I'm Klest Dedja, a PhD graduate in Explainable AI, specialized in Survival Analysis. My research at KULeuven-KULAK, under the supervision of Prof. Celine Vens has been focused on making models interpretable and trustworthy for critical decision-making, especially in high-stakes setting such as healthcare. I have explored Random Forests extensively, as their inherent structure provides both flexibility in predictive modeling and potential pathways to interpretability.

• If coding in my free time (erm... not very often), I am most likely maintaining and evolving a project from my PhD years, namely BELLATREX: an open-access pip package designed to support adoption and transparency of Random Forest models for several prediction tasks: binary classification, regression, survival-analysis, multi-lablel classification, and multi-target regression.

  Do you like BELLATREX? I am looking to collaborate with researchers or practitioners to make BELLATREX better! If you have fresh ideas, feature requests, or are interested in contributing to new functionalities, I’d love to connect 😊. Keep an eye on the repository and don't forget to add a ⭐️

Well, it depends:

• For a professional connection, you find me on LinkedIn: Klest Dedja. Please mention that you found me though the GitHub page if that was the case.
• If it's about a bug or feature request for BELLATREX, please open an issue or Pull Request in the corresponding repository. We will get in touch like that for sure!