Panelist: Prof. Brett Savoie Title: Agents as Lab Managers Abstract: Laboratory automation will create opportunities for new experimental workflows that are data-driven and dynamically optimized. In preparation for this eventuality,
Panelist: Prof. Vahid Tarokh Title: FAST Lexicographic Agile Perception (FLAP) Integrates Decision and Control in a Spike Resolved Sensorimotor Program Abstract: In this presentation the speaker discusses some of their
Panelist: Molei Tao, Georgia Tech Title: Can diffusion generative modeling help physical sciences? Abstract: In this presentation the speaker will share some personal perspectives, largely on a recent generative AI
Title: Towards Artificial General Intelligence (AGI)-Native Wireless Systems Abstract. Next-generation wireless systems, such as 6G and beyond, are expected to tightly embed artificial intelligence (AI) into their design, giving rise to what
Title: Updating the Top Ten Ways that DDDAS Can Save the World – An Update from the World of Drug Discovery Abstract: Ten years ago (DDDAS at the 2014
TUTORIAL-3 TITLE: Predictive Digital Twins: From Design to DeploymentContributors: Michael Kapteyn, Anirban Chaudhuri, Sebastian Henao-Garcia, Prof. Karen Willcox ABSTRACT: Predictive digital twins have the potential to underpin intelligent automation across engineering, science, and
TUTORIAL-2 TITLE: Federated Learning – Introductory Tutorial ABSTRACT: Federated Learning (FL) is a modern paradigm in the field of machine learning, enabling collaborative model training across multiple decentralized agents while preserving data
TUTORIAL-1 TITLE: Adversarial Learning: Secure and Robust AI (*) ABSTRACT: This tutorial covers approaches that prevent malicious interference and adversarial perturbations in (continuous) training and deployment of Deep Neural Networks. Deep learning, including
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