Data
Data

Data

AgeLab Artificial Intelligence Automobiles Autonomous vehicles Behavior Center for Transportation and Logistics Collaboration Data Industry Logistics Safety Transportation

Building an understanding of how drivers interact with emerging vehicle technologies

The MIT Advanced Vehicle Technology Consortium provides data-driven insights into driver behavior, along with trust in AI and advance vehicle technology.

Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Data Electrical engineering and computer science (EECS) Human-computer interaction machine learning MIT Schwarzman College of Computing Research Robotics School of Engineering

Can robots learn from machine dreams?

MIT CSAIL researchers used AI-generated images to train a robot dog in parkour, without real-world data. Their LucidSim system demonstrates generative AI’s potential for creating robotics training data.

Algorithms Artificial Intelligence Computer science and technology Data Design Human-computer interaction Interview machine learning Mechanical engineering MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Research School of Engineering

3 Questions: Inverting the problem of design

MIT and IBM researchers are creating linkage mechanisms to innovate human-AI kinematic engineering.

Algorithms Artificial Intelligence Biological engineering Broad Institute Cells Computer science and technology Data Electrical engineering and computer science (EECS) Genetic engineering Genetics IDSS Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Research School of Engineering

A causal theory for studying the cause-and-effect relationships of genes

By sidestepping the need for costly interventions, a new method could potentially reveal gene regulatory programs, paving the way for targeted treatments.

Algorithms Artificial Intelligence Data Electrical engineering and computer science (EECS) Equity and inclusion Ethics IDSS machine learning MIT Schwarzman College of Computing MIT Sloan School of Management Open access Policy Racism Research School of Engineering Social justice Social sciences Technology and policy

Empowering systemic racism research at MIT and beyond

Researchers in the MIT Initiative on Combatting Systemic Racism are building an open data repository to advance research on racial inequity in domains like policing, housing, and health care.

Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical engineering and computer science (EECS) machine learning MIT Schwarzman College of Computing Research Robotics School of Engineering

A faster, better way to train general-purpose robots

Inspired by large language models, researchers develop a training technique that pools diverse data to teach robots new skills.

Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical engineering and computer science (EECS) Human-computer interaction machine learning MIT Schwarzman College of Computing Quest for Intelligence Research School of Engineering

Making it easier to verify an AI model’s responses

By allowing users to clearly see data referenced by a large language model, this tool speeds manual validation to help users spot AI errors.

Algorithms Artificial Intelligence Computer modeling Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical engineering and computer science (EECS) Faculty machine learning MIT Schwarzman College of Computing Profile School of Engineering Social networks

Modeling relationships to solve complex problems efficiently

Associate Professor Julian Shun develops high-performance algorithms and frameworks for large-scale graph processing.

Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical engineering and computer science (EECS) machine learning MIT Schwarzman College of Computing Research Robotics School of Engineering

How AI is improving simulations with smarter sampling techniques

MIT CSAIL researchers created an AI-powered method for low-discrepancy sampling, which uniformly distributes data points to boost simulation accuracy.

Artificial Intelligence cybersecurity Data Electrical engineering and computer science (EECS) Electronics Light machine learning MIT Schwarzman College of Computing Photonics Privacy Research Research Laboratory of Electronics School of Engineering

New security protocol shields data from attackers during cloud-based computation

The technique leverages quantum properties of light to guarantee security while preserving the accuracy of a deep-learning model.