Sept. 28, 2017 — Computing is one of the least diverse science, technology, engineering, and mathematics (STEM) fields, with an underrepresentation of women and minorities, including African Americans and Hispanics. Leveraging this largely untapped talent pool will help address our nation’s growing demand for data scientists. Computational approaches for extracting insights from big data require the creativity, innovation, and collaboration of a diverse workforce.
As part of its efforts to train the next generation of computational and computer scientists, this past summer, the Computational Science Initiative (CSI) at the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory hosted a diverse group of high school, undergraduate, and graduate students. This group included students from Jackson State University and Lincoln University, both historically black colleges and universities. The Lincoln University students were supported through the National Science Foundation’s Louis Stokes Alliances for Minority Participation program, which provides research and other academic opportunities for minority students to advance in STEM. Two of the students are recipients of prestigious fellowship programs: the Graduate Education for Minorities (GEM) Fellowship, through which qualified students from underrepresented minorities receive funding to pursue STEM graduate education; and the DOE Computational Science Graduate Fellowship (CSGF), which supports doctoral research using mathematics and computers to solve problems in many scientific fields of study, including astrophysics, environmental science, and nuclear engineering.
“To address challenges in science, we need to bring together the best minds available,” said CSI Director Kerstin Kleese van Dam. “Great talents are rare but can be found among all groups, so we reach out to the broadest talent pools in search of our top researchers at every education level and career stage. In return, we offer them the opportunity to work on some of the most exciting problems with experts who are pushing the state of the art in computer science and applied mathematics.”
The students’ research spanned many areas, including visualization and machine learning techniques for big data analysis, modeling and simulation applications, and automated approaches to data validation and verification.
To read the full story, with graphics, please visit the original story at: https://www.bnl.gov/newsroom/news.php?a=212478
Source: Ariana Tantillo, Brookhaven National Laboratory