Jordan Moshcovitis
Jordan Moshcovitis is a Machine Learning Engineer, Researcher, and Head of Applied AI with expertise across complex systems, cyber security, and AI governance for regulated environments. He has led R&D on agent architectures, decision verification systems, PII protection, and privacy compliance across healthcare, education, and critical infrastructure, with experience in APP and HPP compliance and architectural mitigation strategies for regulated sectors.
A specialist in complex systems and machine learning, Jordan has worked across academia and industry on AI model design, interpretability, and bias correction. He brings scientific depth from condensed matter physics and applied mathematics to discussions on LLM infrastructure and risk.
Your AI runs on vibes, not rules: Can you prove your agent made the right decision?
New automated decision-making disclosure laws demand a reasoning chain from autonomous agents, and this session presents primitives for runtime governance.
World-Class Speakers
Hear from the most influential leaders and experts who will discuss pressing issues and emerging trends in cyber security.
