Zeyno Dodd
R&D Architect | AI, Graph Systems, and Secure Distributed Architectures
Rockville, Maryland, United States
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Cloud Solution Architect and Researcher with 25+ years of experience in software development and applied research. Committed to leveraging AI to address complex real-world challenges with societal impact. Specializes in applying Graph Neural Networks within cloud, edge, and hybrid machine learning architectures.
Engages in transformative open-source and open-research collaborations that bridge theoretical research and production-grade systems. Recent work focuses on extending Generative AI and agentic frameworks, including agent-based RAG workflows, to practical solutions across security, healthcare, and data-intensive domains.
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From Edge to Insight: Cybersecurity Intelligence with Kubeflow, vLLM, and GraphRAG
As threats evolve across cloud and edge surfaces, modern cybersecurity demands adaptive, policy-aware AI systems that can detect, reason, and respond autonomously. In this session, we present a security-centric, federated architecture built on Kubeflow. Lightweight ONNX models run on K3s-based edge clusters to analyze Falco logs and detect anomalies locally, minimizing exposure. Only filtered signals and key features are shared to uphold compliance with GDPR, HIPAA, and zero trust principles. In the cloud, KubeFlow orchestrates a GraphRAG pipeline powered by vLLM and Knowledge Graph reasoning aligned to NIST and MITRE ATT&CK. This architecture supports detection, intelligent recommendations and rule automation—such as policy and rule updates—deployable back to the edge. Designed for high-stakes environments like healthcare, OT, and critical infrastructure, this session equips security and DevSecOps teams with practical tools to implement self-improving, compliance-aligned AI defenses.
Future-Proofing Compliance: Leveraging Knowledge Graphs and AI in Cybersecurity
Traditional approaches to cybersecurity compliance are being redefined in an era marked by rapidly evolving cybersecurity threats and stringent compliance requirements. This session explores the innovative integration of Knowledge Graphs (KG) and Retrieval Augmented Generation (RAG) with Generative AI to address the ever-evolving complexities of cybersecurity frameworks like NIST CSF v2.0, NIST 800-171, and CMMC. I will briefly delve into an open-source proof-of-concept demonstrating how these technologies can automate the discovery of compliance relationships and streamline cross-framework assessments. Join me in discovering how we can significantly enhance cybersecurity measures by harnessing open-source tools and AI, reducing the resource burden, and maintaining timely and robust adherence to evolving standards.
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