They Told Me I Wasn’t A "Math Person" — This Is Where I Am Now

Courtesy of Yada Pruksachatkun.
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“You’re not a math person.” For as long as I can remember, I had internalized that phrase. I preferred lessons on history and creative writing to the seemingly meaningless equations I learned in math classes. I was an activist and artist, not a scientist or engineer. When I arrived at college as a bright-eyed 16 year old (I had finished high school early) I declared philosophy and economics majors. But even as a humanities student, I had to take a class to fulfill a the quantitative course requirement. To avoid enrolling in a tedious math course, I signed up for computer science.
That decision changed my life. In the class, I found a tool I could use to create the worlds I had written about as a science fiction writer. I discovered that with computer science, I can create apps that make people healthier, programs to help the visually impaired see, and people who are deaf hear. I learned how math, a subject I once despised, can be used to build tools to predict the spread of diseases and model how everything in this world works. In the span of two years, I did everything I could to rewire my brain. I spent weekends teaching myself new skills, going to hackathons and diving in head first to catch up. I became a computer scientist through internships at Facebook, working with startups, and doing research at labs at MIT. I became an engineer through late nights with friends, managers who helped me find my voice, and rejections from many, many scholarships and internships.
illustrated by Paola Delucca.
All the while, imposter syndrome loomed large. Only 18% of computer science graduates are women, according to National Center for Women and Information Technology (NCIWT). Not all of those graduates enter the technology sector. The result is that women remain seriously underrepresented in industry. The effects of that were obvious to me from the start. I sometimes felt like I didn’t belong. This feeling came in furtive stares when people at hackathons asked my male friends for technical advice that I was equally as equipped to answer. At tech conferences, being one of the only women in the room sometimes led to inappropriate and uncomfortable situations, especially at after-hours events. But despite these feelings of inferiority, I never stopped trying.
Looking back, I think I was able to make the most of my time. Now, thanks to my coding ability and mathematical maturity, I am determined to use deep technology in research labs and apply it to solve problems in healthcare and education accessibility. As the founder of a nonprofit, I have seen firsthand the deep divide between the worlds of technology and social impact really are. Technology has the power to connect and amplify local impact, and I believe that when people in technology and social development come together, exponential impact will occur. Thanks to the Effective Altruism movement and organizations such as DataKind, this separation is starting to disappear, but there is still much more work to be done.
As for me, after graduating I will be delving into how we can use deep learning to help machines understand human language and dialogue as a Capital One Fellow and graduate student at the NYU Center for Data Science, bridging the technical talent imbalance by cofounding a data science fellowship, and continuing to be a venture partner at Contrary Capital, where I support entrepreneurs.
I hope that my experience and path forward will open the doors to balancing the gender scales in tech. And when the next generation of aspiring computer programmers and scientists asks me for advice, here is what I’ll say: Figure out what your values are early on and base your decisions on those, reflect often, and do not let anyone ever, ever tell you to stay in your place. Oh, and don’t be afraid to sign up for that math course.
Yada Pruksachatkun is a senior at Wellesley College studying Computer Science and Mathematics. She is a researcher at MIT CSAIL, and will be packing up for New York to explore Natural Language Processing as part of NYU Center for Data Science after graduation. Follow her on Medium here.

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