A dispatch and routing platform to improve deliveries
Wise Systems has grown from an MIT class project to a company helping multinationals improve last-mile logistics.
Wise Systems has grown from an MIT class project to a company helping multinationals improve last-mile logistics.
With a double major in linguistics and computer science, senior Rujul Gandhi works to surmount language and cultural barriers, globally and on campus.
A deep model was trained on historical crash data, road maps, satellite imagery, and GPS to enable high-resolution crash maps that could lead to safer roads.
Researchers find blind and sighted readers have sharply different takes on what content is most useful to include in a chart caption.
Secure AI Labs, founded by alumna Anne Kim and MIT Professor Manolis Kellis, anonymizes data for AI researchers.
Researchers hope more user-friendly machine-learning systems will enable nonexperts to analyze big data — but can such systems ever be completely autonomous?
This robotic arm fuses data from a camera and antenna to locate and retrieve items, even if they are buried under a pile.
Current and former MIT researchers find novel tools can improve the sustainability of road networks on a limited budget.
Scientists employ an underused resource — radiology reports that accompany medical images — to improve the interpretive abilities of machine learning algorithms.
Neural network identifies synergistic drug blends for treating viruses like SARS-CoV-2.
An AI-enhanced system enables doctors to spend less time searching for clinical information and more time treating patients.
FLC Excellence in Technology Transfer Award recognizes two innovations that have transitioned to commercial use.
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.
Obiageli Nwodoh ’21 repurposed her STEM skills to pave a pre-law path at MIT and pursue social justice.
MIT researchers find a new way to quantify the uncertainty in molecular energies predicted by neural networks.