Sponsored by the DSI, LLNL’s winter hackathon took place on February 16–17. In addition to traditional hacking, the hackathon included a special datathon competition in anticipation of the Women in Data Science (WiDS) conference on March 7.
The MFEM software library provides high-order mathematical algorithms for large-scale scientific simulations. An October workshop brought together MFEM’s global user and developer community for the first time.
In this episode (32:00), LLNL's Jeff Hittinger talks about scientific success, leadership, and the tricks he’s cultivated for communicating science to broader audiences through the Livermore Ambassador Lecture series.
More than 100 LLNL staff and students gathered virtually for the first session of a new career panel series inspired by the annual Women in Data Science conference and sponsored by the Data Science Institute.
Brian Gallagher works on applications of machine learning for a variety of science and national security questions. He’s also a group leader, student mentor, and the new director of LLNL’s Data Science Challenge.
Computing relies on engineers like Stephanie Brink to keep the legacy codes running smoothly. “You’re only as fast as your slowest processor or your slowest function,” says Brink, who works in CASC. By analyzing a legacy code’s performance, Brink and her team can reduce the amount of time it takes to run and allow for more critical science to be accomplished.
Coinciding with International Women’s Day on March 8, LLNL’s 4th Women in Data Science (WiDS) regional event brought women together to discuss successes, opportunities and challenges of being female in a mostly male field.
Nisha Mulakken is advancing COVID-19 R&D and mentoring the next generation. “The opportunities we are exposed to early in our careers can shape the limits we place on ourselves and our approaches to challenges we encounter throughout our careers,” she says.