AI / ML·HPC·Cloud·Quantum·Power Systems
As an experienced Doctoral Researcher at the University of North Dakota, a former Computer Scientist at Pacific Northwest National Laboratory, and with prior industry experience at IBM, I have led research and engineering work spanning AI systems, cloud infrastructure, and national critical infrastructure across research and industry settings.
Applied contributions span production ML systems for power grid security, statistical anomaly detection for IT/OT environments, and agentic AI frameworks for distributed energy resource management, with peer-reviewed publications across IEEE venues.
In cloud and DevOps engineering, I design serverless AWS architectures, implement CI/CD pipelines synchronized with cybersecurity maturity assessments, and build containerized cross-environment workflows using Docker and Singularity that enable reproducible science across DOE supercomputers, cloud platforms, and institutional HPC clusters.
I create accessible technical content, contribute to tech communities, stay active through CrossFit, tennis, and golf. I value thoughtful conversations about ethics, optimism, meaningful use of time, and life beyond work.
Investigating where machine learning meets physical systems, HPC infrastructure, and deployment reproducibility.
Notes on scientific AI infrastructure, HPC workflows, reproducibility in machine learning, and energy systems research.