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 no longer in academia as of May 2020. I am not currently responding to reviewer requests.

Fall 2019

• INFO 4871/5871 - Social Media Data Mining

Spring 2019

• INFO 2301 - Quantitative Reasoning for Information Science

Fall 2018

• INFO 4604/5604 - Applied Machine Learning

Past Courses

• INFO 1301 - Quantitative Reasoning 1: Intuitions & Evidence
  • Spring 2017, Fall 2016
• INFO 2301 - Quantitative Reasoning 2: Uncertainty & Inference
  • Spring 2018, Spring 2017
• INFO 4604/5604 - Applied Machine Learning
  • Fall 2017

Guest Lectures

• CMCI 1020 - Concepts and Creativity (Colorado)
• Who Designs for Whom? (user-centered design, algorithmic discrimination)
• Evaluating Information ("truthiness", fact checking, "filter bubble")
• CS 465 - Natural Language Processing (JHU)
• Topic Models
• NETS 213 - Crowdsourcing & Human Computation (Penn)
• Public Health Meets Social Media

Selected Talks

• Topic Modeling with Structured Priors for Text-Driven Science (University of Colorado, 2/27/2015) (video)
• Making Sense of the Web for Public Health using NLP (University of Maryland, 12/03/2014)
• Using Social Media to Study Public Health (Cafe Scientifique, 5/29/2014)

Selected Press

• 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)