Presentation
During my PhD research at TU Berlin / ATB Potsdam, I worked extensively with sensor data, CFD simulation results, image-based airflow analysis, and explainable AI methods. I have experience with Python, pandas, NumPy, scikit-learn, XGBoost, LightGBM, CatBoost, Streamlit, FastAPI, and data visualization tools.
I can support projects involving data cleaning, exploratory data analysis, machine learning model development, feature engineering, model evaluation, visualization dashboards, and AI-based decision support systems. I am especially interested in applied AI, engineering data, computer vision, and real-world predictive modeling.
I am reliable, detail-oriented, and able to work independently as well as in interdisciplinary teams. My goal is to help companies use data more effectively to solve practical problems and improve decision-making.


