Prof. Xueye Chen, Ludong University, China
Elected as an Excellent Scientific and Technological Worker of Shandong Province, a Young Expert of Taishan Scholar Program, a Provincial Young Top-notch Talent, and a member of the Provincial 100/1000/10,000 Talent Project, and awarded the title of Excellent Supervisor of Master's Degree Theses in Shandong Province. Served as a visiting scholar at Nanyang Technological University in Singapore and The Hong Kong Polytechnic University. Conducts research in micro/nano manufacturing, flexible MEMS intelligent sensing, and microfluidic systems, targeting wearable devices, healthcare, and modern agriculture. Has been awarded 7 provincial-level honors including the Provincial Natural Science Award and the Provincial Academic Achievement Award in Natural Science.
Presides over over 10 key projects, including the National Natural Science Foundation of China and the Shandong Provincial Natural Science Foundation. Publishes numerous papers in top-tier academic journals and holds multiple authorized patents. Serves as a Guest Editor for the special issue of the international academic journal Micromachines, as well as a member of the organizing committees for international conferences such as MSMME, MTMCE, and ICOIP. Acts as a reviewer for renowned international journals including Small, Biosensors and Bioelectronics, and Lab on a Chip, and as an expert reviewer for academic institutions such as the National Natural Science Foundation of China and the Degree Education Center of the Ministry of Education. Has supervised many graduate students who have pursued doctoral degrees at first-class universities nationwide, such as Peking University, Tianjin University, Xiamen University, Beijing Institute of Technology, and National University of Defense Technology. Several of his students have won various scholarships, including the National Scholarship, President's Scholarship, and First-Class Academic Scholarship.
Speech Title: Non-invasive sweat creatinine detection system integrated with Zn-Ni bimetallic MOF flexible sensor and biomimetic microfluidic chip
Abstract: Non-invasive and real-time creatinine detection technologies are in urgent need for the early screening of chronic kidney disease (CKD). Conventional detection methods suffer from drawbacks such as invasiveness, long detection cycles and the inability to achieve real-time monitoring, while existing sweat creatinine sensors are also confronted with bottlenecks including poor selectivity, insufficient stability and the reliance of microfluidic systems on external driving devices. For the first time, this study constructed a non-invasive sweat creatinine detection system integrating a Zn-Ni bimetallic MOF-based flexible sensor and a biomimetic microfluidic chip, providing a novel technical solution for the non-invasive, real-time and accurate monitoring of renal function. Taking laser-induced graphene (LIG) as the flexible substrate, the sensor was fabricated by compositing Zn-Ni bimetallic MOF synthesized via a room-temperature stirring method with carboxylated carbon nanotubes (COOH-CNT). By virtue of the bimetallic synergistic effect and the advantages of multi-material composite, the integration of "recognition-conduction-support" was realized. The sensor exhibited favorable segmented linear relationships in the creatinine concentration range of 0.08~1 mmol/L with correlation coefficients all exceeding 0.978, and its sensitivity reached 283.3 μA/(mmol·cm²). Meanwhile, it possessed excellent anti-interference ability, mechanical stability and batch repeatability, and human sweat spiking experiments verified its feasibility for practical detection. Drawing on the skin microstructure of the Texas horned lizard, the biomimetic microfluidic chip was designed with an asymmetric microgroove array, and its structural parameters were optimized through COMSOL simulation (the side length of the biomimetic structure was 0.12 mm, the inter-structure spacing was 0.08 mm, and the spacing between the biomimetic structure and the channel wall was 0.06 mm), enabling the passive and spontaneous directional transport of sweat at a speed of 9.7 mm/s. The integrated capillary burst valve could effectively avoid sample cross-contamination, and the chip also had good flexibility and mechanical stability. This integrated "sensing-transport" platform breaks through the limitations of traditional technologies and achieves non-invasive, rapid and accurate detection of sweat creatinine, boasting broad application prospects in the fields of early warning of CKD, clinical auxiliary diagnosis, household health management and so on. The study also points out the existing problems of the current system, such as the difficulty in directly detecting low-concentration creatinine and the lack of wireless data transmission function. In the follow-up, the performance and clinical applicability of the platform will be further improved through material modification, multi-biomarker detection, intelligent system integration as well as large-sample clinical verification.
Prof. Zhenmin Zhu, East China Jiaotong University, China
Prof. Zhu was awarded a special allowance by the Jiangxi Provincial Government and selected for the Gan Poyang Talent Program - Youth Innovation High-end Talent. He has presided over or completed more than 30 projects, including research and development funded by the National Natural Science Foundation of China, Jiangxi Province's key research and development plan, the Marshal Project, the Jiangxi Province Outstanding Young Talent Project, provincial invention and patent industrialization projects, provincial natural science funds, and other provincial, ministerial, and enterprise-entrusted projects. Currently, he is primarily engaged in research related to precision visual measurement, intelligent detection, automation systems, and polarization visual imaging. As the first author or corresponding author, he has published more than 90 research papers, including 66 SCI-indexed papers, in journals such as LPR ,IEEE TIM, Optics Express, Optics and Lasers in Engineering, and Measurement. One of his papers was selected as an Editors' Pick. He is the first inventor of 32 national invention patents, and the results of the projects under his leadership have won the Second Prize of Jiangxi Provincial Technological Invention in 2020 (ranked 1st) and the Second Prize of Jiangxi Provincial Scientific and Technological Progress in 2023 (ranked 1st).
Speech Title: Research and Application of Structured Light Measurement Technology Based on Polarization Imaging
Abstract: The high precision calibration of visual imaging and sensor is the core basic technology and fundamental guarantee of optical precision measurement. With the application of optical measurement gradually developed from detection in a fixed environment to measurement in an uncontrollable environment (such as field measurement, etc.), the optical properties of the measurement environment and the surface of the object to be measured become more and more complex. How to ensure the accuracy of the measurement system in the complex measurement environment has become an important direction of the development of structured light measurement system. At present, most of the researches on 3D optical measurement use light intensity as information transmission channel. Aiming at the problem of high precision measurement in complex environment, a calibration method of structured light system based on optimal polarization angle is proposed to improve the precision of system calibration. A single image field calibration method for all parameters of structured light sensor based on cylindrical target is proposed, which solves the high precision field calibration of in-situ structured light optical measurement system and promotes the engineering application of structured light measurement. A structured light coding technique based on polarization state is proposed to reduce the influence of camera defocus in structured light measurement system. A fast measurement technique of polarization enhanced structured light fringes is proposed, which can reconstruct a wide range of reflectivity objects with only once exposure time.
Prof. Meng Zhang, Henan University of Technology, China
He is a member of the Standards Committee of the China Electronic Materials Association and is dedicated to basic research, technological development, and practical applications in electronic materials and rechargeable batteries. He has led the industrialization of micro- and nano-scale electronic powders—including silver-coated copper, silver-coated nickel, and tin alloys—produced via wet chemical methods, for use in the photovoltaic, semiconductor, lighting, and automotive sectors. He has undertaken more than 20 research projects at various levels and corporate R&D initiatives, published over 70 academic papers, authored four academic monographs (either independently or in collaboration), obtained 10 authorized invention patents, contributed to the development of three standards, and received five provincial and ministerial-level academic awards.
Speech Title: Design and Fabrication of Highly Reliable Aqueous Zinc-Based Batteries
Abstract: The reliability of aqueous zinc-based batteries is primarily limited by factors such as zinc dendrites, hydrogen and oxygen evolution side reactions, and cathode degradation. This report analyzes the mechanisms underlying these factors and, based on this analysis, explores corresponding mitigation strategies. It involves the design and optimization of the battery system, electrode materials, and electrolyte additives to develop highly reliable aqueous zinc-based batteries.
Prof. JunjieYe, Xidian University, China
Junjie Ye, Professor, Doctoral Supervisor, Municipal Leading Talent, Editorial Board Member of the international journal Materials Science: Advanced Composite Materials, Executive Chair of the "Academic Conference on Composite Material Structure Mechanics under Extreme Environments," Member of the Composite Material Structure Design Committee of the Chinese Society for Composite Materials, Expert in the Science and Technology Expert Database of Jiangxi and Shaanxi Provinces. Recipient of the Shaanxi Provincial Science and Technology Achievement Second Prize and the Shaanxi Provincial Department of Education First Prize. Graduated from Xi'an Jiaotong University in 2011 with a major in Mechanical Manufacturing and Automation. Joined Xidian University in 2012 to engage in teaching and research. Peer Review Expert for the Engineering and Materials Science Department of the National Natural Science Foundation of China, Council Member of the Fault Diagnosis Committee of the Chinese Society of Vibration Engineering. Mainly engaged in research on damage monitoring technology based on machine learning algorithms and mechanical system damage modeling methods. In recent years, has led four National Natural Science Foundation projects, two Shaanxi Provincial Natural Science Basic Research Program projects (one key project and one youth project), four Central University Basic Research Fund projects, and 20 industry-university collaborative projects.
Speech Title: Development of Intelligent Inspection Quadruped Robots
Abstract: Quadruped robots demonstrate significant advantages in certain fields due to their strong stability, high flexibility, broad adaptability, and outstanding load-carrying capacity. Over the past decade, substantial progress has been made in the field of quadruped robots, yet their potential remains not fully realized. To address complex environments in power plants, research is conducted on quadruped robot structural design, navigation and obstacle avoidance, as well as multi-dimensional perception technologies to achieve intelligent inspection with quadruped robots. Using bionic principles, the structure of the quadruped robot is designed and optimized, integrating both hardware and software. Reinforcement learning is employed for motion control, including gait planning, balance strategies, and recovery. Additionally, multi-sensor fusion technology, combining vision and lidar, is studied to enable autonomous navigation and obstacle avoidance for inspection tasks.