Download RSS feed: News Articles / In the Media / Audio
With the selection of 16 inaugural postdocs, the program seeks to develop the next generation of faculty leaders and help guide the school toward a more diverse and inclusive culture.
Award recognizes Shin’s contributions at Lincoln Laboratory to air vehicle survivability and STEM education in support of national defense.
The new fellowship from the governments of Australia, India, Japan, and the United States, administered by Schmidt Futures, supports graduate education in STEM fields.
Rachel Chae and Sihao Huang ’22 will pursue graduate studies in the United Kingdom.
This year's fellows will work across research areas including telemonitoring, human-computer interactions, operations research, AI-mediated socialization, and chemical transformations.
This computational tool can generate an optimal design for a complex fluidic device such as a combustion engine or a hydraulic pump.
Researchers develop a scalable fabrication technique to produce ultrathin, lightweight solar cells that can be seamlessly added to any surface.
MIT-trained electrical engineer Jorg Scholvin guides researchers fabricating new technology at MIT.nano.
Sara V. Fernandez, Amanda Hu, and Brigette Wang will spend the 2023-24 academic year at Tsinghua University in China studying global affairs.
A new algorithm for automatic assembly of products is accurate, efficient, and generalizable to a wide range of complex real-world assemblies.
New research enables users to search for information without revealing their queries, based on a method that is 30 times faster than comparable prior techniques.
Researchers used a powerful deep-learning model to extract important data from electronic health records that could assist with personalized medicine.
Dan Huttenlocher is a professor of electrical engineering and computer science and the inaugural dean at MIT Schwarzman College of Computing.
New technique significantly reduces training and inference time on extensive datasets to keep pace with fast-moving data in finance, social networks, and fraud detection in cryptocurrency.
New technique could diminish errors that hamper the performance of super-fast analog optical neural networks.