Prof. Dezhi Zheng | Sensitive Mechanism Awards | Best Researcher Award

Prof. Dezhi Zheng | Sensitive Mechanism Awards | Best Researcher Award

Prof. Dezhi Zheng, Beijing Institute of technology, China

Professor Dezhi Zheng is a prominent researcher and doctoral supervisor at the Advanced Research Institute of Multidisciplinary Sciences at Beijing Institute of Technology. With a robust academic background, he earned both his Ph.D. and B.S. degrees in Precision Instruments and Machinery and Mechanical Engineering and Automation from Beihang University. Since 2020, he has been a professor at Beijing Institute of Technology, and prior to this role, he served as a visiting scholar in the Mechanical Engineering Department at the University of Victoria and held various academic positions at Beihang University. Professor Zheng’s research interests focus on collaborative awareness technology, airborne information detection, extreme signal measurement technology, and sensor sensitivity mechanisms. His groundbreaking work in accurate perception technology has led to significant advancements in resonant sensors, ultra-low frequency vibration sensors, and wearable sensing devices for human bioelectrical signals, notably improving measurement accuracy and practical applications in fields like aviation and smart technology. With over 30 national key scientific research projects and more than 70 academic publications to his name, along with over 30 authorized invention patents, Professor Zheng is recognized as a leader in the field of sensors and sensing technology.

Professional Profile:

ORCID

Summary of Suitability for the Best Researcher Award: Dezhi Zheng

Dezhi Zheng is an accomplished researcher and educator with a distinguished record in the fields of sensing technology and precision instrumentation, making him an excellent candidate for the Best Researcher Award. His extensive academic background and impactful contributions in both research and technology application underscore his qualifications.

Education 🎓

  • Ph.D. in Precision Instruments and Machinery
    Beihang University, 2000-2006
  • B.S. in Mechanical Engineering and Automation
    Beihang University, 1996-2000

Work Experience 🏢

  • Professor
    Advanced Research Institute of Multidisciplinary Sciences, Beijing Institute of Technology (2020 – Present)
  • Visiting Scholar
    Mechanical Engineering, University of Victoria (2014 – 2015)
  • Researcher
    Research Institute for Frontier Science, Beihang University (2006 – 2020)
  • Associate Professor
    School of Instrumentation and Optoelectronic Engineering, Beihang University (2006 – 2020)
  • Lecturer
    School of Instrumentation and Optoelectronic Engineering, Beihang University (2006 – 2006)

Achievements 🏆

  • Conducted research on resonant sensors, improving measurement accuracy of aircraft flight height by nearly an order of magnitude. ✈️
  • Developed ultra-low frequency vibration sensors and calibration technology, achieving accurate calibration of 0.01Hz sensors. 📏
  • Researched wearable sensing devices and intelligent sensing technology for weak human bioelectrical signals, leading to practical applications in wearable brain-computer interfaces. 🧠
  • Participated in over 30 major national key scientific research projects. 🔬
  • Published more than 70 academic papers. 📚
  • Authorized more than 30 invention patents. 💡

Awards and Honors 🥇

  • Recognized for contributions to the development of resonant sensors and smart helmets, addressing key challenges in sensor technology. 🛠️
  • Achievements in the field of collaborative awareness technology and extreme signal measurement technology. 🌟

Publication Top Notes:

Hybrid Knowledge-Data Driven Channel Semantic Acquisition and Beamforming for Cell-Free Massive MIMO

Integrated Sensing and Communication With mmWave Massive MIMO: A Compressed Sampling Perspective

Joint Activity Detection and Channel Estimation for Massive IoT Access Based on Millimeter-Wave/Terahertz Multi-Panel Massive MIMO

Next-Generation Massive URLLC with Massive MIMO: A Unified Semi-Blind Detection Framework for Sourced and Unsourced Random Access

Robust phase unwrapping via non-local regularization