Policy + Data Science

I work to leverage data science and visualization techniques to answer policy questions. I support increasing data literacy among decision makers and using data to make informed policy decisions. In primarily use use R in my work (and occasionally Python). I am also interested in learning about, and applying, modern techniques such as neural networks and Bayesian statistics. Currently I am a AAAS Science & Technology Policy Fellow working in the U.S. Government. 

Previously, as a PhRMA Foundation Regulatory Science Fellow in Regulatory Science and Policy at Sanofi I focused on developing data-driven strategies to inform and support policy positions and to further the field of regulatory science. I covered regulatory topic areas related to antimicrobial resistance, vaccines, opioids, and artificial intelligence. Additionally I helped collect and draft comments for proposed FDA regulations.

In my PhD work I used both isolated tissue experimental methods and computational modeling to quantify neuronal control of airways in lung diseases like asthma or after e-cigarette vapor exposure. In my undergraduate work, I studied chemistry, economics, and physics.

In my free time I train for full and half marathons, make podcasts, and study Mandarin Chinese. 我会说一点儿中文 
"We choose to go to the moon in this decade and do the other things, not because they are easy, but because they are hard"
-JFK