The San Diego Supercomputer Center at UC San Diego has planned summer institutes for June and August, one focused on cyberinfrastructure-enabled machine learning and the on high-performance computing (HPC) and data science. Application deadlines are April 15 and May 13, respectively. The Cyberinfrastructure-Enabled Machine Learning (CIML) Summer Institute will be held June 27-29 (with a preparatory session on June 22). The institute will introduce machine learning (ML) researchers, developers and educators to the techniques and methods needed to migrate their ML applications from smaller, locally run resources (such as laptops and workstations) to high-performance computing (HPC) systems (e.g., SDSC's Expanse supercomputer). The CIML application deadline is Friday, April 15.

For the past decade in Los Angeles and the State of California, the question is not if there will be wildfires--but rather when and where they will sprout up and how to protect people from these threats. As such, firefighters need to know how to plan and deploy limited resources. One such solution is controlled burns of flammable brush to prevent worst-case scenarios of growing tinder that left unattended, provides fodder for megafires. With $5 million in support from the National Science Foundation's Convergence Accelerator program, a team of researchers, which includes UC San Diego's San Diego Supercomputer Center (SDSC), the University of Southern California's Viterbi School of Engineering and the Tall Timbers Research Station in Florida, will bring the power of AI to help firefighters strategize how best to plan these controlled burns, as well as manage unexpected blazes. SDSC will lead the effort through the development of "BurnPro3D," a new decision support platform to help the fire response and mitigation community quickly and accurately understand risks and tradeoffs presented by a fire to more effectively plan controlled burns and manage wildfires.

The Federal Statistical Office (FSO) is joining forces with the Swiss Data Science Center, a joint venture between the two federal institutes of technology, to encourage the use of data science and artificial intelligence within the administration. As society becomes more digitalized, institutions need more and more data science skills. This includes the integration of tools arising from artificial intelligence in a way that is safe and beneficial to society as a whole. To this end, as a pioneer within the federal administration, the FSO is teaming up with the Swiss Data Science Center (SDSC), a joint venture between the two federal institutes of technology. "I am extremely enthusiastic about this strategic partnership in a joint flagship project between our two institutes and the FSO," said Martin Vetterli, President of the EPFL.

For more than four decades, UC San Diego Professor of Physics Patrick H. Diamond and his research group have been advancing fundamental concepts in plasma physics, which is an important aspect of furthering advancements in fusion energy. Most recently, Diamond worked with graduate student Robin Heinonen on a model reduction study that used the Comet supercomputer at the San Diego Supercomputer Center at the University of California San Diego to showcase how machine learning produced a novel model for plasma turbulence. Diamond and Heinonen say that advances in machine learning, such as new deep learning techniques, have provided them with new tools to better understand the self-organization process that emerges from what the researchers term as a seemingly chaotic process. "Turbulence and its transport is chaotic in a sense, but this chaos is ordered and constrained," said Heinonen, who co-authored Turbulence Model Reduction by Deep Learning with Diamond in the academic journal entitled Physical Review E. "Moreover, in certain turbulent systems, the chaos conspires to spontaneously form large, long-lived coherent structures and in many cases, we only have a tenuous understanding of why and now. There are definitely aspects of structure formation and self-organization which we do understand, but it's still an active area of research."

Researchers at the San Diego Supercomputer Center at UC San Diego and UC San Diego School of Medicine have received two National Science Foundation (NSF) planning grants worth a combined $2 million under a new NSF initiative to invest in research collaborations between academia, industry, government and communities that enable capabilities beyond what is currently possible in either the private or public sectors. Called Convergence Accelerator awards, the first set of grants has been awarded to research teams, according to a recent NSF release. These projects will evaluate how employers can use sophisticated artificial intelligence tools to connect with the workers they need, while seeking ways to develop the future U.S. workforce with the universities that will educate people and the companies that will employ them. A total of 43 new awards totaling $39 million will support projects across the country. Both grants, which support one of NSF's'Big Ideas' called Harnessing the Data Revolution, are focused on the area of Open Knowledge Networks, which pool many types of information and ideas so they can be accessed and leveraged to create new understanding.