Scholar
Christopher Homan
Google Scholar ID: kU6puLcAAAAJ
Rochester Institute of Technology
Citations & Impact
Citations
1,167
H-index
16
i10-index
24
Publications
20
Co-authors
29
list available
Contact
Publications
Resume (English only)
Academic Achievements
- 1. The paper 'Public knowledge and attitudes towards bystander cardiopulmonary resuscitation (CPR) in Ghana, West Africa' was accepted by the International Journal of Emergency Medicine.
- 2. A study on assessing human translations from French to Bambara for machine learning, co-authored by LPI MS student Allahsera Auguste Tapo and others, was accepted to the AfricaNLP 2020 workshop.
- 3. Research on neighborhood-based pooling for population-level label distribution learning, led by LPI Ph.D. students Weerasooriya and Liu, with PI Homan, was accepted to ECAI 2020.
- 4. PI Christopher Homan presented his work on learning to predict population-level label distributions at the Seventh AAAI Conference on Human Computation and Crowdsourcing, coauthored with LPI Ph.D. student Tong Liu and MS students Akash Venkatachalam & Pratik Sanjay Bongale.
Research Experience
- Christopher Homan has led several research projects, including developing methods to collect, clean data, and evaluate and train translation models using crowdsourcing (the Bayelemabaga project), as well as predicting public health risks from first-person narratives.
Background
- Christopher Homan is an Associate Professor in the Department of Computer Science at Rochester Institute of Technology. His research interests include designing and investigating algorithms that engage, model, and learn from human populations, creating dynamic systems that represent diverse values and beliefs, build trust, and advance community values in public policy and decision making.
