Ian Scheffler
In North Carolina, where Jacob Gardner, Assistant Professor in Computer and Information Science, grew up, hurricanes arrive like unwelcome relatives — Fran, Matthew, Florence. In high school, Gardner interned for a company that attempted to predict hurricanes. “That was my first exposure to machine learning,” he recalls.
Machine learning, a form of artificial intelligence (AI), works by predicting the future using vast amounts of data from the past. As Gardner puts it, “We train models that take the data — examples we’ve seen — and we try to generalize new examples we haven’t seen.”
Today, Gardner applies machine learning not to weather prediction, but to scientific research. Rather than predict the movement of hurricanes, he develops tools that will allow scientists to supercharge fields like drug discovery. “I want to build the AI equivalents of the electron microscope,” he says. “Tools that help scientists do what they’re already doing, just faster, more effectively and with new insight.”