ABSTRACT: Autonomous systems are rapidly moving from research labs into the real world, powering drones, self-driving cars, and service robots. Yet, their widespread adoption hinges not only on performance, but on assurance—the ability to guarantee that robots do what they are intended to do, safely and reliably, even under…

ABSTRACT: The revolutionary capabilities of AI with machine learning have enabled an increasingly broad range of applications, which has brought many new challenges in ensuring the trustworthiness of AI applications. In this talk, I will present our research on trustworthy AI with verifiable guarantees. I will first introduce our…

ABSTRACT: Recent advancements in machine learning, while powerful, are often burdened by significant computational and memory requirements, limiting their deployment in resource-constrained settings. Hyperdimensional Computing (HDC) emerges as an alternative with its simplicity, lightweight operations, and robustness to errors in…

ABSTRACT: In an era of rapid AI progress, leveraging accelerated computing and big data has unlocked new possibilities to develop generalist AI models. As AI systems like ChatGPT showcase remarkable performance in the digital realm, we are compelled to ask: Can we achieve similar breakthroughs in the physical world — to create…