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DHS Touts Centers of Excellence National Security Efforts

Department of Homeland

Security

DHS Touts Centers of Excellence National Security Efforts

The Department of Homeland Security is leaning on its centers of excellence for technology-driven solutions to national security threats, an official said.

DHS Chief Medical Officer Pritesh Gandhi said the department’s scientific minds are exploring how machine learning and data analytics can combat issues like climate change, biological threats and domestic terrorism, Federal News Network reported Thursday.

Gandhi said he is confident in the COEs’ technical capabilities and that he is more concerned with what priorities they will tackle moving forward.

The CMO highlighted an opportunity for COEs to create medical countermeasures against biological threats.

“There’s an opportunity to do risk modeling and build risk matrices across all of the sectors – as a way to help us think through how we respond to bio threats, and how we actualize the resources that we have,” Gandhi said during the DHS Centers of Excellence Summit.

DHS can also help combat the opioid crisis by using geospatial mapping to identify concentrations of depression, a sign of potential narcotics abuse, Gandhi said. 

According to the official, such mapping techniques can be performed without sacrificing individual privacy or data integrity.

DHS has also tasked its COEs to prevent domestic terrorism in crowded places. Retired Coast Guard Rear Adm. Christopher Tomney, director of the department’s Office of Operations Coordination, said his office works with state-level partners to deploy aerial surveillance drones at large public events.

Tomney said the challenge is in ensuring that the drones do not endanger the crowd, in addition to having a robust enough monitoring capability.

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Category: Federal Civilian

Tags: biological threat Center of Excellence Christopher Tomney climate change CoE data analytics Department of Homeland Security DHS DHS Centers of Excellence Summit domestic terrorism federal civilian Federal News Network machine learning Pritesh Gandhi UAV