Harshavardhan Peddireddy

Talk Title:

AI-Driven Data Privacy and Sustainable Computing: Architecting a Resilient and Responsible Future

Abstract:

As artificial intelligence becomes embedded in critical infrastructure across healthcare, financial services, and retail, two obligations now sit at the center of enterprise architecture: protecting the individuals whose data fuels these systems, and building pipelines that remain sustainable, resilient, and trustworthy over time. This keynote examines how these obligations converge in practice. Drawing on more than eighteen years of enterprise experience under regulatory regimes such as HIPAA and PCI-DSS, the talk traces the evolution of privacy engineering from masking, tokenization, and de-identification toward AI-driven approaches, with synthetic data generation as a central case study. It introduces a practitioner framework distinguishing statistical fidelity from business logic fidelity, showing how synthetic data can pass every standard evaluation while silently violating the operational rules real systems depend on, and how the same blind spots weaken privacy guarantees through residual disclosure risk. The session engages the audience directly, inviting them to judge at key points whether a dataset is safe to release and whether a model trained on it will hold in production, before each answer is revealed. The talk closes with an architectural agenda for responsible AI data pipelines: privacy and utility evaluated together, governance built into generation rather than bolted on, and sustainability treated as a property of the entire data lifecycle. Participants leave with a concrete auditing checklist and an open research agenda for making privacy, fidelity, and resilience measurable in one framework.

Profile:

Harshavardhan Peddireddy is a Platform Data Architect and privacy engineering specialist with over eighteen years of enterprise experience across healthcare, financial services, and retail. His work centers on data masking, synthetic data generation, tokenization, de-identification, and AI governance, with a focus on building privacy-preserving data pipelines that meet HIPAA and PCI-DSS requirements. He holds the PMP, CIPP/US, AIGP, and CDPSE certifications, and is designated a Fellow of Information Privacy (FIP) by the IAPP. He is a Senior Member of the IEEE and a PhD Candidate in Artificial Intelligence at the University of the Cumberlands. Harshavardhan is recognized for his contributions to shaping the next generation of AI innovators and his expertise in integrating AI with cybersecurity and cloud security to address complex real-world challenges.