Computational Sensing with Mechanical Metamaterials: Theory and Technology

Prof. Qingbo He

Shanghai Jiao Tong University, China

Abstract

With the continuous enrichment and development of computing resources, the computational sensing technology combining physical field information coding and sensing algorithm breaks through the limitations of traditional sensing methods and reduces the cost of sensing and data acquisition. Metamaterials can encode the physical field information flexibly and plays an important role in computational sensing technology. They have the outstanding advantages of high resolution, lightweight structure, flexible customization and low cost. Aiming at the difficulty that the traditional vibration and acoustics identification methods rely on complex hardware systems such as sensor array and network, this speech introduces mechanical metamaterials-based computational sensing technology for identifying the vibration and acoustic sources. The spatial vibration and acoustic transmission coding metamaterials have been designed. By combining the designed metamaterials with the compressive sensing theory, spatial multi-source localization and trajectory tracking have been realized for the vibration and acoustics driven applications. The research results break through the limitation that current vibration and noise identification technology depend on a large number of sensors, and provide a new idea for accurate and efficient vibration and noise identification under the condition of high integration and lightweight. It has important theoretical and application value in the fields of high-end equipment manufacturing and operational maintenance, intelligent human-computer interaction, Internet of things and so on.

Biographical Sketch

Qingbo He is Professor with the School of Mechanical Engineering, Shanghai Jiao Tong University, China. His research interests include a combination of vibration analysis, signal processing, and smart structures for intelligent sensing, diagnosis, and maintenance of complex machines. He has published more than 130 peer-reviewed journal papers, including Nature Communications, Matter, and IEEE Transactions. He has been selected in the list of Chinese Most Cited Researchers by Elsevier since 2020. He is a recipient of multiple honors and awards, including National Young Professionals in China, Shanghai Outstanding Academic Leaders, the Best Paper Award from several international conferences. He is an Associate Editor of Frontiers in Physics. He is an IEEE Senior Member and serves as Chair of Nanjing/Shanghai/Wuhan Joint Section Chapter of IEEE Instrumentation and Measurement Society. 

Industrial AI: Towards the Era of Industrial Foundation Models

Prof. Lei Ren

 Beihang University, China

Abstract

The Industrial Internet, as a national-level innovation strategy, has witnessed its industry scale surpass 1.35 trillion yuan. Since 2023, the emergence of various large-scale AI models has been impacting on both academia and industry significantly. Driven by this new wave of AI technologies, the Industrial Internet is accelerating its transformation from digitization and networking to intelligence. This report will introduce the development trends of the new generation of AI and intelligent manufacturing, exploring emerging hot technologies in the intelligent transformation of the Industrial Internet. These technologies include industrial edge intelligence, industrial big data intelligence, industrial cloud-edge collaborative intelligence, industrial digital twin intelligence, and industrial metaverse, among other cutting-edge technologies. On this basis, the report will also forecast the future development directions of industrial foundation models and present the progress made by the Beihang University team in building the base for industrial foundation models, as well as advancements in talent cultivation through the integration of industrial internet and education.

Biographical Sketch

Lei Ren is the first recipient of the National Science Foundation for Distinguished Young Scholars of China and serves as the Chief Scientist of the "Industrial Software" Project under the Chinese National Key Research and Development Program. He is a Professor at the School of Automation Science and Electrical Engineering and the School of Software at Beihang University, as well as a Ph.D. advisor and Vice Chairman of the Special Committee of the State Key Laboratory of Intelligent Manufacturing Systems Technology. His research areas include Industrial Internet, industrial software, industrial AI, and large-scale industrial models. He has led over 20 national and provincial-level projects, including Major National Science and Technological Special Project, the National Key Research and Development Programs, and Major Research Programs of the National Science Foundation of China. Professor Ren has published more than 100 papers in internationally renowned journals, such as IEEE Transactions, with nearly 10,000 citations, and has been listed in Stanford's Top 2% Global Scientists for Lifetime Impact. He has led or participated in the formulation of 15 international and national standards. With over 50 patents and software copyrights to his name, his core technologies have been applied by more than 300 enterprises, yielding significant economic and social benefits. He serves on the expert or professional committees of over 10 domestic and international academic organizations, including IEEE, CSF, CCF, CAAI, and CAA. He also serves as the Vice Director of the Intelligent Cyber-Physical Systems Committee of the China Simulation Federation, the Vice Director of the Cloud Control and Decision Committee of the Chinese Institute of Command and Control, and a member of the board of directors of the China Simulation Federation. He is also an editorial board member of international journals such as IEEE TNNLS and TMECH. Additionally, Professor Ren serves as the Vice Chairman of the Talent Working Group of the China Industrial Internet Alliance. He was the first to offer the "Industrial Internet" course and an online digital course at universities nationwide. He has chaired dozens of IEEE and other domestic and international academic conferences and has been invited to deliver over 100 keynote speeches at conferences, including the UN Global AI Summit.

Pioneering Lithium-ion Battery Innovation: The Transformative Power of AI

Prof. Haofeng Chen

Abstract

Artificial Intelligence (AI) has become an indispensable tool across various industries, transforming processes, enhancing efficiency, and enabling innovation. In sectors such as healthcare, finance, manufacturing, and transportation, AI drives advancements through automation, data analysis, predictive modeling, and decision-making support. Lithium-ion batteries, known for their high energy density, rechargeable capability, and emission-free operation, have played a crucial role in addressing the energy crisis and environmental pollution. These batteries are widely adopted in applications such as portable electronics, electric vehicles, and stationary power stations due to their superior performance. This research focuses on the integration of AI in the lithium-ion battery sector. AI techniques are being utilized to accelerate the development of battery materials, improve lifespan prediction, and enhance battery diagnostics, among other aspects. By analyzing vast datasets from material testing, AI can identify new materials with superior properties, leading to more efficient and durable batteries. In lifespan prediction, AI models analyze usage patterns and environmental factors, enabling more accurate predictions of battery life and early identification of degradation signs. Additionally, AI-powered diagnostic tools improve the detection of defects and anomalies in batteries, ensuring higher safety standards and better performance. The integration of AI in these areas not only enhances existing technologies but also drives innovation, paving the way for advanced energy storage solutions to meet the growing demands of the future.

Biographical Sketch

Professor Haofeng Chen, a distinguished Changjiang Scholar, is a Chair Professor at East China University of Science and Technology and a visiting Professor at the University of Strathclyde. He is also a foreign Senior Scientist recognized by the National Natural Science Foundation of China, and a Fellow of both the ASME and the Institution of Mechanical Engineers. From 2008 to 2023, he led the Structural Integrity and Life Assessment Research Group in the Department of Mechanical and Aerospace Engineering at the University of Strathclyde. He also served as an Associate Editor of the ASME Journal of Pressure Vessel Technology from 2011 to 2017. Professor Chen earned all his academic degrees from Tsinghua University, including dual Bachelor's degrees in engineering mechanics and economic management, as well as an MEng and PhD in solid mechanics. His early career included research fellowships at Nanyang Technological University and the University of Leicester. Since joining the University of Strathclyde in 2008, he has established a significant and sustainable research portfolio in structural integrity engineering, particularly in advanced FEA, fracture mechanics, shakedown, ratchetting, high-temperature creep and fatigue analysis, as well as lithium battery research. Professor Chen has published over 220 peer-reviewed research papers and is recognized among the top 2% of the most influential scientists globally.