Population Informatics
Welcome
The Population Informatics Lab applies informatics, data science, and computational methods to the increasingly large digital traces available to advance public health, social science, and population research. This research group is a joint effort between the School of Public Health, the Departments of Computer Science and Engineering, and Industrial Systems and Engineering at Texas A&M University. We specialize in data science, KDD (Knowledge Discovery and Datamining), data integration, visualization, decision support systems, health informatics, computational social science, data governance, and privacy with a focus on collaborating with government agencies and administrative data.
Congratulations!
Congratulations to everyone here at the lab! Our $12.6 Million Award was featured by Vital Record, Texas A&M Health's News Source!
Congratulation to Mohammad! His paper on the financial toll of fighting liver cancer was covered in the US News !
Congratulations to Michelle Hayek! Her paper comparing at-home blood pressure monitoring with traditional clinic-based monitoring was highlighted on TAMU Engineering's news website!
Michelle Hayek received the second-place award in the ISEN PhD Poster Competition for her presentation on the "Economic Impact of Ambulatory Blood Pressure Monitoring Compared with Clinical Blood Pressure Monitoring: A Simulation Model" at this year's ISEN Spring Annual Award Ceremony organized by the Wm Michael Barnes '64 Department of Industrial & Systems Engineering at Texas A&M University.
Announcements
New Fundings and Achievements:
Funding: Texas 1115 Medicaid Waiver Ten Year Extension Evaluation (9/1/2023-831/2032). $12M. PI Kum, Shipp, & Ohsfeldt.
Dr. Kum cochair the Digital Ethology Ernst Strüngmann forum (Forum is supported by the Deutsche Forschungsgemeinschaft, the German Research Foundation). Book in print by MIT press (summer 2024).
Dr. Hye Chung Kum, director of the Population Informatics Lab, was recently inducted as a Fellow of the American Medical Informatics Association (AMIA). Click here to read more about this award.
"Effective Real-world Telemonitoring of Chronic Disease for the Underserved": Lab research on teleservices continues to grow as we secure more funding. The Lab was funded $1M for the next three years to explore more in depth how to develop a more effective telemonitoring system with a focus on serving the underserved. Click here to read more about this grant funding.
"Measuring Perceptions Of Legal And Ethical Frameworks For Authorized Data Use": Lab research on data governance, in collaboration with the Law School, was recently funded by T3 for the next two years.
Summary published in The Conversation: Data privacy laws in the US protect profit but prevent sharing data for public good – people want the opposite
What is Population Informatics?
Computational Social Science is an emerging research area at the intersection of health science, social sciences, computer science, and statistics in which quantitative methods and computational tools are applied to big data about people to answer social science questions. Broadly speaking there are two approaches as follows:
Population Informatics : The systematic study of populations via secondary analysis of massive data collections (termed “big data”) about people. In particular, we focus most on improving health outcomes for a population and the data science approach which is about generating actionable information from raw data. Another important aspect of population informatics is Public health informatics which is more about how to best utilize the information generated using data science to improve public health.
Simulations (i.e., Agent Based Modeling (ABM) ) : Discover useful information and knowledge about our society through simulating the actions and interactions of autonomous agents (individuals and groups/organizations). Many of the parameters to model autonomous agents come from Population Informatics research.
Foundational Publications:
Ragan, E., Kum, H.-C., Ilangovan, G., and Wang, H. (2018). Balancing Privacy and Information Disclosure in Interactive Record Linkage with Visual Masking. Proceedings of the SIGCHI conference on Human factors in computing systems. ACM. CHI2018 Honourable Mention Award (top 5% of all submissions). Also invited to be presented at the Fourteenth Symposium on Usable Privacy and Security (SOUPS) Aug 2018 as a poster.