Dr.-Ing. Hasan Tercan

Scientific Researcher

Head of the Research Field "Industrial Deep Learning"

Area of Research:

• Machine Learning and Deep Learning
• Industrial Artificial Intelligence
• Transfer Learning and Lifelong Learning
• Deep Reinforcement Learning

Biography

Hasan Tercan has been a scientific research at the Institute for Technologies and Management of Digital Transformation at the University of Wuppertal since December 2018. At the same time, he is the head of the Industrial Deep Learning research group. In his work, Mr. Tercan deals with the research, development and realization of machine learning and artificial intelligence methods in the industrial context. Central use cases are AI-based quality assurance in production and intelligent planning and control of manufacturing and assembly processes.

Mr. Tercan received his PhD in 2023. In his dissertation entitled "Machine Learning-based Predictive Quality in Manufacturing Processes", he investigated the use of machine learning techniques for quality prediction in manufacturing. Two main research topics of the dissertation are the development of simulation-to-reality transfer learning approaches to use low-cost training data from manufacturing simulations, and continual learning methods to efficiently train artificial neural networks across changes in the manufacturing process. For his dissertation, Mr. Tercan was awarded the Ph.D. Prize of the Friends and Alumni Association of the University of Wuppertal (FABU).

Mr. Tercan studied computer science at the Technical University of Darmstadt. He specialized in database systems and data mining. In his master thesis he investigated the use of machine learning methods in the insurance sector. Afterwards, he worked as a research assistant at the Chair of Information Management in Mechanical Engineering at RWTH Aachen University, where he developed AI methods in a production context on various research and development projects.

Publications