Laura Kegelmeyer embraces her role as a problem solver. Since arriving at LLNL in 1988, she has brought her expertise to bear on image processing and analysis—first in biomedical applications, such as DNA mapping and breast cancer detection, and now at the National Ignition Facility (NIF), home of the world’s most energetic laser. Her Optics Inspection team combines large-scale database integration with custom machine learning algorithms and other data science techniques to analyze images captured throughout NIF’s 192 beamlines. This inspection process informs an automated “recycle loop” that extends optic lifetimes. Based on this work and previous involvement with Women in Data Science (WiDS) events, Kegelmeyer was invited to speak at the 2019 WiDS conference. “It’s an amazing opportunity to present an example of applying machine learning to ‘big science.’ NIF’s exploration of physical phenomena under extreme conditions has far-reaching impact across the globe and for future generations,” she says. “I hope to inspire data scientists to use their skills to address challenges in exciting scientific areas.” Kegelmeyer holds degrees in Biomedical Engineering and Electrical Engineering from Boston University.