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UID:https://events.ucf.edu/event/4197575/dod-jsto-dtra-program-managers-visit-ucf/
DTSTAMP:20260910T100000
DTSTART:20260910T100000
DTEND:20260910T120000
LOCATION:Live Oak Ballroom/Magnolia Room

SUMMARY:DOD JSTO / DTRA Program Managers Visit UCF
URL:https://events.ucf.edu/event/4197575/dod-jsto-dtra-program-managers-visit-ucf/
DESCRIPTION:You're invited to meet Joint Science and Technology Office (JSTO)/Defense Threat Reduction Agency (DTRA)  Program Managers Tyler Miller and Dr. Jennifer Soliz.\n\nPlease [register to attend](https://ucf.qualtrics.com/jfe/form/SV_4249uQBnia0YD0G) by Sept. 3.\n\nThe JSTO within the DTRA will present an overview of the U.S. Department of War Science and Technology's efforts to advance chemical, biological, radiological, and nuclear (CBRN) detection capabilities, with particular emphasis on the development of low-size, weight, and power (SWaP) microsensors.\n\nThe discussion is intended to introduce the UCF research community to JSTO's CBRN detection mission and technical challenges while fostering dialogue with faculty and researchers whose expertise could contribute to future low-SWaP sensing technologies and other emerging CBRN detection capabilities.\n\nAdditional Details: The seminar will discuss scientific and technical challenges associated with detecting, identifying, and characterizing CBRN hazards in complex operational environments, as well as the research needed to enable the next generation of compact, sensitive, and deployable sensing technologies. A central focus will be the development of miniaturized, low-SWaP sensors to support distributed, persistent and autonomous detection architectures.\n\nTopics will include emerging approaches to chemical and biological sensing and identification; microsensor and microfabrication technologies; sensor miniaturization and integration; power, sensitivity, selectivity, and performance tradeoffs; autonomous and distributed sensing; multi-modal sensor integration; and the application of data analytics, artificial intelligence, and machine learning to improve detection and characterization.\n\nThe seminar will also explore how advances in materials science, microelectronics, photonics, nanotechnology, microfluidics and related disciplines could contribute to future CBRN microsensor capabilities. Particular attention will be given to research that can reduce sensor size and power requirements while maintaining the performance necessary for operationally relevant detection.\nRegistration Link: https://ucf.qualtrics.com/jfe/form/SV_4249uQBnia0YD0G\nRegistration Info: Register to attend by Sept. 3.
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