Hasan Tercan

RWTH Aachen University, University of Wuppertal

Papers

Total Citations

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About

Hasan Tercan is a researcher specializing in the intersection of machine learning, robotics, and smart manufacturing, with a particular focus on advancing automation for Industry 4.0 and Cyber-Physical Production Systems. His most influential contribution, "Motion Planning for Industrial Robots using Reinforcement Learning" (2017), has garnered 78 citations and demonstrated how reinforcement learning can be leveraged to make industrial robot motion planning more flexible, adaptive, and economically viable — a foundational challenge in modern production environments. Tercan has since extended his expertise into transfer learning, exploring why machine learning solutions struggle to transition from research settings into real-world manufacturing practice. His 2022 work, "Insights and Example Use Cases on Industrial Transfer Learning," with 18 citations, identifies key barriers and proposes practical pathways forward. His more recent 2023 paper on cross-robot transfer learning addresses the growing demand for intelligent robotic systems capable of dynamic adaptation across diverse platforms and processes. Collectively, Tercan's research charts a coherent trajectory toward making AI-driven automation truly deployable in industrial contexts, bridging the persistent gap between theoretical machine learning potential and practical manufacturing application.