I build and ship deep learning systems for medical imaging — training image models, wrangling large-scale clinical datasets, and turning research ideas into reproducible, GPU-ready pipelines. My day-to-day lives in PyTorch: designing model architectures, writing data pipelines for chest X-ray / retinal / MRI / CT, and running distributed experiments.
I care about clean, reproducible code, scalable training infrastructure, and building computer vision models that actually work on messy real-world clinical data.
Languages
Deep Learning & ML
Neural network architectures · Transformers · Distributed / multi-GPU training · Model training & evaluation pipelines
Focus Areas Medical Imaging · Computational Imaging · Computer Vision · Image Segmentation & Classification · Chest X-ray · Retinal · MRI · CT
Tooling
