Computing Research Virtual Policy Town Hall on Research Security
CRA’s Virtual Policy Town Hall on research security, with guest speaker Rebbecca Keiser, Chief of Research Security Strategy and Policy at NSF.
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Tag Archive: Webinar
CRA-Industry Virtual Roundtable on Best Practices on Using the Cloud for Computing Research
A major focus in computing research across industry, academia, and government is to advance the frontiers of computing by experimenting with leading-edge compute platforms. This was initially at odds with early instances of cloud/warehouse computing that focused on deploying commodity rather than state-of-the-art systems. However, cloud computing platforms have advanced significantly during the last two decades to the point where there are now many notable examples of their use in research. Further, the cloud’s “pay as you go” model has proved attractive for research related to machine learning and data analytics that benefit from elastic provisioning of resources. It is noteworthy that NSF has extended its CloudBank portal with a CloudBank Catalog with links to commercial cloud services that can be paid from NSF grants. Hence, increased use of the cloud for computing research could offer new revenue opportunities to cloud providers, in addition to joint research across industry and academia. There will also likely be a crossover from the use of cloud computing for research to its use in teaching, thereby making future generations of computing professionals more accustomed to cloud platforms.
CRA Industry Roundtable: Corporate Responsibility and Computing Research
Today, more companies are deliberately extending their social responsibility initiatives at the behest of investors, customers, and employees. How should industry be viewing and factoring societal equity into its research agendas? This roundtable will explore the concept, principles, and best practices of socially responsible computing research. Ideally, participants will gain a sense of considerations that might apply to their strategic research planning by developing a broad framework for the concept of research equity that goes beyond recent examples in machine learning.
