In high school, Gracie was not at all interested in technology like a lot of her classmates. She didn’t play video games or spend time on a computer. She didn’t even know what computer science was until she went to college. Thanks to receiving a scholarship that encouraged women to pursue CS, Gracie was obligated to take her first coding class. She was full of insecurities about being a latecomer to programming: “I figured I’d get it over with, and then forget about CS.” When Gracie discovered, however, that coding is essentially a creative problem-solving tool that can be used in a wide range of professions, she got hooked.

Gracie decided she wanted to use her coding skills to solve problems to save the environment – her passion. She started by working to save endangered animals like orcas. With her speciality in machine learning, she trained computers to recognize individual animals in the wild and track their health and other conditions. Today Gracie uses machine learning to train computers to translate satellite images of earth and produce maps that distinguish the many categories of land use, from urban buildings to forest, to grassland and crops. These maps are critical for governments, non-profits and industries to develop policies for conserving and improving our environment.