AI and machine learning for engineering design
Popular mechanical engineering course applies machine learning and AI theory to real-world engineering design.
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Students
Exploring data and its influence on political behavior
In MIT’s course 17.831 (Data and Politics), students are introduced to the power of analysis, visualization, and research-supported insight into political outcomes.
Read MoreCombining technology, education, and human connection to improve online learning
Caitlin Morris, a PhD student and 2024 MAD Fellow affiliated with the MIT Media Lab, designs digital learning platforms that make room for the “social magic” that influences curiosity and motivation.
Read MoreA sounding board for strengthening the student experience
Composed of “computing bilinguals,” the Undergraduate Advisory Group provides vital input to help advance the mission of the MIT Schwarzman College of Computing.
Read MoreBringing meaning into technology deployment
The MIT Ethics of Computing Research Symposium showcases projects at the intersection of technology, ethics, and social responsibility.
Read MoreEnvisioning a future where health care tech leaves some behind
The winning essay of the Envisioning the Future of Computing Prize puts health care disparities at the forefront.
Read MoreAn anomaly detection framework anyone can use
PhD student Sarah Alnegheimish wants to make machine learning systems accessible.
Read MoreMerging design and computer science in creative ways
MAD Fellow Alexander Htet Kyaw connects humans, machines, and the physical world using AI and augmented reality.
Read MoreU.S. Air Force engineer and PhD student Randall Pietersen is using AI and next-generation imaging technology to detect pavement damage and unexploded munitions.
Read MorePuzzling out climate change
Accenture Fellow Shreyaa Raghavan applies machine learning and optimization methods to explore ways to reduce transportation sector emissions.
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