Andreas Selmaier
Papers
2
Total Citations
91
H-Index
2
About
Dr. Andreas Selmaier is a leading researcher at the intersection of machine learning (ML) and digital transformation, with a focus on bridging the gap between cutting-edge AI and real-world industrial applications. His work centers on two critical pillars: the practical deployment of ML in production environments and the development of agile, process-driven architectures for Industry 4.0. His most influential paper, "Machine Learning in Production – Potentials, Challenges and Exemplary Applications" (2019), with 84 citations, provides a foundational framework for understanding how to operationalize ML beyond the lab, addressing key hurdles in autonomous driving, service robotics, and natural language processing. This work is widely recognized for its pragmatic analysis of data availability, computing power, and software tooling. More recently, Dr. Selmaier has advanced the field with his 2021 paper on a reference architecture and agile development method for BPMN-standard web platforms, tackling the urgent need for resilient, knowledge-driven digital systems in the wake of COVID-19. His research is essential for engineers and students seeking to navigate the complexities of deploying robust, scalable AI solutions in volatile market conditions.
Research Focus
Key Achievements
Top Papers
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