Lehrstuhl SRS

Dominik Polke, M.Eng.

Hochschule Niederrhein

2021	M.Eng. in Electrical Engineering, Faculty of Electrical Engineering and Information Science, University of Applied Sciences, Krefeld, Germany
2019	B.Eng. in Electrical Engineering, Faculty of Electrical Engineering and Information Science, University of Applied Sciences, Krefeld, Germany

Polke, D.; Ahle, E.; Söffker, D.: Adaptive Learning with Gaussian Process Regression: A Comprehensive Review of Methods and Applications. MDPI Machine Learning and Knowledge Extraction (MAKE), 2026.

Polke, D.; Ahle, E.; Söffker, D.: Data-Driven Modeling Frameworks for Industrial Cyber-Physical Systems: A Systematic Review. 9th IEEE International Conference on Industrial Cyber-Physical Systems (ICPS), Perth, Australia, 11.-14. May, 2026.

Polke, D.; Surjana, A.; Hoseini, S.; Wagner L.; Göttert, J.; Quix, C.; Ahle, E.: Development of an Automation Framework for Data-Driven Modeling and Adaptive Learning in Industrial Processes. 9th IEEE International Conference on Industrial Cyber-Physical Systems (ICPS), Perth, Australia, 11.-14. May, 2026.

Polke, D.; Wulf, B.; Ahle, E.; Söffker, D. : Fully Bayesian Anisotropic Polynomial Chaos Expanded Gaussian Process for Active Learning. 2026 13th International Conference on Soft Computing & Machine Intelligence (ISCMI), Vienna, Austria, 18.-20. November, 2026, 1-10, submitted.
Wulf, B.; Polke, D.; Ahle, E.; Söffker, D. : Non-stationary Input Dependency Identification via Anisotropic Chaos Expanded Gaussian Processes. 2026 13th International Conference on Soft Computing & Machine Intelligence (ISCMI), Vienna, Austria, 18.-20. November, 2026, 1-8, submitted.
Polke, D.; Kösters, T.; Ahle, E.; Söffker, D.: Polynomial Chaos Expanded Gaussian Process. MDPI Machine Learning and Knowledge Extraction (MAKE), 2026.

Polke, D.; Ahle, E.; Söffker, D.: Bayesian Active Learning with Polynomial Chaos Expanded Gaussian Process. 2026 3rd IEEE International Conference on Artificial Intelligence, Computer, Data Sciences and Applications, Boracay Island, Philippines, 5-7 February, 2026.

Hoseini, S.; Zhang, G.; Polke, D.; Surjana, A.; Wagner, L.; Schmitz, C.; Quix, C.: Coatings Intelligence: Data-driven Automation for Chemistry 4.0. 7th IEEE International Conference on Industrial Cyber-Physical Systems (ICPS), St. Louis, USA, 12-15 May, 2024, 01. Jun.

Polke, D.; Surjana, A.; Zhang, G.; Hoseini, S.; Wagner L.; Stoffelen-Janssen C.; Schmitz, C.; Göttert, J.; Quix, C.; Ahle, E.: Entwicklung eines Automatisierungsframeworks zur Mehrgr§enoptimierung in chemischen Hochdurchsatz-Prozessen. VDI-AUTOMATION 2024, Baden-Baden, 2-3 Juli, 2024, 791-806.

Wulf, B.; Polke, D.; Ahle, E.: Active Learning for Gaussian Processes Based on Global Sensitivity Analysis. 2024 23rd IEEE International Conference on Machine Learning and Applications , Miami, USA, 18-21 December, 2024, 01. Jul.

Polke, D.; Surjana, A.; Diepers, F.; Ahle, E.; Söffker, D.: Development of a Modular Automation Framework for Data-Driven Modeling and Optimization of Coating Formulations. 27th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) , Sinaia, Romania, 01. Aug, 2023, pp. 1-8.

Diepers, F.; Polke, D.; Ahle, E.; Söffker, D.: Comparison of Different Gaussian Process Models and Applications in Model Predictive Control. 23rd IEEE International Conference on Control, Automation and Systems (ICCAS), Yeosu, South Korea, 2023, pp. 54-59.

Diepers, F.; Polke, D.; Ahle, E.; Söffker, D.: Data-Driven Force Control of an Automated Scratch Test. 10th International Conference on Control, Mechatronics and Automation (ICCMA), Belval, Luxembourg, 2022, pp. 94-99.

Polke, D.; Diepers, F.; Ahle, E.; Söffker, D.: Development of a Framework for Data-Driven Modeling with Cloud Services in the Process Industry. IEEE International Conference on Automation, Robotics and Computer Engineering, Wuhan, China, 2022, pp. 109-115.