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Electrical engineering and computer science (EECS)
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MIT engineering students take on the heat of Miami
A collaboration between MIT and Miami-Dade County has students working with city planning officials to understand why people wait patiently for a bus — and why they bail.
MIT-Pillar AI Collective announces first seed grant recipients
Six teams conducting research in AI, data science, and machine learning receive funding for projects that have potential commercial applications.
MIT PhD student enhances STEM education in underrepresented communities in Puerto Rico
Through her organization, Sprouting, Taylor Baum is empowering teachers to teach coding and computer science in their classrooms and communities.
Six with MIT ties win 2023 Hertz Foundation Fellowships
Award recognizes scholars who have the “extraordinary creativity necessary to tackle problems others can’t solve.”
Atlas of human brain blood vessels highlights changes in Alzheimer’s disease
MIT researchers characterize gene expression patterns for 22,500 brain vascular cells across 428 donors, revealing insights for Alzheimer’s onset and potential treatments.
Envisioning the future of computing
MIT students share ideas, aspirations, and vision for how advances in computing stand to transform society in a competition hosted by the Social and Ethical Responsibilities of Computing.
Novo Nordisk to support MIT postdocs working at the intersection of AI and life sciences
MIT-Novo Nordisk Artificial Intelligence Postdoctoral Fellows Program will support up to 10 postdocs annually over five years.
Bringing the social and ethical responsibilities of computing to the forefront
The inaugural SERC Symposium convened experts from multiple disciplines to explore the challenges and opportunities that arise with the broad applicability of computing in many aspects of society.
New model offers a way to speed up drug discovery
By applying a language model to protein-drug interactions, researchers can quickly screen large libraries of potential drug compounds.
MIT researchers make language models scalable self-learners
The scientists used a natural language-based logical inference dataset to create smaller language models that outperformed much larger counterparts.
Meet the tight-knit technical staff who help MIT.nano handle any challenge
All together, a core group of MIT.nano staffers has more than 400 years of technical experience in nanoscale characterization and fabrication.
Scaling audio-visual learning without labels
A new multimodal technique blends major self-supervised learning methods to learn more similarly to humans.
New tool helps people choose the right method for evaluating AI models
Selecting the right method gives users a more accurate picture of how their model is behaving, so they are better equipped to correctly interpret its predictions.
A more effective way to train machines for uncertain, real-world situations
Researchers develop an algorithm that decides when a “student” machine should follow its teacher, and when it should learn on its own.