I study Computer Science at UCF. Most of what I actually know came from building something, breaking it, and then figuring out why it broke.
Right now I split my time between research code, coursework, and whatever side project I got curious about that week. I like systems programming and machine learning, and I'll pick the readable solution over the clever one almost every time.
School UCF, Computer Science
Research Bioinformatics lab
Interests Systems, ML, GPUs, Impactful Solutions, Fast Code, good tooling
Also into Hackathons, game dev, automating small annoyances
Looking for SWE internships and research positions
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Reads American Sign Language and speaks it out loud. Most of the effort went into getting usable data, not the model.
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A robot control stack in NVIDIA Isaac Sim. An LLM plans the task, PPO trains the skills, and a fused CUDA/C++ reward kernel keeps policy training real time. I distilled the trained policies down into a CNN vision policy and hit 78% success across 100 randomized layouts in my own eval harness.
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Research code from the lab I work in at UCF. Large datasets, C++, and a lot of profiling.
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Runs agents across multiple machines and keeps them in sync. Started as an excuse to learn distributed systems properly.
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CUDA-accelerated algorithms and primitives for machine learning and information retrieval, used as building blocks across the RAPIDS stack.
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A 3D model viewer written in C#, built together with @KahlenHernani.
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Happy to talk about a project, a paper, or a problem you're stuck on.