I graduated with my bachelor’s from Wesleyan University with a double major in computer science and English literature in 2003. Then I received my Ph.D. from UC Berkeley in computer science in 2012.
I've been working at Google since finishing graduate school. I work on natural language processing (NLP) using machine learning – a field that has grown from a few people in research to many thousands of engineers in just a few years.
I don't think I've received any honors or awards since I was in college. The computer science department at Wesleyan gave me a bunch of awards during my undergrad because I was basically the only student.
I'm especially interested in commonalities among languages and how we can represent questions or concepts in any language with a single model. I'm also working on understanding queries that contain multiple languages – linguists call this 'code mixing'.
Statistical analysis of data is making the world's economies run more efficiently. That's generally good – cheaper products, personalized services, Lyft line, advanced basketball analytics. But sometimes it's not – Russia hacked our election by targeting a few key precincts. So that's pretty interesting.
Both the I School and MIDS program have some liberal arts tendencies. You get a well-rounded education, which is unusual for graduate programs. I think that serves students well in the long run for developing their careers.
I like how abstract mathematical ideas can be applied directly to very practical problems.
Be curious and skeptical. Don't forget that there's plenty of hype in data science (and machine learning) just like everywhere else.
I've won some national and world championships playing ultimate frisbee.
I spend a lot of time playing sports.
I recently finished 'Sapiens' by Yuval Harari. It is excellent. I'm currently reading 'Homegoing' by Yaa Gyasi.
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