About Me

I’m Aidan, a computer science graduate student who likes building practical systems with clean, straightforward interfaces. My recent work includes containers and networking, computer vision, and small machine learning projects as well as the website you're viewing now.

I focus on end-to-end projects: collect useful data, process it efficiently, and present it through a fast interface. I prefer readable code, predictable infrastructure, and a small footprint. When I bring in deep learning, it's to enable a clear capability such as smoothing a vision pipeline, ranking items, or improving a tool’s decisions.

At a glance

Selected projects

• KVALD: local dimming and vision pipeline with a U-Net in PyTorch, Dockerized, using OpenCV and Eigen.
• BardBot: Discord bot that records and transcribes D&D sessions with OpenAI's Whisper architecture, providing automatic summary generation.
• Synthetic SCADA Network Traffic Generation: A synthetic SCADA packet generator intended to enable researchers to create realistic network traffic when real-world datasets are limited or unavailable.
• Cloud Storage Systems Benchmarking: A cloud-based database benchmarking framework designed to compare storage systems under realistic, repeatable workloads.

Contact

You can reach me via my LinkedIn, which is linked in the footer. I’m happy to chat about project work, systems problems, collaboration ideas, or employment opportunities.