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. HAN supports consortia projects, workshops and outreach activities, and training events for widespread dissemination.

Vision and Mission

At HAN, our vision is to use the power of data for addressing health and environmental problems based on inter-disciplinary observations and rigorous studies of different sources of vulnerability, heterogeneity and uncertainty.

To achieve our mission, at HAN, we apply some key approaches that include, but are not limited to, the following:

  • fusion of data from different sources, which we synthesize together to produce models for broader understanding of complex phenomena
  • gain insights into population dynamics of interest by statistical analysis of the heterogeneity among the underlying subpopulations
  • generative models to reconstruct stochastic interactions among individuals and groups to predict rare events or emergent behavioral patterns
  • modeling of socioeconomic and environmental factors at local "small area" levels to identify and characterize community-specific disparities
  • risk communication and systems level preparedness for disasters and extreme events towards resiliency and equity of vulnerable populations

The Laboratory for 'Health and Environmental Equity through Data' (HEED-lab) is a collaborator of HAN.

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


Read More

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.


Dr. Saumyadipta Pyne

Founder and President

Dr. Meghana Desai

Co-Founder and Vice President

Dr. Saurav Guha

Research Associate

Dr. Sumanta Ray

Research Associate

Dr. Vishal Deo

Research Associate