Highlighted Projects and Research

Explore some of my key projects like the development of a UNet for lung segmentation, climate modeling using Lagrangian Neural Networks, and diffusion models advancements.

For more information, visit my GitHub profile or LinkedIn page.

CathGrvt/UNet4LungCT
CathGrvt/DiffusionMNIST
CathGrvt/2048Game
CathGrvt/Sudoku

Skills & Achievements

I am adept in Python, Java, MATLAB, and C++, with extensive experience in machine learning frameworks such as PyTorch and Sci-Kit Learn. My projects often involve complex data processing and modeling, including the use of advanced algorithms in neural networks and statistical analysis.

Noteworthy achievements include:

  • Bayesian network prediction for lung cancer prognosis.
  • Climate modeling with Lagrangian Neural Networks.
  • Development of an energy-efficient desalination process using genetically modified cyanobacteria, recognized at the iGEM competition.

These projects showcase my ability to bridge the gap between theoretical data science and practical application, making significant contributions to the fields of medical imaging, environmental science, and healthcare.

Education & Volunteer Work

I am pursuing a Master's degree in Data Intensive Science from Cambridge and hold a Bachelor's degree in Science from the University of Maastricht. I've also actively volunteered in data science-related projects and initiatives, enhancing both my leadership and technical skills.