Dr. Krutthika Hirebasur Krishnappa

Federated AI in Robotics: Securing Edge Intelligence with Quantum and NoC Technologies

Abstract:

As robotics systems increasingly operate in decentralized, real-time environments—such as autonomous vehicles, smart factories, and healthcare robotics there is a critical need for secure, efficient, and scalable AI processing at the edge. This keynote explores how Federated Learning (FL) can empower robotic platforms to learn collaboratively without sharing raw data, preserving privacy and reducing latency. To support this, Network-on-Chip (NoC) architectures enable high-speed, parallel communication across processors in edge hardware, while quantum cryptographic techniques, such as Quantum Key Distribution (QKD), enhance the security of federated updates in distributed robotic networks. The talk will highlight real-world applications, architectural considerations, and emerging research directions at the intersection of AI, robotics, quantum security, and chip-level design providing a holistic view of next-generation intelligent robotic systems.