I am on the job market, looking for an academic position starting Fall 2018!

Oliver L. Haimson

PhD Candidate
Informatics Department

Donald Bren School of Information
and Computer Sciences

University of California, Irvine


Data science for positive social impact

I am passionate about using data science methods to affect positive change in the world. I have worked on a number of projects that use machine learning, predictive analytics, and statistics to understand societal issues and impact real world change, including reducing fire risk, using social media to identify restaurants with public health risks, and using online content to detect HIV prevalence in cities. The Firebird project not only impacted fire inspection processes and potentially saved lives on a local level, but was highlighted by the National Fire Protection Association as a best practice for using data to inform fire inspections.

Collaborators

Hoda Anton-Culver, Jed Brubaker, Polo Chau, Shang-Tse Chen, Xiang Cheng, Bistra Dilikina, Gillian Hayes, Matthew Hinds-Aldrich, Michael Madaio, John Schomberg, Wenwen Zhang

Publications

Firebird: Predicting Fire Risk and Prioritizing Fire Inspections in Atlanta
Michael Madaio, Shang-Tse Chen, Oliver L. Haimson, Wenwen Zhang, Xiang Cheng, Matthew Hinds-Aldrich, Duen Horng (Polo) Chau, Bistra Dilikina
ACM SIGKDD Conference on Knowledge Discovery and Data Mining, August 2016
[full paper acceptance rate: 12%][Best Student Paper Runner-Up]
[PDF]

Supplementing Public Health Inspection via Social Media
John Schomberg, Oliver L. Haimson, Gillian R. Hayes, Hoda Anton-Culver
PLoS ONE 11(3), March 2016
[HTML]

Identifying and Prioritizing Fire Inspections: A Case Study of Predicting Fire Risk in Atlanta
Michael Madaio, Oliver L. Haimson, Wenwen Zhang, Xiang Cheng, Matthew Hinds-Aldrich, Duen Horng (Polo) Chau, Bistra Dilikina
Bloomberg Data for Good Exchange, September 2015
[PDF]

DDF Seeks Same: Sexual Health-Related Language in Online Personal Ads For Men Who Have Sex With Men
Oliver L. Haimson, Jed R. Brubaker, Gillian R. Hayes
ACM CHI Conference on Human Factors in Computing Systems, April 2014
[acceptance rate: 23%]
[PDF]