Mr. Dezhi Zheng | Smart Sensors Awards | Best Researcher Award

Mr. Dezhi Zheng, Beijing Institute of Technology, China

Dr. Dezhi Zheng is a distinguished Professor and Doctoral Supervisor at the Advanced Research Institute of Multidisciplinary Sciences, Beijing Institute of Technology. He received his Ph.D. in Precision Instruments and Machinery and his B.S. in Mechanical Engineering and Automation from Beihang University. With a career spanning roles from Lecturer to Associate Professor at the School of Instrumentation and Optoelectronic Engineering at Beihang University, and a Visiting Scholar at the University of Victoria, Dr. Zheng has made significant contributions to airborne information detection, extreme signal measurement technology, and sensor-sensitive mechanisms. His research, focused on national strategic needs, has advanced the theoretical and applied aspects of precise sensing for weak physical features. Key achievements include innovations in resonant sensor technology to enhance aircraft altitude measurement, ultra-low frequency vibration sensor calibration for explosion monitoring, and wearable sensing devices that address long-term usability in brain-computer interfaces. With over 70 academic publications, 30 invention patents, and participation in more than 30 national research projects, Dr. Zheng’s work has had impactful applications in resonant sensors, low-frequency vibration technology, and smart wearable devices.

Professional Profile:

SCOPUS

Summary of Suitability for Best Researcher Award:

Professor Dezhi Zheng, affiliated with the Advanced Research Institute of Multidisciplinary Sciences at Beijing Institute of Technology, has a distinguished profile that aligns well with the criteria for the Best Researcher Award.

🎓 Education

2000-2006: Ph.D. in Precision Instruments and Machinery, Beihang University 🛠️
2008-2012: B.S. in Mechanical Engineering and Automation, Beihang University 🧑‍🎓

🔬 Research Interests

📡 Airborne Information Detection
🛰️ Extreme Signal Measurement Technology
🎛️ Sensor Sensitivity Mechanism

🔍 Research Highlights

Prof. Zheng’s research addresses major national strategic needs in precise sensing technology and weak physical feature applications. Notable achievements include:

✈️ Enhanced Aircraft Altitude Measurement: Developed resonant sensor technologies that improve flight height measurement by nearly an order of magnitude
🌋 Ultra-Low Frequency Vibration Measurement: Pioneered ultra-low frequency sensors for explosion vibration, achieving precise calibration at 0.01Hz
🧠 Wearable Bioelectrical Sensing: Innovated wearable, long-use sensors for brain-computer interfaces, enabling breakthrough applications in wearable tech

🏆 Key Contributions

Led research applied in resonant sensors, low-frequency vibration calibration, and smart helmets 🪖
Solved technical challenges including sensor device coupled vibration, nonlinear measurement, and dynamic response 🌐
Participated in 30+ national research projects
Published 70+ academic papers 📄
Authorized 30+ invention patents 🔑

Publication top Notes:

UniRTL: A universal RGBT and low-light benchmark for object tracking

Adaptive temperature compensation for MoS₂ humidity sensor in complex environments using ISSA-BP neural network

Catadioptric omnidirectional thermal odometry in dynamic environment

A hybrid method for asynchronous detection of motor imagery electroencephalogram fusing alpha rhythm and movement-related cortical potential

Investigation of the morphology and structural transformation of 6H-SiC induced by a single femtosecond laser pulse

Nuclei engineering for even halide distribution in stable perovskite/silicon tandem solar cells

Ms. Xinlu Bai, Changchun university, China

Xinlu Bai is a dedicated researcher currently pursuing a Master’s degree in Computer Science at Changchun University, following an Engineering Degree from Zhengzhou University of Finance and Economics (2018-2022). Xinlu has made significant contributions to the field of computer vision, particularly in dense pedestrian detection. His research includes the development of the GR-YOLO algorithm, which improves detection performance over existing methods like YOLOv8, with notable advancements in accuracy across various datasets. Xinlu’s work has been published in Sensors and has been guided by esteemed professors Deyou Chen and Nianfeng Li. He has been recognized for his excellence in competitions, winning the first prize in the Jilin Province Virtual Reality Competition, the second prize in the China Virtual Reality Competition (Data Visualization Track), and the third prize in the Jilin Province Ruikang Robot Competition.

Professional Profile:

Orcid

Suitability Summary for Best Researcher Award

Researcher: Xinlu Bai

Summary:

Xinlu Bai is a highly qualified candidate for the Best Researcher Award, distinguished by his innovative research and significant contributions to the field of computer science, particularly in pedestrian detection technology. Bai’s work demonstrates a clear commitment to advancing technology through rigorous research and practical applications.

🎓Education:

Xinlu Bai is a dedicated researcher currently pursuing a Master’s degree in Computer Science at Changchun University, which he has been enrolled in since 2023. He previously completed his Engineering Degree at Zhengzhou University of Finance and Economics, where he studied from 2018 to 2022. Xinlu has made significant contributions to the field of computer vision, particularly in dense pedestrian detection. His development of the GR-YOLO algorithm, which enhances detection performance compared to YOLOv8, has been recognized through publications in Sensors and has been guided by esteemed professors Deyou Chen and Nianfeng Li. His excellence has been acknowledged in various competitions, including winning the first prize in the Jilin Province Virtual Reality Competition, the second prize in the China Virtual Reality Competition (Data Visualization Track), and the third prize in the Jilin Province Ruikang Robot Competition.

🏆Awards:

Xinlu Bai is a dedicated researcher currently pursuing a Master’s degree in Computer Science at Changchun University, having previously completed his Engineering Degree at Zhengzhou University of Finance and Economics. His contributions to computer vision, particularly through the development of the GR-YOLO algorithm, have been published in Sensors and guided by Professors Deyou Chen and Nianfeng Li. Xinlu’s excellence in the field has been recognized with several prestigious awards: he won the First Prize in the Jilin Province Virtual Reality Competition, the Second Prize in the China Virtual Reality Competition (Data Visualization Track), and the Third Prize in the Jilin Province Ruikang Robot Competition.