Anjani Haritha Sannidhanam

Title of the Talk:
Building Trustworthy Autonomous AI Systems: From Self-Healing Infrastructure to Enterprise-Scale Intelligence

Abstract:
Artificial Intelligence is rapidly evolving from a tool that assists humans to a technology capable of autonomous decision-making, adaptive reasoning, and large-scale operational management. As organizations increasingly deploy AI across critical infrastructure, cloud platforms, financial systems, healthcare environments, and enterprise applications, ensuring reliability, safety, and resilience has become a strategic global priority.

This keynote explores the next generation of intelligent systems and the technological foundations required to build trustworthy autonomous AI. Drawing from recent research in autonomous AI agents, self-healing distributed systems, large language model (LLM) reliability, and AI governance, the presentation examines how modern AI architectures can move beyond prediction toward proactive problem solving and operational autonomy.

This keynote is intended for researchers, industry practitioners, policymakers, and technology leaders interested in the future of artificial intelligence, engineering data analytics, and intelligent enterprise systems.

Bio:
Anjani Haritha Sannidhanam is a Software Development Engineer II at Amazon.com Services LLC and an AI researcher specializing in autonomous AI systems, cloud infrastructure, distributed systems, and enterprise-scale machine learning applications. With extensive experience designing and building large-scale distributed platforms, she focuses on developing intelligent systems that improve reliability, scalability, and operational efficiency in modern cloud environments.

Her research interests include autonomous AI agents, self-healing distributed systems, large language model (LLM) reliability, AI safety and governance, prompt engineering, real-time inference systems, and event-driven architectures. Through her published work, she has explored topics such as zero-downtime AI model deployments, AI-driven failure prediction and recovery, guardrails for enterprise AI applications, and reliable LLM implementations in production environments.

Beyond her professional and research contributions, Anjani actively supports the global technology and academic communities as a peer reviewer for IEEE, Springer, and international conferences and journals, a hackathon judge, and an editorial board member for reputed scholarly journals. She regularly evaluates research in artificial intelligence, cloud computing, distributed systems, and emerging technologies, helping promote innovation and scientific excellence.

Her work bridges academic research and industry innovation, with a focus on advancing trustworthy, resilient, and scalable AI systems that address real-world challenges across enterprise and cloud ecosystems.