Mr. Nishanth Sirikonda

Computational Intelligence for Trustworthy Cloud Systems: AI Models for Governance, Anomaly Detection, and Resilience

Abstract:

The rapid growth of cloud-native and distributed platforms has created complex data ecosystems where scalability and flexibility are matched by increased risk of misconfigurations, insider threats, and policy drift. Computational intelligence provides a foundation for addressing these challenges by embedding adaptive, learning-based mechanisms directly into system pipelines.

This session explores how state-of-the-art AI techniques—including large language models (LLMs), anomaly detection algorithms, and automated classification methods—can be applied to enhance governance, compliance, and resilience in modern enterprise systems. LLMs can automate access reviews and policy checks, anomaly detection models surface irregular behaviors in real time, and intelligent classification dynamically labels sensitive fields within integration workflows. Together, these approaches offer a layered security and governance model that adapts as systems evolve.

Attendees will learn how computational intelligence methods not only reduce operational risk but also streamline oversight and improve visibility across distributed environments. Real-world use cases will highlight how these methods can be extended beyond security—such as optimizing workflows, improving system transparency, and enabling self-adaptive governance.

Profile:

Nishanth Sirikonda is a Solutions Architect with over a decade of experience designing and implementing large-scale enterprise cloud solutions across global organizations. He has successfully led end-to-end system integrations, M&A transformations, and post-production optimizations for both public and private sector clients.He is certified in enterprise platforms including Workday HCM, Payroll, Absence, and Time Tracking, and is highly skilled in cloud technologies, data security, and AI-driven governance models. Nishanth has deep expertise in Workday Studio, Prism Analytics, Extend, and advanced integration frameworks, and has delivered measurable efficiencies such as reducing payroll errors through workflow automation.

Outside of his core professional roles, Nishanth holds fellow memberships in multiple scientific organizations, underscoring his recognition within the global technology community. He is an active contributor to knowledge-sharing through the IEEE Raleigh Section, where he mentors peers and promotes innovation in cloud computing and AI adoption. His career demonstrates a unique blend of hands-on technical expertise, strategic leadership in digital transformation, and forward-looking thought leadership in emerging technologies.