I’m a Senior Trustworthy AI Architect at NVIDIA, where I design and influence high-stakes AI systems deployed in security-, privacy-, and regulation-sensitive environments.
My work focuses on building reliable, explainable, and responsible AI in production. I specialize in machine learning security and privacy, fairness, uncertainty-aware AI, reinforcement learning, and computational models of intelligence, helping organizations move from research concepts to deployable, risk-aware systems at scale. I hold multiple patents and publications in AI and trustworthy AI. I’m a recognized industry speaker on trustworthy AI and have delivered keynotes and technical talks for TEDx, Women in Data Science, DEF CON IoT Village, the QS EduData Summit, and other global forums. Through these engagements, I advise and influence engineers, leaders, and institutions on how to operationalize responsible AI in real-world systems.
I’ve taught data science, ethical AI, and machine learning deployment across platforms including Pluralsight, Udacity, ELVTR, Educative, and Eduonix, breaking down complex technical topics into practical, actionable frameworks for practitioners and leaders. I’m a technical pathfinder with a strong commitment to open-source communities and expanding participation in STEM. I was one of the youngest employees to join Intel Corporation at age 14, and my ongoing focus is on shaping how AI systems are built, governed, and trusted at global scale.
The opinions on this website are my own.