Zhao Song| Machine Vision| Best Researcher Award

Dr. Zhao Song| Machine Vision| Best Researcher Award

Associate Researcher,Β  Hangzhou Innovation Research Institute of Beihang University, China

πŸ”¬ Short BiographyΒ πŸŒΏπŸ’ŠπŸ“š

Dr. Zhao Song is an Associate Researcher at the Hangzhou Innovation Research Institute of Beihang University, China. His work focuses on Machine Vision, where he has made impactful contributions to intelligent visual systems, image recognition, and deep learning applications in automation and robotics. Dr. Song’s research bridges cutting-edge algorithm development with real-world industrial applications, earning him recognition in both academic and technology innovation spheres. As a dedicated scholar and innovator, he has published in top-tier journals and actively collaborates on interdisciplinary projects that advance machine vision technologies. His outstanding contributions make him a strong candidate for the Best Researcher Award in Machine Vision

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πŸŽ“ Education

Dr. Zhao Song has a solid educational background that reflects his expertise in automation, systems engineering, and artificial intelligence. He earned his Bachelor’s degree in Automation from Shandong University of Science and Technology (2007–2011). He then pursued a Master’s degree in Systems Engineering from Nankai University (2011–2014), where he laid the groundwork for his algorithmic and system design skills. His academic journey culminated with a Ph.D. in Pattern Recognition and Intelligent Systems from the Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences (2017–2021), focusing on photometric stereo and 3D reconstruction technologies.

πŸ’Ό Experience

Dr. Song began his professional career as an Algorithm Engineer at Guangzhou GRG Banking Equipment Co., Ltd. (2014–2016), where he specialized in embedded C programming for ATM systems. He then transitioned to research as an assistant at the Chinese Academy of Sciences (2016–2017). His postdoctoral research at Huawei Technologies Co., Ltd. (2021–2023) focused on integrating material modeling with structured light systems for digital human modeling. Since September 2023, he has been serving as a Senior Associate Researcher at the Hangzhou Innovation Research Institute of Beihang University, where he leads projects in structured light, photometric modeling, and digital human generation.

πŸ› οΈ Skills

Dr. Song possesses a comprehensive skill set in 3D reconstruction, photometric stereo, structured light systems, and material measurement and modeling. His technical proficiency spans C/C++ programming, GPU parallel computing, OpenCV, and real-time image processing algorithms. He is capable of independently designing, building, and optimizing structured light systems for micrometer-level reconstruction. His interdisciplinary approach combines optics, computer vision, and rendering algorithms, making him adept at solving complex problems in material-aware geometry acquisition.

πŸ”¬ Research Focus

Dr. Song’s research revolves around 3D reconstruction and material acquisition, with a core focus on photometric stereo, binary stripe structured light, and integrated geometry-material modeling systems. During his Ph.D., he proposed innovative LED-based photometric stereo techniques and developed micrometer-level reconstruction methods for reflective surfaces. As a postdoc, he introduced a novel fusion framework combining photometric cues with structured light for enhanced accuracy. His recent work includes pioneering the first structured light system capable of outputting complete material maps (diffuse, specular, roughness, normal) and investigating DMA correction techniques to improve reconstruction under varying lighting and material conditions. He also contributed to high-fidelity digital human creation using Lightstage systems and NeRF-based geometry fusion.

πŸ† Awards & Achievements

Dr. Song has made significant contributions to both academia and industry. His work has led to multiple high-impact publications in journals like Optics Express, Optics and Lasers in Engineering, and Sensors. He has authored several national patents, including groundbreaking methods for 3D object reconstruction and material-aware geometry optimization. His innovations in integrating structured light with material modeling have been successfully translated into commercial applications, notably in digital human rendering. Recognized for his originality and technical acumen, Dr. Song is a prominent candidate for leading awards in Machine Vision and 3D Imaging Systems.

  • Title: A novel calibration method for uniaxial MEMS-based structured light system with linear transition function

    Journal: Measurement

    DOI: 10.1016/j.measurement.2025.117969

    Year: 2025

    Authors: Yuping Ye, Gang Zhou, Xiujing Gao, Zhenghui Hu, Yi Chen, Zhao Song, Zhan Song

    Citations: Not yet available (published for December 2025β€”may not have citations yet)

    Title: Micrometer-level 3D measurement techniques in complex scenes based on stripe-structured light and photometric stereo

    Journal: Optics Express

    DOI: 10.1364/OE.401850

    Publication Date: October 26, 2020

    Authors: Zhao Song, Zhan Song, Juan Zhao, Feifei Gu

    Citations: 43 citations

🏁conclusion:

Dr. Zhao Song is an excellent candidate for the Best Researcher Award. His proven ability to develop cutting-edge, commercial-ready solutions, along with original research that pushes the frontiers of 3D computer vision and graphics, strongly justifies his nomination. Recognizing him with this award would encourage continued innovation at the intersection of vision, AI, and human digitalization.

AFOLABI AWODEYI | Computer Vision | Best Researcher Award

Mr. AFOLABI AWODEYI | Computer Vision | Best Researcher Award

Lecturer , Southern Delta University Ozoro, Delta State ,Nigeria.

πŸ”¬ Short BiographyΒ πŸŒΏπŸ’ŠπŸ“š

πŸ‘¨β€πŸ« Engr. Afolabi Awodeyi is a dedicated Lecturer II at Southern Delta University, Ozoro, Delta State, Nigeria πŸ‡³πŸ‡¬. He is currently pursuing a Ph.D. in Computer Engineering at the University of Uyo. With a distinction in his M.Eng. and multiple diplomas, his academic journey reflects a deep passion for engineering education and innovation πŸ’‘. A registered engineer with COREN πŸ› οΈ and a proud member of IAENG 🌍, Engr. Awodeyi has authored several impactful publications in Scopus-indexed journals πŸ“š. His research focuses on computer vision, biometrics (face, iris, fingerprint) πŸ§ πŸ‘οΈ, and intelligent hardware systems πŸ€–. He’s developed CNN-based biometric fusion systems and self-organizing robots, contributing significantly to access control and smart automation πŸ”. His collaborative spirit and commitment to excellence make him a notable force in the tech research landscape πŸš€.

Profile

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πŸŽ“ Education

πŸ“– 1. Development of an Electronic Weighing Indicator for Digital Measurement

πŸ‘¨β€πŸ”¬ Authors: E. Akindele Ayoola, I. Awodeyi Afolabi, O. Matthews Victor, …
πŸ“… Year: 2018
πŸ”’ Citations: 21

πŸ“– 2. Design and Construction of a Panic Button Alarm System for Security Emergencies

πŸ‘¨β€πŸ”¬ Authors: A. Afolabi, O. Moses, S. Makinde Opeyemi, A. Ben-Obaje Abraham, …
πŸ“… Year: 2018
πŸ”’ Citations: 19

πŸ“– 3. Development of an Intelligent Smart Shopping Cart System

πŸ‘¨β€πŸ”¬ Authors: A.E. Ayoola, A.I. Afolabi, V.W. Oguntosin, O.A. Alashiri, V.O. Matthews, …
πŸ“… Year: 2019
πŸ”’ Citations: 4

πŸ“– 4. Effective Preprocessing Techniques for Improved Facial Recognition under Variable Conditions

πŸ‘¨β€πŸ”¬ Authors: A.I. Awodeyi, O.A. Ibok, I. Omokaro, J.U. Ekwemuka, M.O. Ighofiomoni
πŸ“… Year: 2025
πŸ”’ Citations: 1

πŸ“– 5. Cyber-Physical Systems Attacks and Countermeasures

πŸ‘¨β€πŸ”¬ Authors: P. Asuquo, M. Usoh, B. Stephen, C. Aneke, A. Awodeyi
πŸ“… Year: 2022
πŸ”’ Citations: 1

πŸ“– 6. Comparative Analysis of Preprocessing Techniques for Enhanced Facial Recognition under Challenging Conditions

πŸ‘¨β€πŸ”¬ Authors: A. Awodeyi, O. Ibok, O. Idama, J. Ekwemuka, D. Ebem, R. Mamah, O. Ugwu
πŸ“… Year: 2025
πŸ”’ Citations: –

πŸ“– 7. Development of a Real-Time Auto Encoder Facial Occlusion Recognition System Framework

πŸ‘¨β€πŸ”¬ Authors: A. Awodeyi, P. Asuquo, C. Kalu
πŸ“… Year: 2024
πŸ”’ Citations: –

πŸ“– 8. Development of a Self-Organizing Multipurpose Mobile Robot

πŸ‘¨β€πŸ”¬ Authors: A. Awodeyi, A.E. Akindele, E.E. Dan, O.A. Ibok
πŸ“… Year: 2024
πŸ”’ Citations: –

πŸ“– 9. The Development of a Self-Organizing Multipurpose Mobile Robot

πŸ‘¨β€πŸ”¬ Author: A. Awodeyi
πŸ“… Year: 2024
πŸ”’ Citations: –

πŸ“– 10. Design and Construction of a Microcontroller-Based Automated Intelligent Street Lighting System

πŸ‘¨β€πŸ”¬ Authors: M.V.O. Awodeyi Afolabi, Samuel Isaac Adekunle, Akindele Ayoola
πŸ“… Year: 2018
πŸ”’ Citations: –

🏁conclusion:

πŸŽ“ Yes, Engr. Afolabi Awodeyi is a highly deserving candidate for the Best Researcher Award πŸ†. His unwavering dedication to innovation πŸ’‘, interdisciplinary research 🀝, and academic excellence πŸ“˜ highlights his status as a forward-thinking scholar in the field of computer engineering. With impactful contributions to biometrics πŸ”, intelligent systems πŸ€–, and facial recognition 🧠, his research holds both academic and real-world relevance. As a COREN-registered engineer and active member of IAENG 🌍, he bridges theory and practice, shaping the future of smart technologies. While there is room to grow in citations and patents πŸ“ˆ, his evolving research portfolio shows immense promise. Recognizing Engr. Awodeyi at this stage will not only honor his contributions but also inspire further high-impact and industry-oriented advancements πŸ”¬. His profile perfectly aligns with the award’s mission to uplift emerging leaders driving excellence in research and innovation πŸš€. Truly, he embodies the spirit of modern engineering research 🌟.