Abstract
Human-AI team aims to overcome the lack of flexibility as a limiting factor of current Industry 4.0 while ensuring the role of the human being in the future industrial scenario by means of a human centered AI collaboration. To this aim, the project will rely on the combination of advanced methods for the representation of complex manufacturing processes by means of a novel approach which combines knowledge graphs and relational machine learning to realize true human-AI teaming working schemes, thus answering the actual needs of the industry.
TEAMING.AI‘s paradigm will be particularized and materialized in three manufacturing scenarios with different challenges and requirements in terms of AI: a) agile production with high diversity of products and high frequency of process changes (quality inspection), b) knowledge-intensive processes such as process diagnostics for complex machines (injection moulding), and c) harm prevention in challenging human-machine.
Presenter’s Outline:
• Ph.D. in Computer Science and Technology from Nanjing University, China.
• Post-Doc Researcher at SCCH, Austria.
• Assistant Professor at Department of IT&CS, PAF-IAST, Haripur, Pakistan.
Presenter’s Biography:
Maqbool Khan received his MS degree in Information Security from Huazhong University of Science and Technology (HUST), Wuhan, China in 2013 and PhD degree in Computer Science & Technology from Nanjing University, China in 2018. He worked as a Big Data Solution Architect and Data Scientist at Siemens and Atos China for several years. He has published several research papers in well reputed peer reviewed international conferences and journals. He is also Google certified Professional Cloud Architect. Currently, he is working on Human-AI teaming project with SCCH Austria team. His research includes industrial big data analytics, trustworthy and Interpretable AI, shared mental models and predictive maintenance in Industry 4.0 domain.