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daavidhf/README.md

Hi, I'm David 👋

MSc student in Health Data Science (URV, in collaboration with UB, UAB, UPC, UdG, UdL, UVic-UCC & Grenoble Alpes) | BSc Biomedical Engineer & BSc Industrial Electronics and Automatic Control Engineer (UPC, Barcelona)

I work at the intersection of biomedical engineering and applied data science: signal processing, clinical data pipelines, and ML/AI systems for healthcare — with hands-on exposure to cloud infrastructure (AWS) and reproducible computing (Snakemake, SLURM, Docker).

  • 🔬 Currently: clinical data analytics on ICU signal data, co-author on an accepted IEEE EMBC 2026 paper

  • 🧠 Interests: clinical NLP & EHR, medical imaging, survival analysis, MLOps for health data, cloud architecture for regulated environments

  • 📍 Based in Barcelona, Spain

  • 📫 Reach me: hidalgo.fabregas.david@gmail.com · LinkedIn

🧰 Core stack

Python R SQL scikit-learn PyTorch TensorFlow NetworkX · AWS (EC2, S3, Lambda, VPC) Docker SLURM Snakemake · MIMIC-III DICOM ECG/PPG

📌 Featured projects

  • CHD Risk Classifier FastAPI-Docker (team project — forked, my contribution highlighted in the README) — End-to-end ML pipeline classifying 10-year coronary heart disease risk on a 4,000+ patient cohort; I led the FastAPI service design and Docker deployment, and coordinated the team's technical review.

  • HPC SLURM Job Orchestrator — Python orchestrator for dependent, distributed job executions on a SLURM-managed HPC cluster: job arrays, dependency chaining, and automated result consolidation.

  • BioInformatics Sequence Analysis — Reproducible bioinformatics pipeline (FASTA parsing, DP sequence alignment, CIGAR analysis) orchestrated end-to-end with Conda + Snakemake.

  • CS50AI — Portfolio of Harvard CS50 AI problem sets (search, knowledge/logic, Bayesian inference, CSPs, RL, CNNs, NLP), each documented with design decisions and results.

  • ATP Match Predictor (🚧 work in progress) — Random Forest model estimating a player's win probability, compared against market-implied probabilities from bookmaker odds to flag pricing discrepancies; leak-free walk-forward validation and dynamic feature engineering. (rolling form, surface-aware H2H).

(See pinned repos below for details, code, and READMEs.)

Pinned Loading

  1. chd-classifier-api chd-classifier-api Public

    Forked from koershuis/SP_Final_Project_E

    Random Forest pipeline classifying 10-year coronary heart disease risk (4,000+ patient cohort), deployed as a FastAPI service in Docker. Team project — my role: API design & deployment.

    Jupyter Notebook

  2. alzheimer-semantic-network-classifier alzheimer-semantic-network-classifier Public

    Graph-based classifier separating Alzheimer's patients from healthy controls using semantic networks built from verbal fluency data, community detection, and Random Forest — extends the Zemla & Aus…

    HTML

  3. hpc-slurm-orchestrator hpc-slurm-orchestrator Public

    Python orchestrator for dependent SLURM job arrays on an HPC cluster — dynamic task discovery, parallel job-array computation, and a dependency-gated consolidation phase.

    Python

  4. BioInfo-SeqAnalysis BioInfo-SeqAnalysis Public

    Reproducible bioinformatics pipeline: FASTA parsing, DP sequence alignment with CIGAR traceback, and regex-based stats — fully automated as a Snakemake DAG in an isolated Conda environment.

    Python

  5. clinical-ml-clustering-classification-rnn clinical-ml-clustering-classification-rnn Public

    Forked from Joaomuianga/ML-team-collaboration

    Clinical ML across three paradigms: patient clustering (K-Means, GMM, Hierarchical) on Heart Disease UCI, tumor classification (KNN, LogReg, SVM, Neural Nets) on Breast Cancer Wisconsin, and arrhyt…

    Jupyter Notebook

  6. CS50AI CS50AI Public

    Project portfolio for CS50's Introduction to AI with Python course: technical summary, design decisions, demos, and results.

    Python