Health Analytics Network

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About Us

Health Analytics Network is a closely knit group of researchers with interdisciplinary expertise. HAN works with different organizations and academic institutions to conduct research, training, and networking. Our focus areas include: Health and Environment, Policy and Systems, Data Fusion and Disaggregation, Predictive Modeling and Analysis to support healthy aging. HAN supports consortia projects, workshops and outreach activities, and training events for widespread dissemination.

Vision and Mission

Driven by the power of data and Generative AI, we envision producing new insights and solutions for improved healthspan at individual and community levels.

We harness Generative AI to develop and deploy practical systems that support individuals in navigating the dynamic landscape of healthy aging.

Our AI systems provide innovative, interconnected capabilities for the necessary foresight, decision-making, and planning of the personalized trajectories of healthy aging.

To achieve our mission, our approaches include, but are not limited to, the following:

fusion of real and synthetic data for broader understanding of complex phenomena;
gain insights into population dynamics by dissecting its underlying subpopulations;
generative AI models to predict and reconstruct trajectories of unobserved events;
systems level models for disasters and extreme events for detection of resiliency;
interdisciplinary studies of systemic vulnerability, heterogeneity, and uncertainty.

Areas of expertise:

Public Health Data Science

Population Heterogeneity Modeling
Air Pollution
Carcinogenic Exposures
Environmental Extreme Events
Behavioral Risk Estimation
Public Health Disparities

Precision Bioinformatics

Prediction of Rare Events
Human Phenome Analysis
Single Cell Analysis
Cancer Informatics
Multi-omic Integration

Health Policy and Systems

Healthcare Quality and Safety
Disasters and Emergencies
Social and Environmental Determinants of Health
Polysubstance Use

Computational Statistics

Data Fusion
Augmented Reality
Small Area Estimation
Non-stationary Spatial Models
Generative Deep Learning
Agricultural and Environmental Statistics
Skew Mixture Models

Research

Platform for Modeling of Structural Phenotypes

structural degeneration in optic neuropathies such as glaucoma is characterized by neuroretinal rim (NRR) thinning of the optic nerve head and other clinical parameters.

Computational Advances in Data Fusion Methods

Data fusion is the process of integrating multiple data sources to produce better inference than that provided by any individual source. The statistical file-matching problem aims to characterize.

Calculating Probabilities of Environmental Extremes

Environmental researchers often encounter the problem of determining the probability of extreme events marked by exceedance of a high threshold of a variable of interest such as rainfall or air pollution.

A new algorithm for small area estimation

While essential for policy-making, it reliable local estimates are difficult to compute from a survey due to the limited sample size of a typical "small area". Drs. Saumyadipta Pyne and Shaina Stacy, and collaborators.