🎓 M.Sc. Applied Statistics | 🧠 Machine Learning & AI | 💻 Software Engineering
I'm passionate about applying statistical thinking and machine learning to solve real-world problems.
Currently, I'm exploring the intersection of interpretability and generative AI in my master's thesis at BASF, and developing a Python package for ensemble-based changepoint detection.
Languages: Python, R, SQL, C, MATLAB, Java , PHP, JavaScript/TypeScript
ML / AI: PyTorch, scikit-learn, HuggingFace, XAI (SHAP, LIME)
Tools: Docker, AWS, Git, CI/CD, Tableau/Plotly
The repositories below represent a selection of my public work. Much of my professional code remains proprietary and cannot be shared. Many projects were originally hosted on GitLab (GWDG) and some have since been migrated here. Some earlier work has been lost to old laptops, servers, and Raspberry Pis over the years — such is life I guess.
kickbase_analytics
Analytics dashboard for Kickbase fantasy football
Tech: Python, Streamlit, pandas, Plotly
kaggle_competitions
Kaggle competition submissions and experiments
Tech: Python, scikit-learn, XGBoost, pandas
big_blues_portal
Web portal for university big band management
Tech: Vue.js, TypeScript, Docker
portfolio
Personal portfolio website
Tech: JavaScript, HTML, CSS
machine_learning_university_class
Machine learning algorithms and applications
Tech: Python, scikit-learn, pandas, NumPy
deep_learning_for_computer_vision_university_course
Deep learning for computer vision tasks
Tech: Python, PyTorch, CNNs, Transfer Learning
machine_intelligence_university_course
Machine intelligence and neural networks
Tech: Python, PyTorch, NumPy
advanced_statistical_programming_university_course
Advanced statistical programming and data analysis
Tech: R, tidyverse, ggplot2
operation_systems_university_course
Operating systems fundamentals
Tech: C, Java
mobile_web_app_university_course
Mobile web application development
Tech: PHP, Laravel, Blade