it me

Roy Adams


Postdoc

Room 340
Malone Hall
Johns Hopkins University

About Me

I am a postdoc at Johns Hopkins University working with Professors Suchi Saria and Michael Rosenblum. I completed my PhD in 2018 at UMass working in the Machine Learning for Data Sciences lab with Prof. Benjamin Marlin.



Teaching

Previous courses

COMPSCI 590N: Introduction to Numerical Computing with Python

Research Interests

I am interested in probabilistic and latent variable modeling, inference methods for these models, and the application of these models to problems in health and ecology.

Current Projects

Past Projects

Publications

Learning Models from Data with Measurement Error: Tackling Underreporting. Roy Adams, Yuelong Ji, Xiaobin Wang, and Suchi Saria. ICML, 2019. preprint

Learning Time Series Segmentation Models from Temporally Imprecise Labels. Roy Adams and Benjamin Marlin. UAI, 2018. paper

rConverse: Moment by Moment Conversation Detection Using a Mobile Respiration Sensor. Rummana Bari, Roy Adams, Md. Mahbubur Rahman, Megan Battles Parsons, Eugene H. Buder, Santosh Kumar. IMWUT, 2018. paper

Learning Time Series Detection Models from Temporally Imprecise Labels. Roy Adams and Benjamin Marlin. AISTATS, 2017. paper code

Parsing Wireless Electrocardiogram Signals with Context Free Grammar Conditional Random Fields. Thai Nguyen, Roy Adams, Annamalai, and Benjamin Marlin. IEEE Wireless Health, 2016.

Impact of a Collective Intelligence Tailored Messaging System on Smoking Cessation: The Perspect Randomized Experiment. Rajani Sadasivam, Erin Borglund, Roy Adams, Benjamin Marlin, and Thomas Houstson. Journal of Medical Internet Research, 2016. paper

Hierarchical Span-Based Conditional Random Fields for Labeling and Segmenting Events in Wearable Sensor Data Streams. Roy Adams, Nazir Saleheen, Edison Thomas, Abhinav Parate, Santosh Kumar, and Benjamin Marlin. International Conference on Machine Learning, 2016. paper code

PERSPeCT: Collaborative Filtering for Tailored Health Communications. Roy Adams, Rajani Sadasivam, Kavitha Balakrishnan, Rebecca Kinney, Thomas Houston, and Benjamin Marlin. ACM Conference on Recommender Systems, 2014.

Towards Collaborative Filtering Recommender Systems for Tailored Health Communications. Benjamin Marlin, Roy Adams, Rajani Sadasivam, and Thomas Houstson. American Medical Informatics Association, 2013.

Posters

Parsing Wireless Electrocardiogram Signals with the CRF-CFG Model. UAI Workshop: Machine Learning for Health, 2016.

Hierarchical Nested CRFs for Segmentation and Labeling of Physiological Time Series. Roy Adams, Edison Thomaz, and Benjamin Marlin. NIPS Workshop: Machine Learning for Healthcare, 2015.

Work Experience

Postdoctoral Researcher, Johns Hopkins University, 2018 to present.
Research Assistant, University of Massachusetts, 2012 to 2018.
Research Intern, Yahoo, Summer 2015
Software Engineering Intern, Hewlett-Packard, Summer 2012
Summer REU, Eco-Informatics Summer Institute, Oregon State University, Summer 2011
Student Programmer, Oregon State University, Summer 2010

Education

PhD in Computer Science, University of Massachusetts, 2018.
MS in Computer Science, University of Massachusetts, 2015.
BS with honors in Computer Science Engineering, University of California - Davis, 2011.