2026 International Conference on Sensor Technology and Information Engineering (STIE 2026)

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Prof. Liang Yang

Hunan University, China

Biography:

Liang Yang, Ph.D., Third-Level Professor, Doctoral Supervisor, and Member of the Communist Party of China. He is recognized as a Hunan Province Furong Program Leading Talent in Scientific and Technological Innovation. His main research areas include wireless communication technologies, vehicular networks and mobile edge computing, low-altitude networks, and security and privacy-preserving technologies. He has published over 190 SCI-indexed papers in renowned domestic and international academic journals, including more than 150 IEEE journal papers (nearly 100 in IEEE Transactions), 9 ESI highly cited papers, and 2 ESI hot papers. He has been consecutively listed in the Stanford University Top 2% of Scientists (both career and single-year impact lists) for six years, and was recognized as an Elsevier “Highly Cited Chinese Researcher” in 2023, 2024, and 2025. As the principal investigator, he has led five projects funded by the National Natural Science Foundation of China (NSFC) (four General Projects and one Young Scientist Project) and one sub-project of the National Key R&D Program of China. He has also participated as a sub-project leader in a Key Project of the NSFC Regional Innovation and Development Joint Fund, and as a participant in a Major National Science and Technology Project on Mobile Information Networks. He serves or has served on the editorial boards of numerous prestigious journals, including IEEE Transactions on Communications, IEEE Transactions on Vehicular Technology, IEEE Transactions on Cognitive Communications and Networking, IEEE Internet of Things Journal, IEEE Wireless Communications Letters, IEEE Communications Letters, Science China: Information Sciences, Journal on Communications, Journal of Electronics & Information Technology, and Journal of Internet of Things. He is a member of the 8th and 9th Technical Committees on Communication Theory and Signal Processing of the China Institute of Communications, and a member of the first Technical Committee on Reconfigurable Intelligent Surfaces of the China Institute of Communications. He received the Second Prize of the Hunan Provincial Natural Science Award in 2019 (ranked first), is an Outstanding Scientific and Technological Worker of the Chinese Institute of Electronics, serves as Vice Chairman of the Hunan Institute of Electronics, and is a Minjiang River Scholar Chair Professor.

Speech Title:

Toward 6G: Next-Generation Network Architectures and Enabling Technologies

Abstract:
This report focuses on 6G network architectures and enabling technologies, particularly the integration of Space-Air-Ground Integrated Networks (SAGIN) with Reconfigurable Intelligent Surfaces (RIS). As emerging applications such as IoT, autonomous driving, and remote communications demand ultra-low latency, high bandwidth, and full coverage, traditional systems face growing limitations. The report highlights various RIS architectures—passive/active, single-/multi-layer, and transmit/receive/relay types—and their critical roles in channel reconfiguration and anti-jamming, demonstrating their potential to enhance communication performance in complex environments. Two key research contributions are presented. First, an active RIS-assisted, NOMA-enabled SAGIN framework with cognitive radio is proposed, which jointly optimizes power allocation, UAV trajectory, and RIS parameters to ensure communication quality and improve energy efficiency in remote areas. Second, a multi-layer RIS-assisted receiver architecture for anti-jamming scenarios is developed, incorporating silent and non-interference cooperative protocols to enhance user device resilience and spectral efficiency. Both studies are supported by theoretical modeling and simulation results, offering new insights into the design of reliable 6G communication systems.

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Prof. Tianlei Ma

Zhengzhou University, China

Biography:

Tianlei Ma, Ph.D., Professor and Doctoral Supervisor at Zhengzhou University, Director of the Experimental Center of the School of Electrical and Information Engineering at Zhengzhou University. He is recognized as an Outstanding Postdoctoral Researcher in National Innovation and Entrepreneurship, Excellent Guiding Teacher of the National Graduate Electronic Competition, High-Level Talent in Henan Province, Outstanding Young Talent of Central Plains, Young Scientist of the Henan Province Science and Technology Research and Development Plan Joint Fund, Young Talent in Henan Province, Young Backbone Teacher in Henan Province, Deputy Director of the Henan Digital Organization Engineering Technology Center, and Excellent Bachelor's/Master's Thesis Guiding Teacher in Henan Province. He has long been engaged in research on artificial intelligence and multi-modal sensing for sensors. He has published more than 30 academic papers, presided over over 10 national, ministerial and provincial-level projects including the General Program and Youth Program of the National Natural Science Foundation of China, and the Key R&D Program of Henan Province, and won the Second Prize of Science and Technology Progress of Henan Province.

Speech Title:

Key Technologies for Dim Signal Enhancement and Detection of Infrared Sensors

Abstract:
Dim signal detection in infrared sensors is a core technology in the field of modern sensing, playing an irreplaceably important role in key areas such as national defense security and aerospace exploration. In practical application scenarios, dim target signals on the plane of infrared detectors are susceptible to severe interference from various types of noise (including thermal noise, 1/f noise, shot noise, etc.), resulting in extremely low signal-to-noise ratios and blurred target features, which pose great challenges to the effective detection of dim signals. Aiming at this technical bottleneck, this report focuses on the key technologies for enhanced detection of dim signals in infrared sensors, addressing core issues such as target signal enhancement in noisy environments and reliable signal detection under weak-feature conditions. Experiments show that the proposed technology can significantly improve the detection performance of infrared dim signals under low signal-to-noise ratio conditions. This technology plays an important role in promoting sensor sensitivity through information processing methods, and is of great practical significance for upgrading national defense equipment, strengthening national security capabilities, and driving high-quality development in related civil fields.

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Prof. Dongzhi Zhang

China University of Petroleum (East China)

Biography:

Dongzhi Zhang is a Professor and PhD Supervisor at China University of Petroleum (East China). He is a distinguished Taishan Scholar of Shandong, a Highly-Cited Researcher globally (top 0.05%). He serves as a member of the Teaching Guidance Committee of the Ministry of Education, and Vice President of the Shandong Institute of Electrical Engineering. Professor Zhang’s research focuses on micro-nano detection and advanced sensing technologies, safety monitoring and intelligent risk perception, as well as intelligent detection technologies and microsystems. He has chaired more than 30 research projects, including key projects under the National Key R&D Program of China, National Natural Science Foundation of China projects, and Shandong Provincial Key R&D Program projects. He has published over 290 SCI-indexed papers in internationally renowned journals, among which 49 are ESI Highly Cited Papers. His publications have received more than 23,000 citations, with an H-index of 89. He holds 53 authorized national invention patents and has authored 8 textbooks and academic monographs. Professor Zhang is a member of several distinguished societies and associations, including the Embodied Intelligence Committee of the Chinese Association of Automation, the Professional Committee on Chemical Safety of the Chemical Industry and Engineering Society of China, the Professional Committee on Intelligent Sensors and Detection Technology of the Chinese Association of Automation. He is also a Director of the Precision Machinery Branch of the Chinese Society for Measurement, the Founding Editor-in-Chief of Smart Sensors and an Editorial Board Member of the Journal of Intelligent Sensing and Engineering.

Speech Title:

Intelligent Gas Sensing and Equipment State Perception Technology

Abstract:
The fusion of intelligent gas sensing and equipment state perception technology provides critical support for the intelligent transformation of industries. To resolve problems of coarse-grained state perception, inaccurate risk monitoring, and delayed early warning in energy equipment, such as power facilities and energy storage systems, in-situ online intelligent gas sensors are developed to detect fault characteristic gases from equipment. Combined with multi-dimensional state parameters and advanced artificial intelligence algorithms, our approach enables equipment health monitoring, fault early warning, and intelligent operation and maintenance, forming a “perception–analysis–warning–decision-making” closed-loop monitoring system for equipment states. This report presents key technologies, including gas-sensitive materials and device design, microfabrication and integrated packaging of MEMS gas sensors, multi-parameter monitoring fusion and machine learning algorithms, as well as state perception and predictive early warning. These technologies break through bottlenecks in materials, algorithms, and engineering applications, and exhibit broad application prospects in power equipment, energy storage systems, petrochemical facilities, and other industrial fields.