Translating MIT research into real-world results
MIT’s innovation and entrepreneurship system helps launch water, food, and ag startups with social and economic benefits.
MIT’s innovation and entrepreneurship system helps launch water, food, and ag startups with social and economic benefits.
MIT spinout SiTration looks to disrupt industries with a revolutionary process for recovering and extracting critical materials.
A catalyst tethered by DNA boosts the efficiency of the electrochemical conversion of CO2 to CO, a building block for many chemical compounds.
Leon Sandler reflects on 18 years of helping MIT faculty make their research have real-world impact.
The graduate students will aim to commercialize innovations in AI, machine learning, and data science.
The graduate students will aim to commercialize innovations in AI, machine learning, and data science.
MIT and MGH researchers design a local, gel-based drug-delivery platform that may provoke a system-wide immune response to metastatic tumors.
New coating protects nitrogen-fixing bacteria from heat and humidity, which could allow them to be deployed for large-scale agricultural use.
James Fujimoto, Eric Swanson, and David Huang are recognized for their technique to rapidly detect diseases of the eye; Subra Suresh is honored for his commitment to research and collaboration across borders.
MIT spinout Kronos Bio, founded by Associate Professor Angela Koehler, studies the complex signaling networks of cancer cells to find new drug targets.
Professor and two additional MIT affiliates honored for influential work on optical coherence tomography, which allows rapid detection of retinal disease, among other applications.
Center for International Studies Global Seed Funds program fosters collaboration and innovation.
A biotech entrepreneur, Koehler will help faculty and students launch startups and bring new products to market through the MIT Deshpande Center for Technological Innovation.
Six teams conducting research in AI, data science, and machine learning receive funding for projects that have potential commercial applications.
Researchers used a powerful deep-learning model to extract important data from electronic health records that could assist with personalized medicine.