Professor Homayoun and Team Awarded NSF RAPID Funding for Covid-19

Please join us in congratulating Prof. Houman Homayoun (Electrical and Computer Engineering) in collaboration with Johns Hopkins, Morgan State, and George Mason University Epidemiologist, for receiving National Science Foundation RAPID funding for COVID-19.

The RAPID project, led by UC Davis, will develop models for the COVID-19 pandemic, looking at community spread and mitigation measures for better and scalable policy alternatives to full lockdown. NSF RAPID funds quick-response research of severe national urgency. 

In the last decades emergence of epidemics SARS, Ebola, H1N1, and influenza cause death to thousands of people. In modernized society with tight connectivity between the cities, current measures such as lock down of states was considered in the event of epidemics, in particular for the most recent COVID-19. Despite the effectiveness in slowing down epidemics, isolating the cities cripples the communication, and integrity, yet does not show a guarantee epidemic confinement. This was clearly showed by in recent quarantine measures adapted by various states. A major challenge observed was that for major cities, their health policies and protocols are deviate from one another. Thus, without a global collaborative approach, progress towards working for a cure and universally acceptable policy approach can take longer.

This project focuses on developing models for the COVID-19 pandemic, in particular looking at neighboring community spread and mitigation measures. This project aims to (i) devise a better and scalable alternative to full lockdown; and (ii) devise a cognitive solution that can be applied to various demographics having heterogeneous connectivity and population distribution with minimal information regarding previous epidemic spread. Houman Homayoun’s team at UC Davis will work with epidemiologists at Johns Hopkins and Morgan State as well as George Mason University, and will employ a collection of novel mathematical techniques to the problem that can handle heterogeneity and are scalable. 

This project was awarded under NSF RAPID which is highly competitive program used when there is a severe national urgency with regard to availability of, or access to, data, facilities or specialized equipment, including quick-response research on natural or anthropogenic disasters and similar unanticipated events.