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Brief introduction:

Deep learning research engineer – medical diagnostics.

Responsibilities:

  • Contributed to multiple AI and computer vision projects for medical diagnostics, improving classification and segmentation performance by 5% through model refinement and data-quality improvements.
  • Trained, fine-tuned, and evaluated deep learning models including U-Net, YOLOv5, ResNet, and diffusion transformers, achieving measurable gains in accuracy and robustness through systematic augmentation, hyperparameter optimization, and cross-validation.
  • Collaborated using Git and Git Flow for version control and experiment tracking, improving code reproducibility and team development efficiency in agile project settings.