless sensing technology could help improve patients’ technique with inhalers and insulin pens.

## Researchers develop speedier network analysis for a range of computer hardware

The advance could boost recommendation algorithms and internet search.

## Golland named 2021 AIMBE Fellow

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

## “Liquid” machine-learning system adapts to changing conditions

The new type of neural network could aid decision making in autonomous driving and medical diagnosis.

## Robust AI tools to predict future cancer

Researchers created a risk-assessment algorithm that shows consistent performance across datasets from US, Europe and Asia.

## Designing customized “brains” for robots

A new system devises hardware architectures to hasten robots’ response time.

## Model analyzes how viruses escape the immune system

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

## Building machines that better understand human goals

A new algorithm capable of inferring goals and plans could help machines better adapt to the imperfect nature of human planning

## Shrinking massive neural networks used to model language

A new approach could lower computing costs and increase accessibility to state-of-the-art natural language processing.

## Computer-aided creativity in robot design

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

## Algorithm reduces unnecessary use of antibiotics for UTIs

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

## 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.

## Monitoring sleep positions for a healthy rest

Wireless device captures sleep data without using cameras or body sensors; could aid patients with Parkinson’s disease, epilepsy, or bedsores.

## Toward a machine learning model that can reason about everyday actions

Researchers train a model to reach human-level performance at recognizing abstract concepts in video.

## Shrinking deep learning’s carbon footprint

Through innovation in software and hardware, researchers move to reduce the financial and environmental costs of modern artificial intelligence.

## Looking into the black box

Recent advances give theoretical insight into why deep learning networks are successful.

## Algorithm finds hidden connections between paintings at the Met

A team from MIT helped create an image retrieval system to find the closest matches of paintings from different artists and cultures.

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

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