We are developing transformative and scalable computing and data science technologies to address fundamental problems in real-time epidemic science. Learn more by selecting a topic below.


Forecasting and Situation Assessment for Real-Time Epidemic Science 

With the increased interest in epidemic forecasting and situational assessment during the COVID-19 pandemic, our team members have been actively involved with state and federal agencies.



Computational Foundations

Our team is developing fundamental and generalizable computational advances in science and engineering of MSML networks; AI, theory-guided machine learning, and massive data science; and calibration, validation, and uncertainty quantification.




Pervasive Scalable Technologies & Cyber-environment

We will use innovative computing to advance epidemiological science in the areas of scalable high-performance simulations, analytics, & ML and a cyber-environment for real-time epidemic science.



Applications to Epidemic Science

We have built cohesive teams to actively engage on problems of societal importance, focusing on multi-scale, multi-factor, multi-layer network modeling and planning and response for real-time epidemic science.