Shantao Ping | Computer Vision | Best Researcher Award

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Mr. Shantao Ping | Computer Vision | Best Researcher Award

Associate Senior Engineer, Qiyuan Lab, China

Shantao Ping is an Associate Senior Engineer at Qiyuan Lab, specializing in computer vision, artificial intelligence, and large-scale model algorithms. With a Master’s degree in Computer Science, Shantao has a proven track record of driving innovation through cutting-edge research and development. He has contributed to over 28 research and industry projects and holds 14 national invention patents. His collaborative project with Baidu, an AI-powered medical question-answering system, significantly enhanced user engagement and earned him the prestigious Baidu Best Engineer Award. Shantao is also an active member of the Chinese Institute of Command and Control, where he continuously advances the frontiers of intelligent simulation, image processing, and natural language processing. His work focuses on solving complex engineering problems and has made substantial contributions to simulation scene construction and few-shot object recognition. Passionate about applied research, Shantao Ping is committed to shaping the future of intelligent computing through practical and scalable solutions.

Publication Profile

Education

Shantao Ping holds a Master’s degree in Computer Science from an esteemed institution, equipping him with solid expertise in artificial intelligence, computer vision, and advanced computational algorithms. He also holds the professional qualification of Associate Senior Engineer, recognized by the Ministry of Human Resources and Social Security (MOHRSS), Beijing, China. This designation reflects his deep technical proficiency and leadership in engineering research and development. Throughout his academic and professional training, Shantao focused on bridging theoretical foundations with real-world applications, emphasizing innovation in structured light calibration, simulation modeling, and machine learning-based image processing. His educational journey laid the groundwork for his current role as a highly effective engineer, capable of contributing to both research excellence and industrial breakthroughs. Shantao’s education emphasizes interdisciplinary collaboration, practical application, and a research-driven approach that aligns perfectly with his long-standing commitment to technological advancement and cutting-edge innovation in the rapidly evolving fields of AI and computer vision.

Experience

Shantao Ping is currently an Associate Senior Engineer at Qiyuan Lab, where he has spearheaded numerous high-impact projects in computer vision, AI, and simulation technologies. Over his career, he has successfully completed 28 research and consultancy projects, including a notable collaboration with Baidu to develop an AI-powered medical Q&A system that significantly improved user engagement metrics. His career highlights include leading teams in the development of large-scale model algorithms, simulation scene construction, and few-shot object recognition frameworks. Shantao’s practical experience is reinforced by 14 published or in-process patents and multiple software development achievements, including tools for multi-type algorithm execution and sonar simulation imaging. His work has consistently demonstrated high relevance to industry needs and national innovation strategies. Recognized with the Baidu Best Engineer Award, Shantao continues to push the boundaries of applied AI and intelligent systems. He is also actively involved in the Chinese Institute of Command and Control, enhancing his contributions to the field.

Research Focus

Shantao Ping’s research is primarily centered on computer vision, image processing, natural language processing (NLP), and foundation models. His work addresses critical challenges in simulation scene reconstruction, few-shot object recognition, structured light calibration, and human-computer interaction assisted by large models. He focuses on developing algorithms that integrate simulation with AI to achieve realistic scene modeling and real-time data processing. Shantao is particularly interested in the intersection of AI and simulation, leveraging intelligent algorithms to enhance perception, decision-making, and scene understanding in complex environments. His innovative research in multi-object tracking and global graph matching is paving the way for advanced applications in autonomous systems and smart interaction platforms. Through national patents and practical deployments, he has made significant strides in developing intelligent, scalable solutions that are not only theoretically sound but also practically impactful, contributing directly to the fields of healthcare, simulation technology, and large-scale data interaction.

Publication Top Notes

  1. Multi-view Multi-object Tracking Based on Global Graph Matching Structure (Conference Paper)

    • Authors: Shantao Ping, Chao Li, Hao Sheng, Jiahui Chen, Zhang Xiong

    • Summary: This work proposes a novel global graph matching framework for tracking multiple objects across multiple viewpoints, significantly improving tracking accuracy in complex scenes.

  2. A Method and Apparatus for Specific Target Reconnaissance by Unmanned Aerial Vehicle (Patent)

    • Authors: Shantao Ping, Ying He

    • Summary: Introduces a UAV-based reconnaissance system with enhanced precision for specific target detection in dynamic environments.

  3. A Method, Apparatus, and Device for 3D Scene Construction (Patent)

    • Authors: Shantao Ping, Xulong Ma, Ying He

    • Summary: Details a system for efficient 3D scene modeling using intelligent algorithms, optimizing both speed and accuracy.

  4. Method for Human-Computer Interaction Assisted by Large Models (Patent)

    • Authors: Shantao Ping, Xulong Ma, Ying He, Xiaoqiang Jin, Pinjie Li, Qianchuan Zhao

    • Summary: Presents a human-computer interaction framework enhanced by large foundational models for improved user experience and system adaptability.

  5. Method, Apparatus, Device, and Storage Medium for Generating Sonar Simulated Images (Patent)

    • Authors: Shantao Ping, Xulong Ma, Ying He, Jiacheng Li

    • Summary: Describes a sonar image simulation method that increases the fidelity and reliability of underwater detection simulations.

Conclusion

Shantao Ping is a highly capable, application-driven researcher with an impressive track record of industry-relevant projects, innovative patents, and impactful collaborations, particularly in AI and computer vision. The strong applied research portfolio and demonstrated ability to solve real-world problems make him a solid candidate for the Best Researcher Award. However, to fully align with the traditional benchmarks of this award (which often emphasize academic citations and international recognition), increasing the number of SCI/Scopus journal publications, improving citation metrics, and pursuing more visible academic leadership roles would be beneficial.

Tieshu Fan | Rotor Dynamics | Best Researcher Award

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Dr. Tieshu Fan | Rotor Dynamics | Best Researcher Award

Principle Specialist, Pratt & Whitney Canada, Canada

Dr. Tieshu Fan is an accomplished rotordynamic engineer with over nine years of experience in technical solution development and aerospace research. His expertise lies in turbomachinery, vibration analysis, and rotor-bearing systems, with a particular focus on squeeze film damper (SFD) technology for aircraft engines. Dr. Fan has worked extensively at Pratt & Whitney Canada, contributing to engine system optimization, troubleshooting, and advanced rotordynamic analysis. He has published several influential research articles in top-tier journals and actively collaborated with academic and industry partners to bridge theoretical innovation with practical applications. With a PhD and Master’s degree from the University of Toronto and a Bachelor’s degree from Lanzhou University, Dr. Fan has also contributed significantly to academia through teaching and mentoring. His dedication to research, engineering excellence, and knowledge transfer positions him as a key contributor in the field of rotor dynamics and aerospace engineering.

Professional Profile

ORCID Profile

🎓 Education

Dr. Tieshu Fan holds a Doctor of Philosophy (2015–2020) and a Master of Applied Science (2013–2015) in Mechanical and Industrial Engineering from the University of Toronto, Canada. His doctoral research focused on advanced squeeze film damper (SFD) modeling and rotor vibration analysis for aircraft engine applications, under the supervision of Dr. Kamran Behdinan. Prior to his studies in Canada, Dr. Fan earned his Bachelor of Science in Mechanical and Civil Engineering from Lanzhou University, China (2008–2012). His educational journey provided him with a solid foundation in mechanical systems, structural analysis, and fluid dynamics. Through his studies, Dr. Fan developed strong analytical, computational, and experimental skills, which he has effectively applied in both academic research and industrial projects. His education not only shaped his technical expertise but also fostered his leadership in multidisciplinary collaborations.

💼 Experience

Dr. Tieshu Fan is currently serving as a Principal Specialist and Rotordynamic Engineer at Pratt & Whitney Canada, where he has led numerous projects in rotordynamic analysis, engine system validation, vibration troubleshooting, and structural load assessment. His industrial career spans from 2018 and resumed from 2022 to the present, where he provided critical support across engine development and service lifecycles. As a Post-doctoral Fellow at the University of Toronto (2020–2021), Dr. Fan spearheaded cutting-edge research on SFD models and developed advanced software tools for engine simulations. He also served as a research assistant in prominent laboratories at the University of Toronto, focusing on multibody frictional contact problems and rotor vibration analysis. Additionally, Dr. Fan dedicated seven years to teaching and mentoring as a Teaching Assistant and TA Coordinator, covering a wide range of engineering and mathematics courses. His combined academic and industry experience showcases his comprehensive expertise in rotor dynamics and turbomachinery.

🔬 Research Focus

Dr. Tieshu Fan’s research primarily centers on rotor dynamics, squeeze film damper (SFD) modeling, vibration analysis, and turbomachinery stability. His work has significantly advanced the understanding of fluid-structure interactions in rotating machinery, focusing on the dynamic behavior and damping mechanisms of rotor-bearing systems. He specializes in developing analytical and computational models to predict engine performance, assess structural integrity, and optimize vibration control. His research also explores cavitation effects, lubricant dynamics, and high-speed rotor systems relevant to aerospace engineering. Dr. Fan’s studies integrate theoretical modeling, experimental validation, and software development to support next-generation engine designs. His cross-disciplinary approach ensures practical applicability in industrial settings, particularly within aircraft engine manufacturing and maintenance. Through continuous collaboration with academia and industry, Dr. Fan is contributing to safer, more reliable, and more efficient turbomachinery systems. His work is particularly valuable for advancing the field of aircraft engine vibration control and system integration.

📚 Publication Top Notes

  1. An Analytical Turbulence Model for Squeeze Film Damper Short-Bearing Analysis
    📖 Applied Mechanics, 2025-07-01
    🔗 DOI: 10.3390/applmech6030048
    👥 Authors: Tieshu Fan, Kamran Behdinan
    Summary: Developed a turbulence model for short-bearing squeeze film dampers, enhancing rotordynamic prediction accuracy for high-speed rotating machinery.

  2. An Analytical Model for Open-Ended Squeeze Film Damper with a Circumferential Central Groove
    📖 Journal of Engineering Tribology, 2021
    🔗 DOI: 10.1177/1350650120987652
    👥 Authors: Tieshu Fan, Kamran Behdinan
    Summary: Presented an analytical model addressing groove effects in open-ended SFDs, improving vibration control in rotor systems.

  3. Vibration Analysis of Rotor-Bearing System Using Polynomial Interpolation for Squeeze Film Damper Models
    📖 SN Applied Sciences, 2020
    🔗 DOI: 10.1007/s42452-020-03783-y
    👥 Authors: Tieshu Fan, Kamran Behdinan
    Summary: Introduced polynomial interpolation methods to enhance the vibration analysis of rotor-bearing systems with SFDs.

Conclusion

Tieshu Fan is highly suitable for the Best Researcher Award, particularly in engineering and applied sciences with aerospace applications. His work demonstrates technical depth, practical relevance, and a consistent trajectory of contribution. To further solidify his standing, broadening his international research collaborations, increasing his citation footprint, and expanding mentorship roles would add extra strength to his already impressive profile.