Jie Tian | Experimental methods | Best Researcher Award

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.

💼 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.

🔮 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

 

 

Feiqian Wang | Experimental methods | Best Researcher Award

Assoc Prof Dr. Feiqian Wang | Experimental methods | Best Researcher Award

Associate Professor at The First Affiliated Hospital of Xi’an Jiaotong University, China

Dr. Feiqian Wang is an Associate Professor in the Department of Ultrasound at the First Affiliated Hospital of Xi’an Jiaotong University. With a postdoctoral background in respiratory medicine and a combined master’s and doctoral degree in internal medicine, Dr. Wang has become a prominent figure in medical imaging, particularly in ultrasound and contrast-enhanced imaging. She has contributed significantly to the early diagnosis of liver diseases, microvascular invasion, and hepatocellular carcinoma. Dr. Wang holds several leadership roles, including Secretary-General of the Ultrasound Physicians Branch of the Shaanxi Medical Association, and has earned numerous national and international research grants.

🎓Profile

👩‍⚕️ Early Academic Pursuits

Feiqian Wang began her academic journey in medicine at Xi’an Jiaotong University, where she earned her undergraduate degree in Clinical Medicine (2002–2007). This foundational training laid the groundwork for her later academic and clinical achievements. Building on this, she pursued a combined Master’s and Doctoral degree in Internal Medicine, which she completed in 2012. Feiqian’s early focus on internal medicine provided her with critical clinical skills, which she later applied to the field of ultrasound imaging. She further refined her expertise as a Postdoctoral Researcher in Respiratory Medicine from 2016 to 2022, a period during which she broadened her research interests and honed her academic focus on diagnostic imaging and its applications in liver and cancer diagnostics.

🏥 Professional Endeavors

Since joining the First Affiliated Hospital of Medical School, Xi’an Jiaotong University, Feiqian Wang has consistently advanced in her medical career. She currently holds the position of Associate Professor in the Department of Ultrasound, where she leads cutting-edge research projects while providing expert medical care. Prior to this role, Feiqian served as an Attending Physician (2019–2021) and as both a Resident and Chief-Resident (2012–2018). Her extensive clinical experience in ultrasound, particularly in hepatocellular carcinoma (HCC) imaging, has shaped her research endeavors and her contributions to the medical field. Feiqian’s professional achievements also include her positions as Secretary-General of the Ultrasound Physicians Branch of the Shaanxi Medical Association and as a reviewer for various high-impact journals.

🔬 Contributions and Research Focus

Feiqian Wang’s research focuses primarily on advanced ultrasound imaging technologies, particularly in the early diagnosis of liver diseases such as hepatocellular carcinoma (HCC). Her work integrates multiple imaging modalities, including contrast-enhanced ultrasound (CEUS) and magnetic resonance imaging (MRI), to assess microvascular invasion and other critical markers of HCC. She has secured numerous research grants, notably from the National Natural Science Foundation of China, which underscores the significance and impact of her work. Feiqian’s research into hepatocellular carcinoma, fusion imaging, and elastography technologies continues to contribute to the diagnostic precision and personalized treatment strategies in oncology. Moreover, her innovative approach to combining S-CEUS, U-CEMRI, and SWI imaging in diagnosing HCC has opened new avenues in clinical practice.

🌍 Impact and Influence

Feiqian Wang’s research has had a profound influence in the realm of diagnostic imaging, particularly in the field of oncology and liver diseases. Her pioneering work on CEUS and MRI fusion imaging, along with her nomogram models for predicting vascular patterns in HCC, has contributed to advancements in non-invasive diagnostics. Feiqian’s research has been widely published in leading medical journals such as Radiology, European Journal of Radiology Open, and Biosci Trends. These publications are frequently cited by other researchers, showcasing the broad influence of her work in the scientific community. Additionally, her contributions to patent innovations in ultrasound technology underscore her role in driving forward new medical technologies and improving clinical practices.

🏅 Academic Citations

Feiqian Wang’s research is well-recognized in the academic community, with numerous publications in high-impact journals over the past five years. Her work has earned her respect both nationally and internationally, with publications cited widely in medical and imaging literature. For example, her study on “Contrast-Enhanced Ultrasound and MRI Fusion Imaging for Hepatocellular Carcinoma Diagnosis” has become a reference point for other researchers in the field. These citations reflect the high quality of her work and its relevance to the evolving medical landscape. Feiqian’s ability to secure multiple research grants also highlights her esteemed position within academic circles, further cementing her credibility as a leading expert in her field.

🖥️ Technical Skills

Feiqian Wang is highly skilled in advanced imaging technologies, with expertise in contrast-enhanced ultrasound (CEUS), elastography, and fusion imaging techniques. She is proficient in integrating various diagnostic methods, such as S-CEUS, U-CEMRI, and SWI, to improve early detection and diagnosis of liver diseases. Her technical proficiency extends to the use of deep learning and AI models for image analysis, as evidenced by her research on breast nodule classification using deep convolutional neural networks. Feiqian’s technical acumen in ultrasound imaging not only enhances her clinical diagnostic abilities but also places her at the forefront of innovative research in the field.

🎓 Teaching Experience

As an Associate Professor in the Department of Ultrasound, Feiqian Wang plays an essential role in shaping the next generation of medical professionals. She has taught and mentored undergraduate and postgraduate students, offering training in ultrasound diagnostic techniques and medical imaging. Her commitment to education is further demonstrated by her leadership in various academic committees, including those related to ultrasound medical engineering. Feiqian’s teaching approach is grounded in practical, hands-on training, ensuring that her students acquire the necessary skills to apply diagnostic imaging techniques in clinical settings.

🌟 Legacy and Future Contributions

Feiqian Wang’s legacy is built upon her groundbreaking research, her commitment to improving diagnostic techniques, and her contributions to medical education. Her work in imaging technology has already revolutionized certain aspects of HCC diagnosis and is expected to have an enduring impact on clinical practices. As a leading figure in her field, Feiqian is poised to continue contributing to advancements in ultrasound and medical imaging technologies. In the future, she plans to further develop multimodal imaging strategies for early disease detection and improve the integration of AI and machine learning in medical diagnostics. Her ongoing research in early liver imaging diagnosis and its clinical applications promises to have a significant impact on the early detection of liver diseases, ultimately saving lives through more precise and timely interventions.

🏆 Awards and Recognition

Throughout her career, Feiqian Wang has received numerous accolades for her contributions to science and medicine. She was awarded the second prize in the 2018 Science and Technology Progress Award of Shaanxi Province for her work on microinflammation mechanisms in CKD patients. Additionally, her excellence in ultrasound imaging was recognized with the “Best Slide Making Award” in the China Contrast-Enhanced Ultrasonography Congress. These accolades, along with her academic and professional achievements, highlight her exceptional skills and dedication to advancing medical knowledge and practice.

📖Publication Top Notes

High Spatiotemporal Resolution Contrast-Free Ultrasound Microvascular Imaging Using Adaptive Weight-Based Nonlinear Compounding
    • Authors: Liyuan Jiang, Hanbing Chu, Yang Liu, Jiacheng Liu, Xiao Su, Yichen Yan, Meiling Liang, Yiran Chen, Chaoyang Zhang, Feiqian Wang et al.
    • Journal: IEEE Transactions on Instrumentation and Measurement
    • Year: 2024
A Nomogram Based on Features of Ultrasonography and Contrast-Enhanced CT to Predict Vessels Encapsulating Tumor Clusters Pattern of Hepatocellular Carcinoma
    • Authors: Litao Ruan, Jingtong Yu, Xingqi Lu, Kazushi Numata, Dong Zhang, Xi Liu, Xiaojing Li, Mingwei Zhang, Feiqian Wang
    • Journal: Ultrasound in Medicine & Biology
    • Year: 2024
Added Value of Ultrasound-Based Multimodal Imaging to Diagnose Hepatic Sclerosed Hemangioma before Biopsy and Resection
    • Authors: Feiqian Wang, Kazushi Numata, Hiromi Nihonmatsu, Makoto Chuma, Naomi Ideno, Akito Nozaki, Katsuaki Ogushi, Mikiko Tanab, Masahiro Okada, Wen Luo et al.
    • Journal: Diagnostics
    • Year: 2022
Accurate Assessment of Vascularity of Focal Hepatic Lesions in Arterial Phase Imaging
    • Authors: Feiqian Wang, Kazushi Numata, Litao Ruan
    • Journal: Radiology
    • Year: 2020