MIT Computer Science

• The brain power behind sustainable AI

  PhD student Miranda Schwacke explores how computing inspired by the human brain can fuel energy-efficient artificial intelligence.

• Charts can be social artifacts that communicate more than just data

  Researchers find that design elements of data visualizations influence viewers’ assumptions about the source of the information and its trustworthiness.

• Creating AI that matters

  How the MIT-IBM Watson AI Lab is shaping AI-sociotechnical systems for the future.

• Solar energy startup Active Surfaces wins inaugural PITCH.nano competition

  Twelve START.nano companies competed for the grand prize of nanoBucks to be used at MIT.nano’s facilities.

• New software designs eco-friendly clothing that can reassemble into new items

  To reduce waste, the Refashion program helps users create outlines for adaptable clothing, such as pants that can be reconfigured into a dress. Each component of these pieces can be replaced, rearranged, or restyled.

• Method teaches generative AI models to locate personalized objects

  After being trained with this technique, vision-language models can better identify a unique item in a new scene.

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

  The MIT–MBZUAI Collaborative Research Program will unite faculty and students from both institutions to advance AI and accelerate its use in pressing scientific and societal challenges.

• Using generative AI to diversify virtual training grounds for robots

  New tool from MIT CSAIL creates realistic virtual kitchens and living rooms where simulated robots can interact with models of real-world objects, scaling up training data for robot foundation models.

• Laurent Demanet appointed co-director of MIT Center for Computational Science and Engineering

  Applied mathematics professor will join fellow co-director Nicolas Hadjiconstantinou in leading the cross-cutting center.

• Fighting for the health of the planet with AI

  Assistant Professor Priya Donti’s research applies machine learning to optimize renewable energy.

• AI maps how a new antibiotic targets gut bacteria

  MIT CSAIL and McMaster researchers used a generative AI model to reveal how a narrow-spectrum antibiotic attacks disease-causing bacteria, speeding up a process that normally takes years.

• System lets people personalize online social spaces while staying connected with others

  By enabling users to easily create social apps that serve communities’ needs, the Graffiti framework aims to promote healthier online interactions.

• Responding to the climate impact of generative AI

  Explosive growth of AI data centers is expected to increase greenhouse gas emissions. Researchers are now seeking solutions to reduce these environmental harms.

• New AI system could accelerate clinical research

  By enabling rapid annotation of areas of interest in medical images, the tool can help scientists study new treatments or map disease progression.

• MIT engineers develop a magnetic transistor for more energy-efficient electronics

  A new device concept opens the door to compact, high-performance transistors with built-in memory.

• MIT named No. 2 university by U.S. News for 2025-26

  Undergraduate engineering, computer science, and business programs are all No. 1.

• MIT affiliates win AI for Math grants to accelerate mathematical discovery

  Department of Mathematics researchers David Roe and Andrew Sutherland seek to advance automated theorem proving; four additional MIT alumni also awarded.

• What does the future hold for generative AI?

  At the inaugural MIT Generative AI Impact Consortium Symposium, researchers and business leaders discussed potential advancements centered on this powerful technology.

• A new community for computational science and engineering

  The stand-alone PhD program is building connections and preparing students to make a difference.

• How to build AI scaling laws for efficient LLM training and budget maximization

  MIT-IBM Watson AI Lab researchers have developed a universal guide for estimating how large language models will perform based on smaller models in the same family.

• Machine-learning tool gives doctors a more detailed 3D picture of fetal health

  MIT CSAIL researchers developed a tool that can model the shape and movements of fetuses in 3D, potentially assisting doctors in finding abnormalities and making diagnoses.

• MIT software tool turns everyday objects into animated, eye-catching displays

  The FabObscura system helps users design and print barrier-grid animations without electronics, and can help produce dynamic household, workplace, and artistic objects.

• DOE selects MIT to establish a Center for the Exascale Simulation of Coupled High-Enthalpy Fluid–Solid Interactions

  The research center, sponsored by the DOE’s National Nuclear Security Administration, will advance the simulation of extreme environments, such as those in hypersonic flight and atmospheric reentry.

• Lincoln Laboratory technologies win seven R&D 100 Awards for 2025

  Inventions that protect US service members, advance computing, and enhance communications are recognized among the year's most significant new products.

• A human-centered approach to data visualization

  Balancing automation and agency, Associate Professor Arvind Satyanarayan develops interactive data visualizations that amplify human creativity and cognition.

• A greener way to 3D print stronger stuff

  MIT CSAIL researchers developed SustainaPrint, a system that reinforces only the weakest zones of eco-friendly 3D prints, achieving strong results with less plastic.

• A new generative AI approach to predicting chemical reactions

  System developed at MIT could provide realistic predictions for a wide variety of reactions, while maintaining real-world physical constraints.

• 3 Questions: The pros and cons of synthetic data in AI

  Artificially created data offer benefits from cost savings to privacy preservation, but their limitations require careful planning and evaluation, Kalyan Veeramachaneni says.

• MIT researchers develop AI tool to improve flu vaccine strain selection

  VaxSeer uses machine learning to predict virus evolution and antigenicity, aiming to make vaccine selection more accurate and less reliant on guesswork.

• Learning from punishment

  A new computational model makes sense of the cognitive processes humans use to evaluate punishment.