Experience Across Research, Systems, and Teaching
My experience combines doctoral research, low-level software development, technical instruction, reproducible experimentation, and applied project work. Each role contributes to a deliberate path toward compiler, runtime, performance, and systems engineering.
Professional Experience
Research, engineering, teaching, and applied technical work that has shaped my current expertise and future direction.
Conduct doctoral research on synthetic cybersecurity data, generative modeling, malware-image classification, reliable evaluation, and reproducible high-performance research infrastructure.
- Designed and executed reproducible experiments across GAN, VAE, diffusion, autoregressive, and probabilistic models.
- Evaluated synthetic data using KID, MS-SSIM, balanced accuracy, macro F1, macro AUPRC, and downstream utility.
- Built repeatable research workflows using manifests, fixed seeds, artifact tracking, scripts, reports, and HPC execution.
- Developed publication-focused studies on utility, selection policies, external conditioning, and trustworthy evaluation.
Supported undergraduate instruction across systems programming, computer architecture, cybersecurity, network security, and data communications.
- Assisted students with C programming, pointers, memory, files, processes, debugging, and systems interfaces.
- Supported coursework involving computer organization, instruction execution, memory hierarchy, and hardware-software interaction.
- Helped reinforce cybersecurity principles, network threats, access control, defensive practices, and secure computing.
- Reviewed technical work, clarified concepts, and provided structured feedback on correctness, design, and reasoning.
Contributed to the TruNorth initiative, including applied research and development work supporting an ROI-calculation platform for agricultural and operational decision-making.
- Helped translate operational requirements into measurable inputs, calculations, outputs, and user-facing workflows.
- Participated in system design, research coordination, validation, and technical documentation.
- Worked across technical and domain-specific concerns to support a practical decision-support application.
- Strengthened experience in applied research, stakeholder requirements, and interdisciplinary software development.
Contributed to AI-training and evaluation tasks requiring precise instructions, deterministic outputs, automated verification, containerized execution, and careful interpretation of technical requirements.
- Developed and refined tasks involving file processing, structured JSON outputs, and automated verification.
- Evaluated whether instructions were sufficiently precise for agents to produce testable and reproducible results.
- Worked with Python, Docker, command-line tools, test scripts, and task configuration files.
- Strengthened understanding of specification quality, validation, failure analysis, and agent-evaluation design.
Teaching Experience
Courses supported as a Graduate Teaching Assistant at the University of North Dakota.
Systems Programming
C programming, memory, pointers, file I/O, processes, system interfaces, debugging, and software-development fundamentals.
Computer Architecture
Processor organization, memory hierarchy, instruction execution, computer organization, and hardware-software interaction.
Computer & Network Security
Security principles, network threats, access control, defensive practices, vulnerabilities, and secure-computing concepts.
Data Communications
Networking fundamentals, communication protocols, layered architectures, data transmission, and network behavior.
Cybersecurity & Information Assurance
Security foundations, risk, information assurance, organizational context, technical controls, and defensive reasoning.
What These Experiences Build
The recurring capabilities developed across research, instruction, engineering projects, and technical evaluation.
Technical Depth
Increasing understanding of memory, systems interfaces, architecture, debugging, reproducibility, and low-level software behavior.
Clear Communication
Explaining difficult concepts, reviewing technical work, documenting systems, and translating requirements into actionable engineering tasks.
Evidence-Driven Work
Using tests, measurements, controlled experiments, metrics, automated verification, and repeatable workflows to support conclusions.
Systems Direction
Building the foundation required for future roles in compilers, runtimes, performance engineering, and dependable systems infrastructure.
Experience with a Deliberate Technical Direction
My research, teaching, and engineering work are converging toward one objective: developing the depth required to build reliable, performance-conscious compiler and runtime systems.