NSF Award Announced for the CIML Project!
NSF Award Ah2stract #2017767
CyberTraining: Implementation: Small: Developing a Best Practices Training Program in Cyberinfrastructure-Enabled Machine Learning Research
See: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2017767&HistoricalAwards=false
The Cyberinfrastructure-enabled Machine Learning (CIML) training system will use a “best practices” approach to develop a unique program targeted towards the NSF workforce who use machine learning (ML) and big data analytics methods for their domain specific applications or instructional material on large-scale NSF funded cyberinfrastructure. We will apply methods of Cyber Literacy and HPC Competencies to define a set of core ML and domain specific literacy areas as a function of the dimensions of learning ranging from a technological focus to a problem-solving focus or a focus on ML or computational science. Sources for the CIML system will be drawn from the work of HPC training, existing HPC researchers and users, collaborators, as well as new code and methods. CIMIL efforts will be focussed on 2 communities: (1) users who want to understand what technologies and skills they need to master in order to run a particular ML application, what systems to use, and suggested software libraries; and (2) trainers who need to know what topics to teach.
The outcome of our efforts will result in a community of machine learning and data analytics CI Users (CIUs) and Contributors (CICs) who actively contribute to the training material repository and incorporate the materials into their projects and courses. The results of our efforts support both goals of the solicitation by ensuring that the CI modules run on advanced CI tools and resources (goal #1: “Broadening Adoption of Advanced CI,”), and that core literacy and discipline-appropriate advanced skills in advanced CI will be integrated into curriculum/instructional material (goal #2: “Integration of CI Skills into Curriculum/Instructional Material Fabric”). As a result of our efforts, the CIML program will extend the scope of the ongoing education and training across the NSF research workforce by developing cyberinfrastructure-based materials that will utilize and contribute to training material developed for XSEDE training, higher education, and other programs, and will impact thousands of existing and new users, including students (undergrads/grads), postdocs, PIs, researchers, and educators, each with their own diverse backgrounds and application requirements. CIML training material will be available online, so the project has an unlimited potential to reach beyond the NSF cyber workforce and to impact other communities including hospital and medical treatment systems, transportation and electrical monitoring systems, stock and market monitoring systems, and disaster response systems.