Jian Zhao | Image processing | Best Researcher Award

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Dr. Jian Zhao | Image processing | Best Researcher Award

Lecturer at Nanjing Institute of Technology, China

Dr. Jian Zhao is a Lecturer at the School of Computer Engineering, Nanjing Institute of Technology. He earned his PhD in Physical Electronics from Southeast University (2019) and was a visiting scholar at Newcastle University, UK, specializing in Stereoscopic Vision. His research focuses on light field displays, deep learning for micro-expression analysis, and ultrafast spatial light modulation. He has secured multiple grants, including from the National Natural Science Foundation of China. Dr. Zhao has published in OPTICS EXPRESS, IEEE Photonics Journal, and IET Image Processing, contributing significantly to computational imaging and display technologies. 📡📸

Publication Profile

Orcid

Educational Background 🎓📚

Dr. Jian Zhao holds a Doctoral Degree in Physical Electronics from Southeast University (2012-2019), where he specialized in advanced optical and electronic systems. To enhance his expertise, he pursued a research stay as a visiting student at Newcastle University, UK (2017-2018), focusing on stereoscopic vision. His academic journey reflects a strong foundation in optics, imaging, and display technologies, equipping him with the skills to innovate in light field displays and computational imaging. His international experience has further broadened his research perspective, enabling him to contribute to cutting-edge developments in visual perception and display systems. 🌍🔬

Research and Academic Work Experience 🔬📡

Dr. Jian Zhao has led multiple research projects in cutting-edge imaging and display technologies. He has secured funding from the National Natural Science Foundation of China for projects on deep network models for micro-expression analysis in complex environments and ultrafast phase-type spatial light modulation using disordered structure metasurfaces. Additionally, his work, supported by the Natural Science Foundation of Jiangsu Province, explores near-eye light field imaging with polarization volume holographic gratings. He also received funding from the Jiangsu Provincial Department of Education to study near-eye display systems based on human visual perception. His research contributes significantly to computational imaging advancements. 🎥📊

Research Focus Areas

Dr. Jian Zhao specializes in computational imaging, display technology, and deep learning applications. His research spans autostereoscopic displays 🖥️, light field imaging 📸, and human visual perception 👀. He applies AI and deep learning 🤖 to urban waterlogging detection 🌊, visual fatigue assessment 👓, and surface defect detection 📱. His expertise extends to virtual avatars 🧑‍💻 and photonic nanotechnology 🔬. Dr. Zhao contributes significantly to metasurface optics, spatial light modulation, and advanced display systems. His interdisciplinary work impacts computer vision, optoelectronics, and smart imaging technologies. 🚀✨

Publication Top Notes

  • 2025: “Urban Waterlogging Monitoring and Recognition in Low-Light Scenarios Using Surveillance Videos and Deep Learning”

    semanticscholar.org

  • 2024: “A Multimodal Visual Fatigue Assessment Model Based on Back Propagation Neural Network and XGBoost”

    semanticscholar.org

  • 2023: “Study on Random Generation of Virtual Avatars Based on Big Data”

    semanticscholar.org

  • 2023: “Viewing Zone Expansion of Autostereoscopic Display With Composite Lenticular Lens Array and Saddle Lens Array”

    semanticscholar.org

  • 2023: “Mobile Phone Screen Surface Scratch Detection Based on Optimized YOLOv5 Model (OYm)”

    semanticscholar.org

  • 2019: “Spatial Loss Factor for the Analysis of Accommodation Depth Cue on Near-Eye Light Field Displays”

    semanticscholar.org

  • 2019: “Tilted LCD Pixel With Liquid Crystal GRIN Lens for Two-Dimensional/Three-Dimensional Switchable Display”

    semanticscholar.org

  • 2019: “Hybrid Computational Near-Eye Light Field Display”

    semanticscholar.org

  • 2019: “Switchable Photonic Nanojet by Electro-Switching Nematic Liquid Crystals”

    semanticscholar.org

 

Eyob Mersha Woldamanuel | Digital Image Processing | Best Researcher Award

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Mr. Eyob Mersha Woldamanuel | Digital Image Processing | Best Researcher Award

Mr. Eyob Mersha Woldamanuel, Haramaya University, Ethiopia

Based on the information provided for Eyob Mersha Woldamanuel, here is an evaluation considering the criteria for the Best Researcher Award

Publication profile

Scopus

Orcid

Academic and Professional Background

Eyob’s academic background includes a B.Sc. in Electrical and Computer Engineering and an M.Sc. in Electronics and Communication Engineering. His professional journey started as an assistant lecturer and evolved to his current role as a lecturer and researcher, highlighting a steady progression in his career.

Research and Innovations

Eyob has completed several research projects, notably in the areas of medical image enhancement and adaptive code modulation for rainfall fade mitigation. His ongoing projects further emphasize his focus on real-time waste management systems and comparative studies in image enhancement, showcasing his active involvement in applied research.

Publications

Hybrid Simulated Annealing‐Evaporation Rate‐Based Water Cycle Algorithm Application for Medical Image Enhancement

Grayscale Image Enhancement Using Water Cycle Algorithm

Enhanced adaptive code modulation for rainfall fade mitigation in Ethiopia

Contributions

Eyob has pioneered the application of the Water Cycle Algorithm for image enhancement, demonstrating innovation in his field. His work on adaptive code modulation for rain fade mitigation is particularly noteworthy for its practical application in Ethiopia’s unique climate.

Consultancy/Industry Projects, Books, and Patents

There are no consultancy or industry projects, books, or patents associated with Eyob, which might be a consideration for higher-level awards but does not detract from his strong research contributions.

Professional Memberships and Collaborations

Eyob has collaborated on university-level grant projects but lacks formal professional memberships, which could be an area for future development to enhance his profile.

Conclusion

Suitability for the Best Researcher Award:
Eyob Mersha Woldamanuel presents a solid case for consideration for the Best Researcher Award, particularly due to his innovative research in image processing and contributions to local technological advancements. While his citation metrics and lack of consultancy or industry projects suggest that he is still building his research impact, his ongoing projects and future PhD studies at Eindhoven University of Technology indicate strong potential for further significant contributions.

In summary, Eyob is a promising researcher with demonstrated expertise in his field, making him a suitable candidate for the Best Researcher Award, particularly if the award considers the trajectory and potential of emerging researchers in addition to established metrics.