Mr. Wolfgang Rannetbauer | Data Science | Best Researcher Award.

Wolfgang Rannetbauer at Voestalpine Stahl GmbH, Netherlands

Professional Profiles:

👨‍🎓 Bio Summary:

Wolfgang Rannetbauer is a dedicated data scientist and statistician with a strong background in machine learning, data analysis, and statistical modeling. Currently pursuing his doctorate in Technical Sciences – Mathematics at Johannes Kepler University Linz, Wolfgang combines academic rigor with practical experience in various industries. His research focuses on the application of machine learning and statistical methods to solve complex problems, particularly in industrial settings.

🎓 Education:

Doctorate in Technical Sciences – Mathematics (Ongoing)

Institution: Johannes Kepler University Linz

Topic: Data-driven development and enhancement of operational equipment

Start Year: 2022

Master’s in Statistics / Data Science (2019 – 2021)

Institution: Johannes Kepler University Linz

Thesis: Interpretability of supervised machine learning methods

Bachelor’s in Statistics (2016 – 2019)

Institution: Johannes Kepler University Linz

Thesis: Einsatz neuronaler Netze zur Prognose des Ausgleichsenergiepreises (Application of Neural Networks to Predict Balance Energy Prices)

Professional Experience: 💼

Wolfgang Rannetbauer has a diverse background in data science, statistics, and teaching. Since 2022, he has been working as a Freelance Data Scientist at Voestalpine AG, where he focuses on data-driven development and enhancement of operational equipment as part of his doctoral research. In 2021, he served as a Statistician at Tractive, utilizing statistical methods and machine learning techniques to analyze data and identify key influencing factors. In 2020, Wolfgang worked as a Methodology Analyst at Statistik Austria, where he was involved in analysis, reporting, and modeling tasks. Additionally, he has been a Lecturer at Johannes Kepler University Linz since 2019, teaching introductory and advanced statistics courses such as Descriptive Statistics, Statistics I, and Statistics II.

Research Interest:

Wolfgang’s research interests include machine learning, data analysis, statistical modeling, Bayesian statistics, time series analysis, and the application of artificial intelligence in industrial and commercial contexts. His work aims to enhance the interpretability and applicability of machine learning methods, particularly in the context of industrial data-driven decision-making.

📚 Top Noted Publications :

Title: Enhancing Predictive Quality in HVOF Coating Technology: A Comparative Analysis of Machine Learning Techniques

Authors: Wolfgang Rannetbauer, Christian Hambrock, Simon Hubmer, Roland Ramlau

Journal: Procedia Computer Science

Year: 2024

Volume: 232

Pages: 1377–1387

Author Metrics 📊 :

Wolfgang’s research has had a notable impact, as evidenced by his author metrics, including citations and h-index.

📅 Research Timeline:

Wolfgang’s research journey began with his Bachelor’s thesis on neural networks for energy price prediction. He then progressed to his Master’s thesis on the interpretability of supervised machine learning methods. Currently, he is focused on his Ph.D. research on the data-driven (further) development of operating resources.