Ashlynn Daughton is an information science PhD student interested in leveraging Internet data to better inform public health decision makers. She is a graduate of the University of California, Berkeley (BS in molecular biology) and Boston University (MA in public health concentrating in maternal and child health and epidemiology). She works with Michael Paul at CU Boulder, and holds a position at Los Alamos National Laboratory in the Analytics, Intelligence and Technology Division. Her current research focuses on using machine learning techniques to better understand human behavior, development of decision support tools for public health professionals and methods to better incorporate Internet and social media data into traditional epidemiological models. In her spare time Ashlynn enjoys running, salsa dancing and copious amounts of coffee.