Electrical engineering and computer science (EECS)

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New materials could boost the energy efficiency of microelectronics

Artificial Intelligence, Computer chips, Computer science and technology, Electrical engineering and computer science (EECS), Electronics, Energy, Materials science and engineering, Microsystems Technology Laboratories, MIT Schwarzman College of Computing, MIT.nano, Nanoscience and nanotechnology, Research, School of Engineering, Sustainable computing

MIT researchers have developed a new fabrication method that could enable the production of more energy efficient electronics by stacking multiple functional components on top of one existing circuit.In traditional circuits, logic devices that perform computation, like transistors, and memory devices that store data are built as separate components, forcing data to travel back and […]

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MIT affiliates named 2025 Schmidt Sciences AI2050 Fellows

Algorithms, Artificial Intelligence, Awards, honors and fellowships, Economics, Electrical engineering and computer science (EECS), Faculty, Graduate, postdoctoral, MIT Schwarzman College of Computing, Research Laboratory of Electronics, School of Engineering, School of Humanities Arts and Social Sciences, Staff

Two current MIT affiliates and seven additional alumni are among those named to the 2025 cohort of AI2050 Fellows.  Zongyi Li, a postdoc in the MIT Computer Science and Artificial Intelligence Lab, and Tess Smidt ’12, an associate professor of electrical engineering and computer science (EECS), were both named as AI2050 Early Career Fellows. Seven additional MIT

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MIT researchers “speak objects into existence” using AI and robotics

Architecture, Artificial Intelligence, Center for Bits and Atoms, Computer science and technology, Design, Electrical engineering and computer science (EECS), Fabrication, Human-computer interaction, Mechanical engineering, MIT Morningside Academy for Design, MIT Schwarzman College of Computing, Natural Language Processing, Research, Robotics, School of Architecture and Planning, School of Engineering

Generative AI and robotics are moving us ever closer to the day when we can ask for an object and have it created within a few minutes. In fact, MIT researchers have developed a speech-to-reality system, an AI-driven workflow that allows them to provide input to a robotic arm and “speak objects into existence,” creating

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Robots that spare warehouse workers the heavy lifting

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

There are some jobs human bodies just weren’t meant to do. Unloading trucks and shipping containers is a repetitive, grueling task — and a big reason warehouse injury rates are more than twice the national average.The Pickle Robot Company wants its machines to do the heavy lifting. The company’s one-armed robots autonomously unload trailers, picking

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A smarter way for large language models to think about hard problems

Algorithms, Artificial Intelligence, Computer science and technology, Electrical engineering and computer science (EECS), IDSS, Laboratory for Information and Decision Systems (LIDS), Machine Learning, Mechanical engineering, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Research, School of Engineering

To make large language models (LLMs) more accurate when answering harder questions, researchers can let the model spend more time thinking about potential solutions.But common approaches that give LLMs this capability set a fixed computational budget for every problem, regardless of how complex it is. This means the LLM might waste computational resources on simpler questions

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MIT engineers design an aerial microrobot that can fly as fast as a bumblebee

Aeronautical and astronautical engineering, Artificial Intelligence, Bioinspiration, Drones, Electrical engineering and computer science (EECS), Electronics, Laboratory for Information and Decision Systems (LIDS), Machine Learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, Research Laboratory of Electronics, Robotics, School of Engineering

In the future, tiny flying robots could be deployed to aid in the search for survivors trapped beneath the rubble after a devastating earthquake. Like real insects, these robots could flit through tight spaces larger robots can’t reach, while simultaneously dodging stationary obstacles and pieces of falling rubble.So far, aerial microrobots have only been able

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New control system teaches soft robots the art of staying safe

Artificial Intelligence, Civil and environmental engineering, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical engineering and computer science (EECS), IDSS, Laboratory for Information and Decision Systems (LIDS), Machine Learning, Mechanical engineering, MIT Schwarzman College of Computing, Research, Robotics, Safety, School of Engineering

Imagine having a continuum soft robotic arm bend around a bunch of grapes or broccoli, adjusting its grip in real time as it lifts the object. Unlike traditional rigid robots that generally aim to avoid contact with the environment as much as possible and stay far away from humans for safety reasons, this arm senses

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MIT scientists debut a generative AI model that could create molecules addressing hard-to-treat diseases

Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Drug development, Electrical engineering and computer science (EECS), Health sciences and technology, Jameel Clinic, Machine Learning, Medicine, MIT Schwarzman College of Computing, Pharmaceuticals, Proteins, Research, School of Engineering, Special events and guest speakers

More than 300 people across academia and industry spilled into an auditorium to attend a BoltzGen seminar on Thursday, Oct. 30, hosted by the Abdul Latif Jameel Clinic for Machine Learning in Health (MIT Jameel Clinic). Headlining the event was MIT PhD student and BoltzGen’s first author Hannes Stärk, who had announced BoltzGen just a few days

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Researchers discover a shortcoming that makes LLMs less reliable

Artificial Intelligence, Computer science and technology, data, Electrical engineering and computer science (EECS), Human-computer interaction, Institute for Medical Engineering and Science (IMES), Laboratory for Information and Decision Systems (LIDS), Machine Learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, School of Engineering, Technology and society

Large language models (LLMs) sometimes learn the wrong lessons, according to an MIT study.Rather than answering a query based on domain knowledge, an LLM could respond by leveraging grammatical patterns it learned during training. This can cause a model to fail unexpectedly when deployed on new tasks.The researchers found that models can mistakenly link certain

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Five with MIT ties elected to National Academy of Medicine for 2025

Alumni/ae, Artificial Intelligence, Awards, honors and fellowships, Biology, Computer Science and Artificial Intelligence Laboratory (CSAIL), Disease, Electrical engineering and computer science (EECS), Faculty, Harvard-MIT Health Sciences and Technology, Health care, Health sciences and technology, Koch Institute, Mechanical engineering, MIT Schwarzman College of Computing, Physics, Ragon Institute, School of Engineering, School of Science, Vaccines, Wireless

On Oct. 20 during its annual meeting, the National Academy of Medicine announced the election of 100 new members, including MIT faculty members Dina Katabi and Facundo Batista, along with three additional MIT alumni.Election to the National Academy of Medicine (NAM) is considered one of the highest honors in the fields of health and medicine,

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