Hi, I'm Hugo Gómez García
Computer Science & Mathematics double-degree student
I build software on a solid mathematical foundation. I'm drawn to artificial intelligence, machine learning, and shipping polished systems end to end.
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Featured projects
A selection of my best work, in case-study form.
Kairo — AI-assisted research automation on Claude Code
A personal research automation pipeline built entirely on Claude Code that runs literature synthesis, adversarial hypothesis critique, preregistration, and real experiments as a disciplined, auditable process instead of a single chat conversation.
Quantized GEMM Error — Isolating the two design choices behind MXFP4 vs. NVFP4
A research paper isolating what actually explains NVIDIA's claimed NVFP4-over-MXFP4 training advantage: a from-scratch quantization engine, a numerical-error bound derived from first principles, and a 1.6-million-trial factorial study pinning the advantage on scale format rather than block size.
RAG Hallucination Detector
A hallucination detector for RAG systems: a full pipeline (retrieval + generation + verification) with a model matching published state-of-the-art results, plus a research paper auditing an unexploited annotation-quality issue in the field's standard benchmark.
MCMT — Real-time multi-camera multi-target tracking
Person-tracking engine across hundreds of cameras (up to 1,300 simultaneously), combining a geometric C++ core with a graph neural network to resolve ambiguous cases.
EchoLens — Real-time in-browser audio classifier
CNN that classifies urban sounds instantly on your own device: trained in PyTorch, quantized to INT8, and running 100% on WebAssembly in the browser — no server, no audio ever leaving the device.
BioFit — AI-powered integral health ecosystem
AI coach that analyses your exercise technique in real time using computer vision, designs personalised routines, and tracks your nutrition and progress.
Clinical Fidelity Belt — Evaluation gate for AI-humanized radiology reports
A four-layer evaluation gate that decides whether an AI-humanized radiology report still preserves clinical severity well enough for a patient to read — plus a documented negative result: a transformer clinical NER backend that collapsed from 56% to 8.6% entity recall.
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Technologies
Tools I work with day to day.
Languages
- Python
- C++
- SQL
- Java
- C
Machine Learning
- PyTorch
- scikit-learn
- NumPy
- Pandas
- Scipy
Tools
- Git
- Linux
- Docker
- PostgreSQL