UC Merced & UC Riverside tackle Data Science Challenge on ML-assisted heart modeling

For the first time, students from the University of California (UC) Merced and UC Riverside joined forces for the two-week Data Science Challenge (DSC) at LLNL, tackling a real-world problem in machine learning (ML)-assisted heart modeling. Held in the Livermore Valley Open Campus’s newly remodeled University of California Livermore Collaboration Center from July 10-21, the event brought together 35 UC students—ranging from undergraduates to graduate-level students from a diversity of majors—to work in groups to solve four key tasks, using actual electrocardiogram (ECG) data to predict heart health. According to organizers, the purpose of the challenge was to give students a taste of the broad scope of work that goes on at a national laboratory and provide them with experience working in interdisciplinary teams. “One of my main goals is developing the students’ technical skills, but I also want to get people excited about going to grad school who hadn't thought about it yet,” said LLNL computer scientist Brian Gallagher, who co-directed the DSC program. “I want to get people thinking about a science career, not just a web development career or software engineering career. The students have been super engaged and interested in career paths and job progressions. Many have asked how to get an internship, which I take as a good sign.” Read more at LLNL News.