<span class="vcard">Rachel Gordon | MIT CSAIL</span>
Rachel Gordon | MIT CSAIL
Algorithms Artificial Intelligence Brain and cognitive sciences Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical Engineering & Computer Science (eecs) Imaging machine learning Microscopy MIT Schwarzman College of Computing Nanoscience and nanotechnology Neurons Neuroscience Research School of Engineering Synapses

Using AI to optimize for rapid neural imaging

MIT CSAIL researchers combine AI and electron microscopy to expedite detailed brain network mapping, aiming to enhance connectomics research and clinical pathology.

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

AI copilot enhances human precision for safer aviation

Designed to ensure safer skies, “Air-Guardian” blends human intuition with machine precision, creating a more symbiotic relationship between pilot and aircraft.

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

AI copilot enhances human precision for safer aviation

Designed to ensure safer skies, “Air-Guardian” blends human intuition with machine precision, creating a more symbiotic relationship between pilot and aircraft.

Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Data Electrical Engineering & Computer Science (eecs) Laboratory for Nuclear Science machine learning MIT Schwarzman College of Computing Physics Research School of Engineering School of Science

From physics to generative AI: An AI model for advanced pattern generation

Inspired by physics, a new generative model PFGM++ outperforms diffusion models in image generation.

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

Multi-AI collaboration helps reasoning and factual accuracy in large language models

Researchers use multiple AI models to collaborate, debate, and improve their reasoning abilities to advance the performance of LLMs while increasing accountability and factual accuracy.

Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Defense Advanced Research Projects Agency (DARPA) Electrical Engineering & Computer Science (eecs) machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Research School of Engineering Technology and policy Technology and society

Using AI to protect against AI image manipulation

“PhotoGuard,” developed by MIT CSAIL researchers, prevents unauthorized image manipulation, safeguarding authenticity in the era of advanced generative models.

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

AI helps household robots cut planning time in half

PIGINet leverages machine learning to streamline and enhance household robots’ task and motion planning, by assessing and filtering feasible solutions in complex environments.

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

AI helps household robots cut planning time in half

PIGINet leverages machine learning to streamline and enhance household robots’ task and motion planning, by assessing and filtering feasible solutions in complex environments.

Algorithms Artificial Intelligence Biology Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology DNA Drug development Electrical Engineering & Computer Science (eecs) Jameel Clinic machine learning Medicine MIT Schwarzman College of Computing Pharmaceuticals Proteins Research School of Engineering

Generative AI imagines new protein structures

MIT researchers develop “FrameDiff,” a computational tool that uses generative AI to craft new protein structures, with the aim of accelerating drug development and improving gene therapy.

Artificial Intelligence Arts Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Electrical Engineering & Computer Science (eecs) machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Research School of Engineering School of Science

Computer vision system marries image recognition and generation

MAGE merges the two key tasks of image generation and recognition, typically trained separately, into a single system.