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Keynote Speakers
Industrial Keynote
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Jean-François GERMAIN Digital Transformation and Information Technology / STMicroelectronics
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How high tech industry can move to lights-out manufacturing?
Chip fabrication process provides an overview of the complexity and challenges addressed daily within the manufacturing plant. It emphasizes the importance of integrating IT systems with manufacturing machines. This process operates in the realm of nanometers, where highly complex procedures are executed by advanced and expensive equipment in an environment purer than a hospital operating room. The current level of IT integration with production machines, including the application of AI, is discussed. Additionally, the document explores foreseeable opportunities and challenges associated with future advancements in AI. The transformation journey of manufacturing towards a lights-out concept presents significant technical challenges and impacts the way humans and systems in fabrication plants will adapt to this evolution.
Short Biography :
Jean-François Germain is part of the Digital Transformation and Information Technology (DTIT) organization at STMicroelectronics and has been the Head of IT Manufacturing Solutions since June 2016. He oversees IT operations, solutions and infrastructure supporting the company’s factories (14 sites) and leads the transformation of the IT manufacturing ecosystem toward advanced solutions. The IT manufacturing organization plays a key role in deploying fully automated fabs in the company’s most advanced facilities, including the 300 mm diffusion fab, 200mm SiC campus, and advanced packaging plants.
He began his career in 1993 as the IT Manager of the Rennes plant (France). He holds a degree in electronics and computer engineering from INSA Rennes, France.
Academic Keynote
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Pr. Shenle Pan Mines Paris, PSL University
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AI-driven smart city logistics operations: combing data and system intelligence
Recent research in city logistics is increasingly exploring new management paradigms in the context of Smart Cities, where IoT devices are deployed and managed through data platforms and Digital Twins. Once data are collected and consolidated, AI-driven operations can be developed along two complementary axes: data intelligence and system intelligence. Data intelligence concentrates on using data to generate knowledge and insights to optimize decisions and operations (e.g., data analytics, Generative AI), while system intelligence emphasizes system-wide cooperation and coordination (e.g., cognitive systems, multi-agent systems). Focusing on the latter, this presentation investigates how Cognitive Digital Twins—Digital Twins with augmented semantic capabilities—can integrate actual operational knowledge (e.g., destination-specific constraints) to optimize logistics planning and urban resource allocation. We propose a four-layer architectural framework for semantically integrating logistics objects and systems into Smart Cities, leveraging enabling technologies and standards such as Property Graph, Web Ontology Language (OWL), and Web of Things. A simulation-based optimization study of last-mile parcel delivery in Paris is conducted to demonstrate practical applications, using the Thing’in Digital Twin platform provided by Orange France. Experimental results and insights illustrate how AI and knowledge-driven approaches can enhance smart city logistics operational efficiency. Future research directions will also be discussed.
Short Biography :
Shenle Pan is a Full Professor (holding Habilitation and Engineering Degree) in logistics and supply chain management at MINES Paris, PSL University, France. He serves as Co-Director of the Physical Internet Chair and Associate Head of the Center for Management Science. Since 2010, he has led, co-led, or contributed to over 20 research projects funded by EU programs (HE, H2020, FP7), French national programs (ANR, PIA, ADEME), and industry partners. He has published more than 100 peer-reviewed papers and guest-edited six special issues in leading academic journals. His research focuses on sustainable and resilient logistics and supply chains, the Physical Internet, and smart city logistics, with a methodological emphasis on Operations Research, data analytics, AI-driven decision-making, and semantic digital twins. His contributions have earned multiple best paper and project awards, and he was included in the 2024 Stanford/Elsevier Top 2% Scientists list in his field. He also regularly serves as a reviewer for academic journals and as an evaluator for research proposals across various countries and regions.
