Brendan T. O'ConnorAssistant Professor, College of Information and Computer Sciences
University of Massachusetts Amherst
Email: firstname.lastname@example.org Twitter: @brendan642
Room 238, Computer Science Building, 140 Governors Drive, Amherst, MA 01003
I am an assistant professor in the College of Information and Computer Sciences at University of Massachusetts Amherst (since Fall 2014). I am affiliated with the Computational Social Science Institute, the Initiative in Cognitive Science, and the Centers for Data Science and Intelligent Information Retrieval.
Links: SLANG Lab, Teaching, CV, Bio, Talks, Notes, Misc.
Teaching in Spring: COMPSCI 690D: Deep Learning for Natural Language Processing. If you are interested in enrolling but wasn't able to, please see the information on the course webpage.
Currently teaching: CS 589, Machine Learning. Fall 2018 office hours: MW 4:00-4:45
Talks on current research:
Recent press coverage:
What can statistical text analysis tell us about society? I develop text analysis methods that can help answer social science questions. I'm interested in statistical machine learning and natural language processing, especially when informed by or applied to areas like political science or sociolinguistics. My work often uses text data from news and social media.
See also my earlier research statement or publications below.
There is a rich set of other faculty at UMass interested in areas from computational social science to natural language processing. See the Computational Social Science Institute (CSSI) website, and this list of computation+language researchers and courses.
I joined UMass after receiving my PhD from Carnegie Mellon University's Machine Learning Department, where I was advised by Noah A. Smith. I have also been a Visiting Fellow at Harvard IQSS, and interned with the Facebook Data Science team. Before grad school, I worked on crowdsourced annotations at CrowdFlower / Dolores Labs, and natural language search at Powerset. I started studying the intersection of AI and social science as an undergrad and masters student in Stanford Symbolic Systems (cognitive science).