Keeping Data Science Broad: Negotiating the Digital and Data Divide Among Higher Education Institutions

The goal of the “Keeping Data Science Broad” series of webinars and workshops was to garner community input into pathways for keeping data science education broadly inclusive across sectors, institutions, and populations. Input was collected from data science programs across the nation, either traditional or alternative, and from a range of institution types including community colleges, minority-led and minority-serving institutions, liberal arts colleges, tribal colleges, universities, and industry partners. The series consisted of two webinars (August 2017 and September 2017) leading up to a workshop (November 2017) exploring the future of data science education and workforce at institutions of higher learning that are primarily teaching-focused. A third follow-up webinar was held after the workshop (January 2018) to report on outcomes and next steps. Program committee members were chosen to represent a broad spectrum of communities with a diversity of geography (West, Northeast, Midwest, and South), discipline (Computer Science, Math, Statistics, and Domains), as well as institution type (Historically Black Colleges and Universities (HBCU’s), Hispanic-Serving Institutions (HSI’s), other Minority-Serving Institutions (MSI\u27s), Community College\u27s (CC’s), 4-year colleges, Tribal Colleges, R1 Universities, Government and Industry Partners)

Keeping Data Science Broad: Negotiating the Digital and Data Divide Among Higher Education Institutions

The goal of the “Keeping Data Science Broad” series of webinars and workshops was to garner community input into pathways for keeping data science education broadly inclusive across sectors, institutions, and populations. Input was collected from data science programs across the nation, either traditional or alternative, and from a range of institution types including community colleges, minority-led and minority-serving institutions, liberal arts colleges, tribal colleges, universities, and industry partners. The series consisted of two webinars (August 2017 and September 2017) leading up to a workshop (November 2017) exploring the future of data science education and workforce at institutions of higher learning that are primarily teaching-focused. A third follow-up webinar was held after the workshop (January 2018) to report on outcomes and next steps. Program committee members were chosen to represent a broad spectrum of communities with a diversity of geography (West, Northeast, Midwest, and South), discipline (Computer Science, Math, Statistics, and Domains), as well as institution type (Historically Black Colleges and Universities (HBCU’s), Hispanic-Serving Institutions (HSI’s), other Minority-Serving Institutions (MSI\u27s), Community College\u27s (CC’s), 4-year colleges, Tribal Colleges, R1 Universities, Government and Industry Partners)

Applications of Analytics and Machine Learning in Energy Industry-Academia Workshop : Welcome and Overview

Presented on September 6, 2016 from 8:00 a.m.-8:10 a.m. at the Klaus Advanced Computing Building, Room 1116W, Georgia Institute of Technology.South Big Data Innovation Hub ; Applications of Analytics and Machine Learning in Energy Industry-Academia WorkshopRuntime: 08:05 minutesThe goal is to connect industry partners with academic researchers in the domains of Energy: Power, Smart Grid, etc as well as Big Data and Data Science. Speakers will be specifically selected to share their perspective on high-impact applications or challenges surrounding the use of data science, analytics, informatics, and machine learning in the Energy space. Attendees will come from academic research institutions across the 16 states that comprise the South Big Data Innovation Hub and industrial partners across the country. Participants will engage in active scoping and round-table discussions in order to build partnerships across highimpact application verticals

Global population-specific variation in miRNA associated with cancer risk and clinical biomarkers

Background: MiRNA expression profiling is being actively investigated as a clinical biomarker and diagnostic tool to detect multiple cancer types and stages as well as other complex diseases. Initial investigations, however, have not comprehensively taken into account genetic variability affecting miRNA expression and/or function in populations of different ethnic backgrounds. Therefore, more complete surveys of miRNA genetic variability are needed to assess global patterns of miRNA variation within and between diverse human populations and their effect on clinically relevant miRNA genes

Data Challenges and Opportunities for Next Generation Materials Innovation

Presented on August 25, 2016 from 11:15 a.m.-12:30 p.m. at the Klaus Advanced Computing Building, Room 1116W, Georgia Institute of Technology.South Big Data Innovation Hub ; Data Infrastructure for Materials and Advanced Manufacturing Workshop.Renata Rawlings-Goss is with the SouthBDHub.Chuck Ward is with the Air Force Research Laboratory.Turab Lookman is with the Los Alamos National Lab.Runtime: 9:08 minutes (Rawlings-Goss)Runtime: 24:32 minutes (Ward)Runtime: 35:40 minutes (Lookman)South Big Data Innovation Hu

Data Infrastructure for Materials and Advanced Manufacturing Workshop : Welcome Address

Presented on August 25, 2016 from 8:00 a.m.-8:15 a.m. at the Klaus Advanced Computing Building, Room 1116W, Georgia Institute of Technology.South Big Data Innovation Hub ; Data Infrastructure for Materials and Advanced Manufacturing Workshop.Runtime: 12:53 minutesThe goal of this workshop is assess and deliberate on the current state of the data infrastructure supporting the accelerated insertion of new and advanced materials into commercial products. For this purpose, we have attempted to convene diverse stakeholders involved in this emerging f1eld, including industry, academia, national laboratories, and nonprofits, whose expertise cuts across several traditional disciplines such as materials science and engineering, design and manufacturing sciences, and computer and data sciences. Speakers have been specifically selected to share their perspective on high-impact applications or challenges surrounding the use of Data Science and Informatics in the Materials and Advanced Manufacturing space. Attendees will come from academic research institutions across the 16 states that comprise the South Big Data Innovation Hub. Participants will engage in active scoping and round-table discussions in order to build partnerships across high-impact application verticals

Welcome Remarks and South Hub Impacts and Opportunities

Presented on April 9, 2019 at 8:30 a.m. in the Technology Square Research Building (TSRB) Banquet Hall, Georgia Institute of Technology.South Big Data Innovation Hub ; All Hands MeetingChaouki T. Abdallah, PhD., is the Executive Vice President for Research (EVPR) at Georgia Tech and a professor in the School of Electrical and Computer Engineering. As EVPR, Dr. Abdallah, directs Georgia Tech’s research program and serves as chief research officer providing overall leadership for the research, economic development, and related support units within the Institute. He is a proud alumnus of Georgia Tech earning his M.S. and Ph.D. in Electrical Engineering in 1982 and 1988, respectively.Stan Ahalt, PhD. Principal Investigator, South Big Data Regional Innovation Hub – University of North Carolina-Chapel Hill, is the Director of the Renaissance Computing Institute (RENCI) at UNC-Chapel Hill. As Director, he leads a team of research scientists, software and network engineers, data science specialists, and visualization experts who work closely with faculty research teams at UNC, Duke, and NC State as well as with partners across the country. RENCI’s role is to provide enabling cyberinfrastructure to these research collaborations, which entails working on the challenges of data management, sharing, integration, and security. Dr. Ahalt is also a Professor in the UNC Computer Science Department and the Associate Director of the Informatics and Data Science (IDSci) Service in the North Carolina Translational and Clinical Sciences Institute (NC TraCS), UNC’s CTSA award. Dr. Ahalt earned his Ph.D. in Electrical and Computer Engineering from Clemson University and has over 30 years of experience in high performance computing, signal processing, and pattern recognition.Srinivas Aluru, PhD. is a Principal Investigator of the South Big Data Regional Innovation Hub (South Hub), a co-Executive Director of the Georgia Tech Interdisciplinary Research Institute (IRI) in Data Engineering and Science (IDEaS) and a professor in the School of Computational Science and Engineering within the College of Computing at Georgia Tech. Dr. Aluru conducts research in high performance computing, data science, bioinformatics and systems biology, combinatorial scientific computing, and applied algorithms. He pioneered the development of parallel methods in computational biology, and contributed to the assembly and analysis of complex plant genomes.Renata Rawlings-Goss, PhD. Executive Director, South Big Data Regional Innovation Hub – Georgia Institute of Technology. Dr. Rawlings-Goss currently leads the South Big Data Innovation Hub. Formerly, she worked with the White House Office of Science and Technology Policy to create the National Data Science Organizers Group, which facilitates data science groups to address national “Grand Challenge” problems. Dr. Rawlings-Goss was awarded a AAAS fellowship and worked with the National Science Foundation in the directorate of Computer and Information Science and Engineering (CISEOAD) on the Big Data research program, as well as Big Data policies and priority goals for the foundation. She sat on the NITRD interagency Big Data Senior Steering group, charged with strategic planning for Big Data research funded by the federal government. Dr. Rawlings-Goss is a biophysicist by training where her research interests include data-driven analysis of genetic/expression variation among worldwide human populations.Runtime: 56:42 minutesThe SBDH All Hands meetings are organized to bring together the SBDH community in order to foster new and support existing data science collaborations, share best practices and resources for data and Data Science related projects in the priority areas for the southern region. The meeting is an opportunity to find collaborators, share accomplishments, extend your network, offer resources, and take on a leadership role in regional initiatives