As other high school seniors were taking their SATS or working on college applications, Andrew Jin of San Jose, California, was developing a machine learning algorithm so that his computer could detect mutations in DNA.
While his algorithm is impressive in itself, the 17-year-old has taken it one groundbreaking step further: The DNA mutations he’s discovered could be used to develop medication that resists HIV or meningitis.
According to Fast Company, Jin’s project — which won the First Place Medal of Distinction for Global Good at Intel’s Science Talent Search along with a $150,000 prize — started out as a simple research endeavor.
“I was doing it out of curiosity,” Jin told Fast Company. “I started thinking about natural selection and evolution, and that we understand so much about its theory, but we know nothing about reality. I was curious about what mutations help us be sophisticated human beings.”
Jin began his research by studying 179 human DNA sequences from around the world. But since each sequence involved 3 million base pairs of DNA, Jin realized the need for a machine-learning algorithm. Once the algorithm was in place, he discovered over 100 mutations that could resist meningitis, influenza and HIV.
“The main goal of my project was to actually identify these adaptive mutations to figure out how humans evolved over the past maybe 30,000 years or so,” Jin told The Wall Street Journal. “And the way I went about doing that was I developed a machine-learning approach where I trained models to think like scientists in a sense to actually identify these very complicated patterns and large data sets that no human can actually accomplish.”
The budding scientist told Fast Company he also needs to decide which college he will attend next year. For now, he’s narrowed his future field of study down to computer science or biology and is an avid Boy Scout and pianist in his free time.
Top photo courtesy of the Society for Science & the Public’s Facebook page