Budding coders create apps aimed at real-world impact
MIT App Inventor’s “Appathon” joins programmers from around the world to imagine a better future and start building it one app at a time.
MIT App Inventor’s “Appathon” joins programmers from around the world to imagine a better future and start building it one app at a time.
Preparing for a career advancing the science and policy of climate issues, junior Ryan Conti focuses on math, computer science, and the philosophy of language.
Scientists employ an underused resource — radiology reports that accompany medical images — to improve the interpretive abilities of machine learning algorithms.
An electrical impedance tomography toolkit lets users design and fabricate health and motion sensing devices.
MIT scientists show how fast algorithms are improving across a broad range of examples, demonstrating their critical importance in advancing computing.
New property in an ultrathin cousin of graphene could allow for much denser computer memory.
Undergraduate engineering and computer science programs are No. 1; undergraduate business program is No. 2.
MIT professor is designing the next generation of smart wireless devices that will sit in the background, gathering and interpreting data, rather than being worn on the body.
A former department head who established the MEng degree for EECS undergraduates, Penfield developed courses illuminating the equivalence of information and thermodynamic entropy.
Obiageli Nwodoh ’21 repurposed her STEM skills to pave a pre-law path at MIT and pursue social justice.
ARROW, a reconfigurable fiber optics network developed at MIT, aims to take on the end of Moore’s law.
Competing research teams trained machine learning models to predict optimal routing based on real field datasets.
SensiCut, a smart material-sensing platform for laser cutters, can differentiate between 30 materials commonly found in makerspaces and workshops.
PhD student Rodrigo Ochigame designs alternative search engines and seeks to disrupt cultural assumptions in their teaching and research.
MIT researchers employ machine learning to find powerful peptides that could improve a gene therapy drug for Duchenne muscular dystrophy.