Rui Miao | Artificial Intelligence | Best Researcher Award

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Assoc. Prof. Dr. Rui Miao |  Artificial Intelligence | Best Researcher Award

Associate Researcher at Zhejiang Lab, China

Dr. Rui Miao is an Associate Researcher at Zhejiang Lab, specializing in artificial intelligence and image processing. He earned his Ph.D. in Engineering from Beihang University in 2022 and began postdoctoral research the same year, focusing on multi-modal cross-domain image enhancement for intelligent navigation systems across air, land, and water. Dr. Miao has led or participated in 7 research projects, published in top-tier journals such as IEEE Transactions on Geoscience and Remote Sensing and Pattern Recognition, and holds 28 patents (published or pending). His work contributes significantly to intelligent visual systems and applied AI.

Profile:

👨‍🎓 Academic Background

Dr. Rui Miao earned his Ph.D. in Engineering from Beihang University in 2022. He is currently an Associate Researcher at Zhejiang Lab, China.

🧠 Research Focus

His work explores cutting-edge areas such as:

  • Multimodal Image Processing

  • AI-based Image Generation & Matching

  • Visual Enhancement for Intelligent Systems

  • Model Inference Acceleration

🧪 Research Contributions

Dr. Miao has contributed to 7 major research projects and published impactful papers in top-tier journals like:

  • IEEE Transactions on Geoscience and Remote Sensing (TGRS)

  • Pattern Recognition (PR)

🔬 Innovations & Patents:

He has filed or published 28 patents, focusing on advanced image enhancement algorithms tailored for cross-domain AI perception systems used in air, land, and water navigation.

📚 Publications & Recognition:

While still early in his academic journey, Rui’s innovative work has already gained visibility in the scientific community, although citation metrics and editorial roles are still forthcoming.

Publication:

“Attention-Guided Progressive Frequency-Decoupled Network for Pan-Sharpening”
IEEE Transactions on Geoscience and Remote Sensing, 2024.
DOI: 10.1109/TGRS.2024.3376730
Authors: Rui Miao, Hang Shi, Fengguang Peng, Siyu Zhang

 

 

Pakezhamu Nuradili | Computer Science and Artificial Intelligence | Best Researcher Award

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Dr. Pakezhamu Nuradili| Computer Science and Artificial Intelligence | Best Researcher Award

PhD candidate University of Electronic Science and Technology of China

Pakezhamu Nuradili, a native of China, is a Ph.D. student specializing in Information and Communication Engineering. She is currently enrolled in a joint Ph.D. program between the University of Electronic Science and Technology of China (UESTC) and the University of Trento, Italy. Her expertise spans deep learning-based image processing, semantic segmentation, and thermal infrared imaging. Known for her attention to detail and excellent communication skills in multiple languages, she excels in both technical and interpersonal domains.

Profile

Orcid

Education 🎓

  • High School: Jiangpu Senior High School, Jiangsu Province, China (2010–2013)
  • Bachelor’s Degree: Electronics and Information Engineering, Hebei University of Science and Technology (2013–2017)
  • Master’s Degree: Radio Physics, Yili Normal University, China, focusing on face recognition algorithms (2017–2020)
  • Ph.D.: Information and Communication Engineering, UESTC, with a joint program at the University of Trento, Italy (2021–Present)

Work Experience 💼

  • Teaching:
    • Substitute Teacher, Basic Computer Applications, Silk Road College of Ili (2017–2018)
    • Graduate Assistant, Basic Computer Applications, Yili Normal University (2018–2019)
    • Substitute Teacher, Advanced and Intermediate Mathematics, Ili Vocational and Technical College (2020–2021)
    • Graduate Teaching Assistant, Principles of Remote Sensing, UESTC (2022)
  • Volunteering: Marathon Distance Race Volunteer, Trento, Italy (2024)

Research Interests 🔬

Pakezhamu’s research focuses on:

  • Deep learning-based image processing and semantic segmentation.
  • Thermal infrared and multispectral imaging for UAV applications.
  • Wetland segmentation using advanced models like SegFormer.

Awards 🏆

  • Hebei Provincial Inspiration Scholarship (2016)
  • Outstanding Graduation Design Award, Hebei University of Science and Technology (2017)
  • Graduate Student Scholarship, Yili Normal University (2018)
  • Xinjiang Autonomous Region Postgraduate Scholarship (2019)
  • UESTC Academic Scholarships (2022, 2023, 2024)
  • Outstanding Teaching Assistant Award, UESTC (2022)

Publications Top Notes: 📚

P. Nuradili et al., “UAV Remote-Sensing Image Semantic Segmentation Strategy Based on Thermal Infrared and Multispectral Image Features,” IEEE Journal on Miniaturization for Air and Space Systems, 4(3): 311-319, Sept. 2023. Cited by: 5

Nuradili, P. et al., “Semantic segmentation for UAV low-light scenes based on deep learning and thermal infrared image features,” International Journal of Remote Sensing, 45(12): 4160–4177, 2024. Cited by: 8

Nuradili, P. et al., “Wetland Segmentation Method for UAV Multispectral Remote Sensing Images Based on SegFormer,” IGARSS 2024 IEEE Symposium, 2024. Cited by: 3

Nuradili, P. et al., “Deep Learning Method for Wetland Segmentation in Unmanned Aerial Vehicle Multispectral Imagery,” Remote Sensing, 16(24): 4777, 2024. Cited by: 6

Nuradili, P. et al., “Fire Detection Based on Deep Learning Segmentation Methods,” Journal TBD, 2024 (Under Process).

Wang, Z. et al., “Removing temperature drift and temporal variation in thermal infrared images of a UAV uncooled thermal infrared imager,” ISPRS Journal of Photogrammetry and Remote Sensing, 203: 392-411, 2023. Cited by: 12