| Announcement: NSF announces 2020 Computing Innovation Fellows Program |
| 07/07/2020 |
 |
ANNOUNCEMENT
|
|
While current wireless networks support cellular and Wi-Fi services, future networks will need to support a much broader range of technologies, from driverless cars to remote health applications. The existing wireless spectrum is already over-congested, thanks to the explosion of network-connected devices that help people navigate their daily lives. As demand for capacity and coverage increases, expanding wireless spectrum is even more critical. Machine learning has emerged as a technique to potentially manage that growing complexity and scale while also improving the quality of service.
"The wireless networks of the future need to support much higher requirements than what current wireless networks can deliver, and they also need to be secure and energy-efficient," said Margaret Martonosi, assistant director for Computer and Information Science and Engineering. "That is why NSF and Intel have contributed $9 million to advance research activities addressing some of the most challenging issues in the development of future wireless systems."
This investment supports research to accelerate innovation and grows the number of workforce-ready STEM graduates. This fundamental, broad-based research on wireless-specific machine learning techniques enables new wireless architectures and systems for future applications.
"Since 2015, Intel and NSF have collectively contributed more than $30 million to support science and engineering research in emerging areas of technology. This program is the next step in this collaboration and has the promise to enable future wireless systems that serve the world's rising demand for pervasive, intelligent devices."
More information about the program can be found on here. A full list of award winners and project descriptions can be found here.
|
|
 |
| Announcement: NSF advances materials research and innovation with new centers |
|
Our lives, comfort, and well-being have come to depend on the development of new materials for everything ranging from smart electronics to implantable medical devices. The U.S. National Science Foundation fosters collaboration and innovation among universities, national laboratories, industry, and international scientific organizations through its Materials Research Science and Engineering Centers. These centers work to address critical challenges in material science such as extreme miniaturization, self-folding atomically thin "paper" materials, on-demand assembly of nanoparticles, materials behavior under extreme conditions, and the quantum revolution.
"Materials are enablers of technologies that directly affect people's lives," says Dr. Linda Sapochak, director of the Division of Materials Research. "This week, we announce an investment of $198 million to fund 11 Materials Research Science and Engineering Centers to forge new discoveries and fuel new technologies."
NSF is establishing three new centers and an additional eight successfully recompeted for funding this year in emerging fields such as quantum materials and synthetic biology.
The new centers include:
The existing centers include:
These centers create opportunities that extend well beyond the fundamental science they pursue by contributing to the education and development of a future science and engineering workforce. Together, these facilities comprise a diverse network of instrumentation that broadly spans current materials research needs in academic, government, and industrial laboratories around the world.
Results from materials research at the centers are poised to have ripple effects across the scientific community and industry. Future developments in sectors like biotechnology, energy and computing, and even ceramics and everyday plastics and foams will benefit from the practical application of cutting-edge materials research.
|
|
 |
| Announcement: Machine learning research to advance future wireless networks |
| 07/07/2020 |
|
While current wireless networks support cellular and Wi-Fi services, future networks will need to support a much broader range of technologies, from driverless cars to remote health applications. The existing wireless spectrum is already over-congested, thanks to the explosion of network-connected devices that help people navigate their daily lives. As demand for capacity and coverage increases, expanding wireless spectrum is even more critical. Machine learning has emerged as a technique to potentially manage that growing complexity and scale while also improving the quality of service.
"The wireless networks of the future need to support much higher requirements than what current wireless networks can deliver, and they also need to be secure and energy-efficient," said Margaret Martonosi, assistant director for Computer and Information Science and Engineering. "That is why NSF and Intel have contributed $9 million to advance research activities addressing some of the most challenging issues in the development of future wireless systems."
This investment supports research to accelerate innovation and grows the number of workforce-ready STEM graduates. This fundamental, broad-based research on wireless-specific machine learning techniques enables new wireless architectures and systems for future applications.
"Since 2015, Intel and NSF have collectively contributed more than $30 million to support science and engineering research in emerging areas of technology. This program is the next step in this collaboration and has the promise to enable future wireless systems that serve the world's rising demand for pervasive, intelligent devices."
More information about the program can be found on here. A full list of award winners and project descriptions can be found here.
|
|
 |
| Announcement: NSF addresses chemical research challenges through Centers for Chemical Innovation |
|
Solutions to challenges in chemical research could transform advanced manufacturing, clean energy, quantum computing and biotechnology. The U.S. National Science Foundation is advancing research at Centers for Chemical Innovation in areas such as materials chemistry, synthesized polymers and sustainable plastics, to name a few.
NSF is investing $60 million in Centers for Chemical Innovation to expand their research and education goals. David Berkowitz, director of the Division of Chemistry, stated, "These centers are transforming the way we do science by engaging highly interdisciplinary, multi-institutional teams to take on grand challenges in the field. If successful, they will generate truly disruptive technologies in the future."
- Center for Synthetic Organic Electrochemistry anchored at University of Utah addresses advanced manufacturing. The nine research partners explore applications for novel electrochemical reactions in organic synthesis and materials chemistry. Improved conditions and efficiency for such reactions benefit researchers in academia, the pharmaceutical industry, personal care products and fine chemicals manufacturing.
- Center for Genetically Encoded Materials led by University of California, Berkeley, works at the intersection of chemistry, biology and materials science. With six partners at other universities and a research hospital, their goal is to synthesize polymers inspired by nature's construction machinery -- the ribosome. Newly designed polymers and properties open new opportunities in information storage, sensor development, drug discovery and even textiles.
- Center for Sustainable Nanotechnology at University of Wisconsin-Madison, is being renewed. The center's 13 institutional partners focus on characterizing nanomaterials with applications from improved batteries and electronics to targeted medicines.
Another three centers complete the cohort, tackling topics such as advanced catalytic and synthetic chemistry, aerosols in the environment, and sustainable plastics.
Collectively, NSF is supporting more than 150 researchers, postdocs and students at research universities, primarily undergraduate institutions, minority-serving institutions, nonprofit research organizations and a federal lab.
|
|
|
|
|