I will ecg signal processing, arrhythmia detection, and biomedical data analysis

Turn your ECG/biomedical signal data into working, evaluated deep learning models.

I'm a Biomedical Engineering student with hands-on hospital research experience (Armed Forces Institute of Cardiology) and a strong focus on ECG signal processing and deep learning.

What I can do for you:

Clean, filter, and preprocess ECG/biomedical signal data

R-peak detection, RR-interval analysis, feature extraction

Build CNN-based deep learning models for classification, detection, or biometric verification

ArcFace-based verification

GAN-based synthetic signal generation

Model training, evaluation, and performance reporting (accuracy, EER, confusion matrices)

Clear documentation suitable for academic papers, theses, or research use

Tools: Python, TensorFlow, MATLAB, NeuroKit2

Why work with me:

I recently took a biometric verification model from broken training to a research-grade result (0.56% EER), diagnosing issues like optimizer state bugs and flawed validation splits along the way. I bring the same rigor and attention to detail to every project.

Great for: FYP/thesis support, research reproducibility, dataset preprocessing, model debugging, and academic paper-ready results.