Harish Janardhanan

Talk Title:

Toward Resilient AI Systems: Adaptive Cyber Defense and Privacy-Preserving Intelligence at Scale

Abstract

Dependable AI requires security, privacy, scalability, and sustainability. This talk presents three research pillars: adaptive cybersecurity, federated learning for privacy-preserving edge intelligence, and hierarchical RL for autonomous systems. This talk presents a unified framework combining Hierarchical RL for coordination, RAG for knowledge retrieval, and MCP for tool execution. Drawing on IEEE research, this provides practical guidance for building dependable, cost-effective AI systems across various industries.

Profile

Harish Janardhanan is an IEEE Senior Member and Distinguished Fellow of the Soft Computing Research Society. He holds a Master of Science degree from Boston University, USA. With over two decades of experience as a technology leader, he currently serves as a Software Development Manager at a leading global e-commerce company, bridging academic research and enterprise engineering. His IEEE research focuses on AI security, data privacy, and systems that can operate autonomously. His contributions have been recognized with the Apex Award and the International TechXcellence Leadership Award for advancing intelligent, dependable, and cost-aware AI systems across industries. He is a peer reviewer for numerous IEEE conferences, committed to elevating the field through shared learning and rigorous scholarship.