Jie Tian | Experimental methods | Best Researcher Award

Posted on by High Energy Physics

Prof. Jie Tian | Experimental methods | Best Researcher Award

Dr. Jie Tian is a distinguished Professor at the Institute of Acoustics, Chinese Academy of Science, Beijing, China. He holds a Ph.D. in Automatic Control from Beijing Institute of Technology (2002) and a Bachelor’s degree in Automatic Control from Northwestern Polytechnic University (1995). His primary research focus lies in the fields of underwater information and signal processing and classification & image processing.

👨‍🎓Profile

Scopus

🎓 Early Academic Pursuits

Dr. Tian’s academic journey began at Northwestern Polytechnic University, where he earned his Bachelor’s degree in Automatic Control in 1995. Building on this foundation, he pursued his Ph.D. at Beijing Institute of Technology, specializing in Automatic Control. His studies laid the groundwork for his deep engagement with signal processing and image processing algorithms, disciplines that continue to define his career today.

đź’Ľ Professional Endeavors

Dr. Tian’s professional career spans over two decades, marked by significant contributions to both academia and research. He is currently a Professor at the Institute of Acoustics, Chinese Academy of Science, where he has worked since 2002. His career trajectory includes a Postdoctoral fellowship and Associate Professorship at the same institution, where he developed theoretical algorithms for image processing and worked extensively on information processing systems. His transition from postdoc to professor reflects his growing influence in his field, particularly in the domain of underwater acoustic communication networks and image classification.

🔬 Contributions and Research Focus

Dr. Tian’s research contributions are far-reaching and impactful. His expertise includes underwater information processing, with a particular focus on underwater object classification, and sonar image processing. Notable areas of his work include:

  • Cross-layer routing protocols for underwater acoustic communication networks.
  • Deformable residual networks and transfer learning for underwater object classification in SAS images.
  • Deep neural networks for classification in high-resolution sonar images.

His focus on advanced algorithms such as deep neural networks and SVM-based techniques has helped push forward the frontiers of image classification and signal processing in challenging underwater environments.

🧑‍🏫 Teaching Experience

Dr. Tian is not only a researcher but also a dedicated educator. As a Professor, he has mentored countless students and guided the next generation of researchers in the Institute of Acoustics. His expertise in image processing and signal processing provides students with valuable insights into cutting-edge technologies, preparing them for careers in academic research and industry applications.

đź”® Legacy and Future Contributions

Dr. Tian’s work has already left a lasting impact on underwater imaging and signal processing. Looking ahead, his future contributions are likely to expand into AI-driven underwater communication systems and real-time processing algorithms, further advancing the practical applications of his research. His continued focus on image processing algorithms and deep learning will undoubtedly lead to more innovative breakthroughs that enhance the capabilities of underwater technologies, benefiting both scientific exploration and practical communication systems.

Publications Top Notes

  • Cross-Layer Routing Protocol Based on Channel Quality for Underwater Acoustic Communication Networks
    Authors: He, J., Tian, J., Pu, Z., Wang, W., Huang, H.
    Journal: Applied Sciences (Switzerland)
    Year: 2024
  • Underwater Object Classification in SAS Images Based on a Deformable Residual Network and Transfer Learning
    Authors: Gong, W., Tian, J., Liu, J., Li, B.
    Journal: Applied Sciences (Switzerland)
    Year: 2023
  • Underwater Object Classification Method Based on Depthwise Separable Convolution Feature Fusion in Sonar Images
    Authors: Gong, W., Tian, J., Liu, J.
    Journal: Applied Sciences (Switzerland)
    Year: 2022
  • Underwater objects classification method in high-resolution sonar images using deep neural network
    Authors: Zhu, K., Tian, J., Huang, H.
    Journal: Shengxue Xuebao/Acta Acustica
    Year: 2019
  • Small Underwater Objects Classification in Multi-View Sonar Images Using the Deep Neural Network
    Authors: Zhu, K., Tian, J., Huang, H.
    Journal: Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument
    Year: 2020

 

 

Ziyao Jie | Experimental methods | Best Researcher Award

Posted on by High Energy Physics

Dr. Ziyao Jie | Experimental methods | Best Researcher Award

Postdoc at State Grid Jibei Electric Power Co., Ltd. Research Institute in China

Ziyao Jie is a postdoctoral researcher at the State Grid Jibei Electric Power Research Institute. He holds a Ph.D. in Electrical Engineering from Tsinghua University, where his research centered on the microwave plasma-based synthesis of nanomaterials for lithium-ion battery applications. Throughout his academic career, Ziyao has made notable contributions to sustainable energy and plasma science, with a focus on improving energy storage technologies. His work on graphene-coated silicon nanomaterials addresses critical issues in battery performance, such as energy capacity and cycling stability. Ziyao’s research has been widely recognized, with multiple patents and publications in high-impact journals.

Profile:

Education:

Ziyao Jie earned his Ph.D. in Electrical Engineering from Tsinghua University, where he specialized in plasma science and nanomaterials synthesis under the guidance of Professor Guixin Zhang. His doctoral thesis focused on the development of microwave plasma methods for producing graphene-coated silicon nanoparticles, designed to enhance lithium-ion battery performance. During his studies, Ziyao gained a comprehensive understanding of high-voltage technologies, nanomaterial properties, and energy storage solutions, which equipped him to tackle real-world challenges in sustainable energy. His academic excellence is reflected in his deep knowledge of plasma diagnostics and high-temperature material synthesis.

Professional Experience:

Ziyao Jie has amassed significant experience in plasma science and energy storage. Following his doctoral research at Tsinghua University, where he developed innovative methods for synthesizing advanced materials for batteries, he continued as a postdoctoral researcher at the State Grid Jibei Electric Power Research Institute. His current work focuses on high-voltage and energy storage systems, contributing to the development of large-scale, sustainable energy solutions. Ziyao has collaborated on key projects such as the Beijing Science and Technology Planning Project, and his expertise spans the areas of nanomaterial synthesis, waste treatment with plasma, and renewable energy applications.

Research focus:

Ziyao Jie’s research focuses on the intersection of plasma science, nanomaterials, and sustainable energy. His primary area of interest is the synthesis of nanomaterials using microwave plasma technologies, with a particular focus on developing advanced materials for energy storage, such as graphene-coated silicon nanoparticles for lithium-ion batteries. His work aims to address key challenges in energy density, stability, and scalability for future battery technologies. Ziyao is also involved in developing plasma-based waste treatment systems, including medical waste management, using high-temperature plasma torches. His research is distinguished by its potential to revolutionize both energy storage and environmental sustainability.

Awards and Honors:

Ziyao Jie has received numerous accolades for his groundbreaking work in plasma science and nanomaterials. His research on microwave plasma-based synthesis earned him recognition in energy storage circles, particularly for his contributions to improving lithium-ion battery technology. Ziyao was a participant in the Beijing Science and Technology Planning Project, which recognized his innovative work on high-energy and high-voltage technologies. Additionally, his patented inventions, which include advanced methods for medical waste treatment and nanomaterial applications, have further established his reputation as a leading researcher. Ziyao’s contributions have also led to high citation indices, highlighting his influence in the academic community.

Publication Top Notes:

  • Mechanisms of Gas Temperature Variation of the Atmospheric Microwave Plasma Torch
    Z. Jie, C. Liu, S. Huang, G. Zhang
    Journal of Applied Physics, 129 (23), 2021
    Citations: 12
  • Microwave Plasma Torches for Solid Waste Treatment and Vitrification
    Z. Jie, C. Liu, D. Xia, G. Zhang
    Environmental Science and Pollution Research, 30 (12), 32827-32838, 2023
    Citations: 10
  • Imaging Diagnostics and Gas Temperature Measurements of Atmospheric-Microwave-Induced Air Plasma Torch
    S. Huang, C. Liu, Z. Jie, G. Zhang
    IEEE Transactions on Plasma Science, 48 (6), 2153-2162, 2020
    Citations: 10
  • Polymer Dielectrics with Outstanding Dielectric Characteristics via Passivation with Oxygen Atoms through C–F Vacancy Carbonylation
    T.Y. Wang, X.F. Li, Z. Jie, B.X. Liu, G. Zhang, J.B. Liu, Z.M. Dang, Z.L. Wang
    Nano Letters, 23 (18), 8808-8815, 2023
    Citations: 8
  • An Atmospheric Microwave Plasma-Based Distributed System for Medical Waste Treatment
    Z. Jie, C. Liu, D. Xia, G. Zhang
    Environmental Science and Pollution Research, 30 (17), 51314-51326, 2023
    Citations: 6
  • Surface-Wave-Sustained Plasma Synthesis of Graphene@Fe–Si Nanoparticles for Lithium-Ion Battery Anodes
    Z. Jie, Z. Zhang, X. Bai, W. Ma, X. Zhao, Q. Chen, G. Zhang
    Applied Physics Letters, 123 (11), 2023
    Citations: 3
  • Determination of 915-MHz Atmospheric Pressure Air Microwave Plasma Torch (MPT) Parameters
    Z. Jie, C. Liu, D. Xia, Z. Zhang, X. Zhao, G. Zhang
    IEEE Transactions on Plasma Science, 51 (2), 456-465, 2023
    Citations: 2
  • The Treatment of Medical Waste by Atmospheric Microwave Plasma
    D. Xia, C. Liu, Z. Jie, G. Zhang
    2021 IEEE International Conference on Plasma Science (ICOPS), 2021
    Citations: 2
  • Microwave Plasma Torch for Solid Waste Treatment
    Z. Jie, C. Liu, D. Xia, G. Zhang
    IET Digital Library, 2021
    Citations: 2
  • Continuous Batch Synthesis with Atmospheric-Pressure Microwave Plasmas
    Z. Jie, T.Y. Wang, S. Huang, X. Bai, W. Ma, G. Zhang, N. Luo
    iScience, 27 (8), 2024
    Citations: N/A

Conclusion:

Ziyao Jie is a strong candidate for the Best Researcher Award, with his groundbreaking contributions in plasma science and energy storage technologies. His research has direct implications for sustainable energy solutions, positioning him at the forefront of innovations in high-energy physics and computational science. His achievements, particularly his patents and numerous high-impact publications, showcase his potential to make lasting contributions to academia and industry, making him highly suitable for this prestigious award.