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
COMPSCI 590N: Introduction to Numerical Computing with Python
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.
Health Monitoring with Wearable Sensors
The emerging field of mobile health (mHealth) seeks to replace the use of self report data with continuously recorded physiological data streams collected using wearable sensors. While mHealth technologies have the potential to yield novel insights into health and behavior, significant data analysis challenges must first be overcome. In particular, I work on novel structured predcition models for detecting activities of interest, such as smoking and eating, while integrating out the uncertainty caused by imperfect observation processes.
Targeted Health Messaging
Behavioral science research has shown that periodical targeted messaging (via email, text message, etc.) can improve the success of smoking secession rates as part of a comprehensive treatment plan. Furthermore, evidence suggests that targeted messaging is more effective if personalized. The goal of this project is to develop and deploy a targeted health messaging system based around current recommender system technologies.
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.
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.
, Johns Hopkins University, 2018 to present.
, University of Massachusetts, 2012 to 2018.
, Yahoo, Summer 2015
Software Engineering Intern
, Hewlett-Packard, Summer 2012
, Eco-Informatics Summer Institute, Oregon State University, Summer 2011
, Oregon State University, Summer 2010
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.