MIT Computer Science

• A leg up for STEM majors

  MIT undergraduates broaden their perspectives and prospects through political science.

• AI system predicts protein fragments that can bind to or inhibit a target

  FragFold, developed by MIT Biology researchers, is a computational method with potential for impact on biological research and therapeutic applications.

• Like human brains, large language models reason about diverse data in a general way

  A new study shows LLMs represent different data types based on their underlying meaning and reason about data in their dominant language.

• AI model deciphers the code in proteins that tells them where to go

  Whitehead Institute and CSAIL researchers created a machine-learning model to predict and generate protein localization, with implications for understanding and remedying disease.

• Gift from Sebastian Man ’79, SM ’80 supports MIT Stephen A. Schwarzman College of Computing building

  Alumnus is the first major donor to support the building since Stephen A. Schwarzman’s foundational gift.

• Bridging philosophy and AI to explore computing ethics

  In a new MIT course co-taught by EECS and philosophy professors, students tackle moral dilemmas of the digital age.

• To keep hardware safe, cut out the code’s clues

  New “Oreo” method from MIT CSAIL researchers removes footprints that reveal where code is stored before a hacker can see them.

• Puzzling out climate change

  Accenture Fellow Shreyaa Raghavan applies machine learning and optimization methods to explore ways to reduce transportation sector emissions.

• Can deep learning transform heart failure prevention?

  A deep neural network called CHAIS may soon replace invasive procedures like catheterization as the new gold standard for monitoring heart health.

• Creating a common language

  New faculty member Kaiming He discusses AI’s role in lowering barriers between scientific fields and fostering collaboration across scientific disciplines.

• Validation technique could help scientists make more accurate forecasts

  MIT researchers developed a new approach for assessing predictions with a spatial dimension, like forecasting weather or mapping air pollution.

• Eleven MIT faculty receive Presidential Early Career Awards

  Faculty members and additional MIT alumni are among 400 scientists and engineers recognized for outstanding leadership potential.

• Introducing the MIT Generative AI Impact Consortium

  The consortium will bring researchers and industry together to focus on impact.

• User-friendly system can help developers build more efficient simulations and AI models

  By automatically generating code that leverages two types of data redundancy, the system saves bandwidth, memory, and computation.

• With generative AI, MIT chemists quickly calculate 3D genomic structures

  A new approach, which takes minutes rather than days, predicts how a specific DNA sequence will arrange itself in the cell nucleus.

• 3 Questions: Modeling adversarial intelligence to exploit AI’s security vulnerabilities

  MIT CSAIL Principal Research Scientist Una-May O’Reilly discusses how she develops agents that reveal AI models’ security weaknesses before hackers do.

• New training approach could help AI agents perform better in uncertain conditions

  Sometimes, it might be better to train a robot in an environment that’s different from the one where it will be deployed.

• Toward video generative models of the molecular world

  Starting with a single frame in a simulation, a new system uses generative AI to emulate the dynamics of molecules, connecting static molecular structures and developing blurry pictures into videos.

• Explained: Generative AI’s environmental impact

  Rapid development and deployment of powerful generative AI models comes with environmental consequences, including increased electricity demand and water consumption.

• Algorithms and AI for a better world

  Assistant Professor Manish Raghavan wants computational techniques to help solve societal problems.

• Karl Berggren named faculty head of electrical engineering in EECS

  Professor who develops technologies to push the envelope of what is possible with photonics and electronic devices succeeds Joel Voldman.

• Fast control methods enable record-setting fidelity in superconducting qubit

  The advance holds the promise to reduce error-correction resource overhead.

• New computational chemistry techniques accelerate the prediction of molecules and materials

  With their recently-developed neural network architecture, MIT researchers can wring more information out of electronic structure calculations.

• Q&A: The climate impact of generative AI

  As the use of generative AI continues to grow, Lincoln Laboratory's Vijay Gadepally describes what researchers and consumers can do to help mitigate its environmental impact.

• Teaching AI to communicate sounds like humans do

  Inspired by the human vocal tract, a new AI model can produce and understand vocal imitations of everyday sounds. The method could help build new sonic interfaces for entertainment and education.

• Images that transform through heat

  The Thermochromorph printmaking technique developed by CSAIL researchers allows images to transition into each other through changes in temperature.

• Ecologists find computer vision models’ blind spots in retrieving wildlife images

  Biodiversity researchers tested vision systems on how well they could retrieve relevant nature images. More advanced models performed well on simple queries but struggled with more research-specific prompts.

• MIT affiliates receive 2025 IEEE honors

  Five MIT faculty and staff, along with 19 additional alumni, are honored for electrical engineering and computer science advances.

• Need a research hypothesis? Ask AI.

  MIT engineers developed AI frameworks to identify evidence-driven hypotheses that could advance biologically inspired materials.

• MIT researchers introduce Boltz-1, a fully open-source model for predicting biomolecular structures

  With models like AlphaFold3 limited to academic research, the team built an equivalent alternative, to encourage innovation more broadly.