I am a founding faculty member in the new Information Science department in the College of Media, Communication, and Information at CU-Boulder (see: CU vs. UC).
I received a Ph.D. in Computer Science from Johns Hopkins University in 2015,
and a B.S. in Computer Science from the University of Illinois at Urbana-Champaign in 2009.
See my CV.
My research is at the intersection of text analysis and health/social science.
On the methodological side, I research machine learning and natural language processing, and in particular I develop methods in topic modeling, which I use to discover patterns in large text datasets.
On the applied side, I study social media to learn about human behavior, especially in the context of public health.
I am currently on leave and will not be responsive to most messages.
- INFO 1301 - Quantitative Reasoning 1: Intuitions & Evidence
- INFO 2301 - Quantitative Reasoning 2: Uncertainty & Inference
- INFO 4604/5604 - Applied Machine Learning
- That Tweet You Just Sent Could Help Predict a Flu Outbreak (NBC News, 5/19/2017)
- Someone is tracking how much you 'vape' on Twitter (Washington Post, 2/24/2016)
- Scientists using social media to track air pollution in China (CBS News, 11/21/2014)
- When Google got flu wrong (Nature, 2/13/2013)
- Tracking the flu with technology and Twitter (CNN.com, 1/30/2013)
- 10 Things We Can Learn From Your Health-Related Twitter Rants (The Atlantic, 7/15/2011)
- Twitter Provides A Trove Of Health Trends (NPR, 7/13/2011)
- The Naked Future (book interview, pages 61-67)
- Press:Here interview (NBC Bay Area, aired 8/05/2011)
- Twitter Stories: the future of public health (Twitter video series, published 3/12/2012)