Q&A: Dina Katabi on a “smart” home with actual intelligence
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.
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.
Probabilistic programming language allows for fast, error-free answers to hard AI problems, including fairness.
Two research projects on the design of state-of-the-art hardware could one day power next-generation 5G and 6G mobile networks.
Advancing the study and practice of thinking responsibly in computing education, research, and implementation.
Longtime faculty member was a pioneer in developing the computer programming systems used in structural design.
Originally developed at MIT Lincoln Laboratory, the technology allows organizations to ensure the security of sensitive data stored in the cloud.
Researchers share progress applying network science to disinformation tracing, Covid-19 modeling, and machine learning.
A novel method to represent robotic manipulators helps optimize complex and organic shapes for future machines.