School of Engineering

Auto Added by WPeMatico

3 Questions: How AI is helping us monitor and support vulnerable ecosystems

Abdul Latif Jameel Water and Food Systems Lab (J-WAFS), Algorithms, Animals, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, data, Ecology, Electrical engineering and computer science (EECS), Environment, Graduate, postdoctoral, Interview, Machine Learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Pollution, Research, School of Engineering, Students, Sustainability

A recent study from Oregon State University estimated that more than 3,500 animal species are at risk of extinction because of factors including habitat alterations, natural resources being overexploited, and climate change.To better understand these changes and protect vulnerable wildlife, conservationists like MIT PhD student and Computer Science and Artificial Intelligence Laboratory (CSAIL) researcher Justin Kay […]

3 Questions: How AI is helping us monitor and support vulnerable ecosystems Read More »

Teaching robots to map large environments

Aeronautical and astronautical engineering, Algorithms, Artificial Intelligence, Autonomous vehicles, Computer science and technology, Computer vision, Disaster response, Electrical engineering and computer science (EECS), Laboratory for Information and Decision Systems (LIDS), Machine Learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, Robotics, School of Engineering

A robot searching for workers trapped in a partially collapsed mine shaft must rapidly generate a map of the scene and identify its location within that scene as it navigates the treacherous terrain.Researchers have recently started building powerful machine-learning models to perform this complex task using only images from the robot’s onboard cameras, but even

Teaching robots to map large environments Read More »

MIT researchers propose a new model for legible, modular software

Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical engineering and computer science (EECS), Human-computer interaction, Machine Learning, MIT Schwarzman College of Computing, Programming, Programming languages, Research, School of Engineering, Software

Coding with large language models (LLMs) holds huge promise, but it also exposes some long-standing flaws in software: code that’s messy, hard to change safely, and often opaque about what’s really happening under the hood. Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) are charting a more “modular” path ahead. Their new approach breaks

MIT researchers propose a new model for legible, modular software Read More »

Charting the future of AI, from safer answers to faster thinking

Algorithms, Artificial Intelligence, Classes and programs, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, data, Electrical engineering and computer science (EECS), Graduate, postdoctoral, Institute for Medical Engineering and Science (IMES), Laboratory for Information and Decision Systems (LIDS), Machine Learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Research, School of Engineering, Students

Adoption of new tools and technologies occurs when users largely perceive them as reliable, accessible, and an improvement over the available methods and workflows for the cost. Five PhD students from the inaugural class of the MIT-IBM Watson AI Lab Summer Program are utilizing state-of-the-art resources, alleviating AI pain points, and creating new features and

Charting the future of AI, from safer answers to faster thinking Read More »

Understanding the nuances of human-like intelligence

Artificial Intelligence, Brain and cognitive sciences, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical engineering and computer science (EECS), Faculty, Machine Learning, MIT Schwarzman College of Computing, Profile, School of Engineering

What can we learn about human intelligence by studying how machines “think?” Can we better understand ourselves if we better understand the artificial intelligence systems that are becoming a more significant part of our everyday lives?These questions may be deeply philosophical, but for Phillip Isola, finding the answers is as much about computation as it

Understanding the nuances of human-like intelligence Read More »

MIT Energy Initiative conference spotlights research priorities amidst a changing energy landscape

Artificial Intelligence, Batteries, Carbon dioxide, Chemistry, Cleaner industry, Climate change, Collaboration, DMSE, Electric grid, Energy, Energy storage, Faculty, government, infrastructure, Innovation and Entrepreneurship (I&E), Investments, Mechanical engineering, MIT Energy Initiative, Policy, Renewable energy, School of Engineering, School of Science, Special events and guest speakers, Startups, Students, Sustainability, The Engine, Transportation

“We’re here to talk about really substantive changes, and we want you to be a participant in that,” said Desirée Plata, the School of Engineering Distinguished Professor of Climate and Energy in MIT’s Department of Civil and Environmental Engineering, at Energizing@MIT: the MIT Energy Initiative’s (MITEI) Annual Research Conference that was held on Sept. 9-10.Plata’s

MIT Energy Initiative conference spotlights research priorities amidst a changing energy landscape Read More »

MIT Schwarzman College of Computing and MBZUAI launch international collaboration to shape the future of AI

Artificial Intelligence, Collaboration, Computer science and technology, Electrical engineering and computer science (EECS), Funding, International initiatives, MIT Schwarzman College of Computing, Research, School of Engineering, Technology and society

The MIT Schwarzman College of Computing and the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) recently celebrated the launch of the MIT–MBZUAI Collaborative Research Program, a new effort to strengthen the building blocks of artificial intelligence and accelerate its use in pressing scientific and societal challenges.Under the five-year agreement, faculty, students, and research staff

MIT Schwarzman College of Computing and MBZUAI launch international collaboration to shape the future of AI Read More »

Helping scientists run complex data analyses without writing code

Algorithms, Alumni/ae, Artificial Intelligence, Disease, Electrical engineering and computer science (EECS), Health, Innovation and Entrepreneurship (I&E), Machine Learning, Medicine, School of Engineering, Startups

As costs for diagnostic and sequencing technologies have plummeted in recent years, researchers have collected an unprecedented amount of data around disease and biology. Unfortunately, scientists hoping to go from data to new cures often require help from someone with experience in software engineering.Now, Watershed Bio is helping scientists and bioinformaticians run experiments and get

Helping scientists run complex data analyses without writing code Read More »

Checking the quality of materials just got easier with a new AI tool

Artificial Intelligence, Imaging, Light, Machine Learning, manufacturing, Materials science and engineering, Mechanical engineering, Research, School of Engineering

Manufacturing better batteries, faster electronics, and more effective pharmaceuticals depends on the discovery of new materials and the verification of their quality. Artificial intelligence is helping with the former, with tools that comb through catalogs of materials to quickly tag promising candidates.But once a material is made, verifying its quality still involves scanning it with

Checking the quality of materials just got easier with a new AI tool Read More »

Blending neuroscience, AI, and music to create mental health innovations

Artificial Intelligence, Brain and cognitive sciences, Graduate, postdoctoral, Media Lab, Mental health, MIT Schwarzman College of Computing, Music, Music and theater arts, Neuroscience, Profile, School of Architecture and Planning, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, Students, Undergraduate Research Opportunities Program (UROP)

Computational neuroscientist and singer/songwriter Kimaya (Kimy) Lecamwasam, who also plays electric bass and guitar, says music has been a core part of her life for as long as she can remember. She grew up in a musical family and played in bands all through high school.“For most of my life, writing and playing music was

Blending neuroscience, AI, and music to create mental health innovations Read More »