The 2025 Homeland Protections Systems Workshop (HPTW) at MIT Lincoln Laboratory will center on utilized study and technological know-how advancement for more resilient and safe U.S. crucial infrastructure. Subjects pertinent into a broad audience incorporate the modernization from the U.S. electric grid, operational technologies cybersecurity, and also the interdependencies that exist between sectors of critical infrastructure.
All operates that relate to collision-absolutely free path planning or navigation for a number of brokers are welcome, including but not restricted to:
“I was actually excited to view how alive Airmeet appeared. The first time I raised my virtual hand to talk to an issue, I had been introduced up on stage, my digicam flipped on, and I was able to speak with the presenters, which was the marketed-minute in my head!
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The workshop will element a wide choice of perspectives from your DoD, DHS, state/local stakeholders, and critical infrastructure house owners/operators. Recent highlights in utilized study and technological know-how progress is going to be provided by subject matter professionals and innovators Doing the job to deal with probably the most urgent issues. This workshop is by invite only. All attendees are required to be U.S. citizens.
Together with the following exploration themes, we motivate novel contributions from scientists that convey unique perspectives on the Main concentration with the workshop:
This workshop addresses vital troubles in improving trustworthiness and reliability in genuine-entire world configurations, rendering it a important discussion for academia and business.
This workshop is geared toward gurus, scientists and policymakers considering implementing AI to community health, education, environmental monitoring and social products and services.
Given get more info that the AI Local community improvements in establishing human-like algorithms, it can be very important to be familiar with their implications for scalable and productive AI units. While AI excels at little-scale details responsibilities, running substantial-scale, dynamically increasing datasets provides new problems. Addressing these requires collaboration concerning academia and market, focusing on both equally essential analysis and used technologies.
We also welcome contributions that use present benchmarks to demonstrate safety or AI devices or discover unsafe behaviors.
We invite submissions to the theoretical foundations, algorithmic tactics, and sensible tactics to ensure the accountable deployment of AI models. The topics of fascination include, but are certainly not limited to, the next:
Recognized papers will probably be introduced within the workshop and included in a workshop continuing, Except opted out via the authors.
This workshop will take a look at the purpose of information in AI basic safety, with a particular emphasis on knowledge-centric AI approaches as well as their current limitations over the AI lifecycle.
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