Prof. Yanlong Tai | Machine Learning | Best Researcher Award

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Prof. Yanlong Tai | Machine Learning | Best Researcher Award

Prof. Yanlong Tai, shenzhen institute of science and technology, China academic of science, China

Prof. Dr. Yanlong Tai is a distinguished researcher and professor in the field of smart sensing and flexible electronics. He is the Principal Investigator of the Smart-Sensing-Lab (SM-SE Lab.-SIAT) and serves as the Head of both the SIAT-UAEU International Smart Sensing & Energy Joint Lab and the SIAT-Fudan University (Zhuhai) Joint Innovation Center. Currently, he is a Full Professor at the Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS), China, and a Joint Professor at the University of Science & Technology Shenzhen. Dr. Tai earned his Ph.D. from Fudan University, China (2009-2012), and was a visiting student at OHM University, Germany (2011-2012). He also holds Bachelor’s and Master’s degrees from Anhui University (2001-2008). His professional journey includes extensive research experience across multiple international institutions. He served as a Postdoctoral Researcher at University of California, Davis, USA (2012-2013), Fraunhofer ENAS, Chemnitz, Germany (2013-2014), and KAUST, Saudi Arabia (2014-2017). He later worked as a Research Scientist at Masdar Institute, UAE (2017-2019) before joining SIAT as a Professor in 2019.

Professional Profile:

GOOGLE SCHOLAR

Summary of Suitability for Best Researcher Award – Prof. Dr. Yanlong Tai

Prof. Dr. Yanlong Tai is an outstanding researcher and innovator, making him a highly suitable candidate for the Best Researcher Award. His extensive experience, leadership roles, and impactful research in smart materials, energy harvesting, and wearable electronics position him as a global leader in advanced sensing technologies.

🎓 Education

  • Ph.D. (2009 – 2012) – Fudan University, China

  • Visiting Student (2011 – 2012) – OHM University, Germany

  • Bachelor & Master Degree (2001 – 2008) – Anhui University, China

💼 Work Experience

  • Professor (2019 – Present) – Shenzhen Institutes of Advanced Technology (SIAT), CAS, China

  • Research Scientist (2017 – 2019) – Masdar Institute, United Arab Emirates

  • Postdoc Researcher (2014 – 2017) – King Abdullah University of Science and Technology (KAUST), Saudi Arabia

  • Postdoc Researcher (2013 – 2014) – Fraunhofer ENAS, Chemnitz, Germany

  • Postdoc Researcher (2012 – 2013) – University of California, Davis, USA

🏆 Achievements, Awards & Honors

  • 📌 Principal Investigator of Smart-Sensing-Lab (SM-SE Lab.-SIAT)

  • 🏅 Head of SIAT-UAEU International Smart Sensing & Energy Joint Lab

  • 🏅 Head of SIAT-Fudan University (Zhuhai) Joint Innovation Center

  • 🎖️ Full Professor at SIAT, CAS, Shenzhen, China

  • 🎖️ Joint Professor at the University of Science & Technology, Shenzhen

Publication Top Notes:

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Mr. Fangzhou Lin | Deep Learning | Best Scholar Award

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Mr. Fangzhou Lin | Deep Learning | Best Scholar Award 

Mr. Fangzhou Lin, Hong Kong University of Science and Technology, Hong Kong

Fangzhou Lin is a Ph.D. researcher in Civil Engineering at the Hong Kong University of Science and Technology (HKUST), specializing in deep learning, machine vision, construction robots, and multimodal data fusion. He holds a Bachelor’s degree in Civil Engineering from Fuzhou University (2015-2019) and a Master’s degree in Structural Engineering from Southeast University (2019-2022). Fangzhou Lin’s research focuses on the integration of artificial intelligence and robotics in construction automation, with applications in fire safety inspection, resource management, visual measurement, and quality assessment. His work has been published in leading journals such as Automation in Construction, Computer-Aided Civil and Infrastructure Engineering, and Advanced Engineering Informatics. He has contributed to multiple cutting-edge studies on robotic systems for construction site management, vision-based measurement techniques, and reinforcement learning-based scheduling for electric concrete vehicles. As an emerging scholar in construction automation and AI-driven inspection technologies, Fangzhou Lin actively collaborates on multi-disciplinary research projects to enhance efficiency, safety, and sustainability in the built environment. His contributions to automated reality capture, rebar positioning, and construction robotics are shaping the future of intelligent construction and infrastructure development.

Professional Profile:

SCOPUS

Suitability of Fangzhou Lin for the Best Scholar Award

Fangzhou Lin is an outstanding early-career scholar with a strong background in deep learning, machine vision, construction robotics, and multimodal data fusion within the field of civil engineering. His academic trajectory, research productivity, and innovative contributions make him a compelling candidate for the Best Scholar Award. Below is a detailed assessment of his suitability based on key criteria.

🎓 Education

  • 2015.09 – 2019.06 | Fuzhou University – Bachelor’s Degree in Civil Engineering
  • 2019.09 – 2022.06 | Southeast University – Master’s Degree in Structural Engineering
  • 2022.09 – Present | Hong Kong University of Science and Technology – Ph.D. in Civil Engineering

🏗️ Work & Research Experience

  • Expertise in: Deep learning, machine vision, construction robots, multimodal data fusion
  • Published in top journals such as Automation in Construction and Computer-Aided Civil and Infrastructure Engineering
  • Conducting research on:
    • 🔥 Fire Safety Inspection using AI-driven visual inspection
    • 🤖 Robotics for Construction Management with multi-task planning and automatic grasping
    • 🏗️ BIM-integrated Reality Capture for indoor inspection using multi-sensor quadruped robots
    • 🎯 Vision-based Monitoring for assembly alignment of precast concrete bridge members

🏆 Achievements & Awards

  • Published multiple high-impact journal papers 📚
  • Lead researcher on innovative construction technology projects 🔍
  • Contributed to advanced AI-driven automation for civil engineering 🤖
  • Research works under review in prestigious engineering journals 🏅
  • Collaborated with leading experts in civil engineering and robotics 🤝

Publication Top Notes:

Efficient visual inspection of fire safety equipment in buildings

 

Dr. Peng Zhi | Deep Learning | Best Researcher Award

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Dr. Peng Zhi | Deep Learning | Best Researcher Award 

Dr. Peng Zhi, Lanzhou University, China

Peng Zhi is a Ph.D. candidate in Computer Science at Lanzhou University, China, specializing in computer vision, deep learning, and autonomous driving. He earned his Bachelor’s and Master’s degrees in Computer Science and Technology from Lanzhou University in 2017 and 2020, respectively. His research focuses on LiDAR-camera fusion, 3D object detection, and AI applications in intelligent transportation systems. He has published several high-impact papers in renowned journals and conferences, contributing to advancements in autonomous vehicle perception and artificial intelligence. Additionally, he has co-authored the book Theories and Practices of Self-Driving Vehicles, further solidifying his expertise in the field.

Professional Profile:

ORCID

Summary of Suitability for the Best Researcher Award

Peng Zhi is a strong candidate for the Best Researcher Award, given his innovative contributions to computer vision, deep learning, and autonomous driving. As a Ph.D. candidate at Lanzhou University, he has been actively involved in research that enhances LiDAR-based 3D object detection, cross-domain generalization, and deep learning applications in autonomous systems.

🎓 Education

  • Ph.D. in Computer Application Technology (2021 – Present)
    Lanzhou University, Lanzhou, China
  • Master’s in Computer System Architecture (2017 – 2020)
    Lanzhou University, Lanzhou, China
  • Bachelor’s in Computer Science and Technology (2013 – 2017)
    Lanzhou University, Lanzhou, China

💼 Work Experience

  • Ph.D. Candidate & Researcher (2021 – Present)
    Lanzhou University, Lanzhou, China

    • Conducts advanced research in computer vision, deep learning, and autonomous driving
    • Publishes in top-tier journals and conferences
    • Develops LiDAR and camera fusion models for 3D object detection

🏆 Achievements & Contributions

  • Published Multiple Research Papers 📄 in top journals and conferences, including Tsinghua Science and Technology, Electronic Research Archive, and IEEE ITSC
  • Author of a Book on Self-Driving Vehicles 📘 Theories and Practices of Self-Driving Vehicles (Elsevier, 2022)
  • Developed DefDeN Model 🤖 A deformable denoising-based LiDAR and camera feature fusion model for 3D object detection
  • Research on Autonomous Driving 🚗 Focused on boundary distribution estimation and cross-domain generalization for LiDAR-based 3D object detection

🏅 Awards & Honors

  • Best Paper Award 🏆 at an International Conference on Intelligent Transportation Systems (ITSC)
  • Outstanding Researcher Award 🎖️ at Lanzhou University for contributions to AI and autonomous driving
  • National Scholarship 🏅 for academic excellence in computer science and AI research

Publication Top Notes:

Cross-Domain Generalization for LiDAR-Based 3D Object Detection in Infrastructure and Vehicle Environments