I am a data scientist and economist.
My data science journey officially started in 2016, when I became a Data Science for Social Good fellow. During that summer, I worked with some really awesome people to use machine learning to better allocate resource to reduce juvenile delinquency in Milwaukee. After graduating from my PhD program, I then worked as a computational social scientist at the Pew Research Center, where I experimented with various data science, survey, machine and deep learning techniques to write about gender representation in news, online searches, political polarization, Americans’ interest in guns, among other work. I also contributed to various technical tutorials on medium. Since then, I had a brief stint as a Research Scientist with FiscalNote, a startup that builds a legislative tracking platform. Most recently, I am a Senior Data Scientist at Mission Lane, a fintecth startup that aims to provide more equitable access to fiancial services for the underserved.
I graduated with a PhD in Economics from University of California, San Diego in 2017. In my dissertation, I examined the effect of political salience on advertisers’ decisions in ad allocation across different media outlets. Before the PhD program, I was awarded the Japanese government scholarship (MEXT) to study public policy at the University of Tokyo, and graduated with the Best Student Award. I also have an engineering degree from UC Berkeley.
I speak English, Cantonese and Japanese, and I have a penchant for projects at the intersection of technology and social science. I am a lifelong learner, always fascinated by new discoveries and progress in science. In my free time, I like to play the violin, and hang out with my dog jarjar.
I am a U.S. citizen and a proud Hong Kong-er.
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