Bruno Mendes

Physicist and Python enthusiast with over three years of experience in machine learning, data science and medical imaging. As a student of the Doctoral Program in Biomedical Engineering at FEUP, I am using machine/deep learning methods to assess the effectiveness of radiotherapy treatments for prostate cancer.

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Skills

Scikit-learn

  • Preprocessing
  • Feature selection methods
  • Regression and classification models
  • Performance metrics

Pytorch

  • U-net architecture
  • Image transforms
  • Custom datasets and dataloaders
  • TorchMetrics

Pandas

  • Data analysis
  • Data manipulation
  • Conversion to csv, json and xls
  • Queries and filtering
  • Plotting

Matplotlib

  • Data visualization
  • Image viewers
  • Dicom (medical) images volume viewer

NumPy

  • Numerical computations

OpenCV

  • Camera streaming
  • Blob detection
  • ArUco markers and calibration
  • Breathing monitoring system

SimpleITK

  • Dicom images reading
  • Filtering
  • Segmentation
  • Registration

Seaborn

  • Statistical visualization
  • Hierarchy clustering
  • Heatmaps
  • Violinplots

Django

  • Web apps
  • Rest API
  • Backend
  • SQLite3 + PostgreSQL
  • Apache + Heroku

Google Charts

  • Web apps charts

React

  • Personal small projects
  • Frontend
  • Web, desktop and mobile app development

Flutter

  • Personal small projects
  • Frontend
  • Web, desktop and mobile app development

Ongoing Projects

Prostate Cancer Aggressiveness Prediction

  • 2020

Prostate and OAR's Segmentation - UNet

  • 2021

Artificial Intelligence to Evaluate Cancer Treatment Effectiveness

  • 2022