Research Projects

HEALS: Health Empowerment by Analytics, Learning, and Semantics

The HEALS project applies advanced cognitive computing capabilities to help people understand and improve their own health conditions. In particular, we are exploring areas including personalized and mobile medical care, improved healthcare analytics, and new data-based approaches to driving down the cost of medical care.

Health INCITE: Health Informatics Challenges in Technology Education

This project recruits and prepares students at Rensselaer and worldwide to be data scientists in healthcare using early data analytics courses and experiential research projects centered on real-world health challenges.

MORTALITYMINDER: Enabling healthcare researchers, providers, payers, and policy makers to gain actionable insights into how, where, and why midlife mortality rates are rising in the United States

MortalityMinder (MM) is a web-based visualization tool that enables interactive exploration of social, economic and geographic factors associated with premature mortality among mid-life adults ages 25-64 across the United States. Using authoritative data from the CDC and other sources, MM is a freely available, publicly-accessible, open source, and easily maintained tool. The goal of MortalityMinder (MM) is to enable healthcare researchers, providers, payers, and policy makers to gain actionable insights into how, where, and why midlife mortality rates are rising in the United States (US). It is designed to help healthcare payers, providers and policymakers at the national, state, county and community levels identify and address unmet healthcare needs, healthcare costs, and healthcare utilization.

Privacy-Preserving Synthetic Health Data for Research and Education

The inability to share private health data can severely stifle research and innovation in health informatics. Studies based on unpublished electronic medical record (EMR) data cannot be reproduced, thus future researchers are not able to use them to develop and compare new research. This contributes to the reproduciblity crisis in biomedical research. Making open data available for research can spur innovation and research.

SCALES: Smart Contracts Augmented with LEarning and Semantics

This project addresses the challenge of agent driven smart contracts on the blockchain with semantics, advances in machine learning, and state of the art in multi agent systems research.