Xin Liu | Deep Learning | Best Researcher Award

Posted on by Network Science

Dr. Xin Liu | Deep Learning | Best Researcher Award

Associate Professor at Wenzhou Business College, China📖

Dr. Xin Liu is an Associate Professor and Physical Education Teacher at Wenzhou Business College. With a strong academic background in physical training and deep learning, his research focuses on integrating technology with sports science to optimize athletic performance and injury prevention. His work leverages infrared thermal imaging and deep learning models to analyze heat energy expenditure in athletes. He has authored two books and actively contributes to advancing sports training methodologies through innovative research.

Profile

Orcid Profile

Education Background🎓

  • Ph.D. in Physical Education, Jose Rizal University, 2020–2023
  • Master’s in Physical Education, Shanghai Normal University, 2017–2019
  • Bachelor’s in Physical Education, Shandong Agricultural University, 2013–2017

Professional Experience🌱

  • Physical Education Teacher, Wenzhou Business College (2024–Present)
    Engaged in teaching and research on physical training methodologies, integrating AI-driven analytics in sports science.
  • Researcher in Sports Science & Deep Learning Applications
    Focused on using AI models, particularly CNN, to predict and enhance athletic performance.
Research Interests🔬
  • Physical Training & Sports Performance Optimization
  • Application of Deep Learning in Sports Science
  • Infrared Thermal Imaging for Athlete Monitoring

Author Metrics

Dr. Xin Liu has made significant contributions to the field of physical training and sports science through his research on integrating deep learning models with infrared thermal imaging technology. He has authored two books (ISBN: 978-7-5498-5469-1, 978-7-7800-2061-9) that focus on advancements in sports performance and training methodologies. His research includes two completed/ongoing projects, with findings published in reputed platforms such as Elsevier (Link). While his citation index is yet to be established, his pioneering work in applying AI-driven techniques to athlete monitoring is gaining recognition in the academic community.

Publications Top Notes 📄
Simulation of Infrared Thermal Images Based on Deep Learning in Athlete Training: Simulation of Thermal Energy Consumption
  • Authors: Xin Liu, Li Zhang, Wei Chen
  • Journal: Heliyon
  • Volume: 11
  • Issue: 1
  • Publication Date: January 2025
  • Article Number: e00823
  • DOI: Link to Article
  • Publisher: Elsevier
  • Abstract Summary: This study explores the application of deep learning techniques to simulate infrared thermal images for analyzing and predicting athletes’ thermal energy consumption. The research highlights how AI-driven thermal imaging enhances training efficiency, minimizes injury risks, and provides insights into optimizing sports performance.

Conclusion

Dr. Xin Liu is a strong candidate for the Best Researcher Award due to his innovative contributions in integrating deep learning and infrared thermal imaging in sports science. His research holds substantial potential for real-world applications, optimizing athlete performance, and advancing AI-driven monitoring techniques. With continued efforts in increasing citations, industry collaborations, and publishing in high-impact journals, he can further solidify his position as a leading researcher in the field.

Chenru Jiang | Deep Learning | Best Researcher Award

Posted on by Network Science

Dr. Chenru Jiang | Deep Learning | Best Researcher Award 

post doctor, at Duke Kunshan University, China.

Chenru Jiang is a dedicated researcher in artificial intelligence, specializing in deep learning, pattern recognition, and computer vision. He is a Postdoctoral Research Fellow at Duke Kunshan University, contributing to cutting-edge projects in 3D point cloud analysis, human pose estimation, and healthcare applications of AI. With professional experience spanning academia and industry, Chenru has developed advanced algorithms for face detection, tracking, and 3D modeling. A passionate academic mentor, he actively supports students and colleagues in research and teaching activities. Chenru’s work has been featured in prestigious journals and conferences worldwide.

Profile

Scopus

ORCID

Google Scholar

Education

🎓 University of Liverpool, UK

  • Ph.D. in Computer Science & Engineering (2023): Dissertation on “Investigation of Human Pose Estimation from 2D to 3D,” supervised by Prof. Kaizhu Huang.
  • M.E. in Multi-media Telecommunication Technology (2017): Thesis on “Siamese Network Based Online Tracking,” co-supervised by Prof. Tammam Tillo and Prof. Kaizhu Huang.
  • B.E. in Digital Media Technology (2015): Focused on “Depth Data Acquisition by One Monocular Camera,” under the guidance of Prof. Tammam Tillo.

Professional Experience

👨‍💻 Postdoctoral Research Fellow – Duke Kunshan University, China (2024–Present)

  • Developed machine learning and deep learning algorithms for healthcare and 3D data processing.
  • Mentored students in advanced computational methodologies.

🧑‍💻 Algorithm Engineer – Suzhou Institute of Nano-Tech and Nano-Bionics, CAS (2017–2019)

  • Designed and implemented face detection and tracking systems.

🚗 Algorithm Engineer – China North Industries Group Co., Ltd (2017)

  • Contributed to driving assistance systems for special vehicles.

Research Interests

🧠 Chenru Jiang’s research focuses on AI for healthcare, including deep learning models for human pose estimation and 3D point cloud analysis. His interests extend to developing innovative algorithms for pattern recognition and machine learning systems, addressing real-world challenges in areas like robotic perception, 3D reconstruction, and zero-shot learning. He is particularly passionate about improving human-computer interaction with advanced vision-based solutions.

Awards

🏆 Chenru Jiang has received numerous accolades for his academic contributions, including recognition for his top-tier publications in CAS-JCR Q1 journals and his presentations at CCF-A conferences like ACM Multimedia and CVPR. His innovative work in algorithm design and pose estimation systems has been praised for its impact in both industry and academia.

Top Noted Publications

📚 Selected Journal Publications

Revisiting 3D Point Cloud Analysis with Markov Process

  • Authors: Jiang C., Ma W., Huang K., Wang Q., Yang X., Zhao W., Wu J., Wang X., Xiao J., & Niu Z.
  • Journal: Pattern Recognition, Volume: 158, Article: 110997, Year: 2025.
  • Cited by: 15.
    Read Article

2. PointGS: Bridging and Fusing Geometric and Semantic Space for 3D Point Cloud Analysis

  • Authors: Jiang C., Huang K., Wu J., Wang X., Xiao J., & Hussain A.
  • Journal: Information Fusion, Volume: 91, Pages: 316-326, Year: 2022.
  • Cited by: 30.
    Read Article

3. Aggregated Pyramid Gating Network for Human Pose Estimation Without Pre-Training

  • Authors: Jiang C., Huang K., Zhang S., Wang X., Xiao J., & Goulermas Y.
  • Journal: Pattern Recognition, Volume: 138, Article: 109429, Year: 2022.
  • Cited by: 20.
    Read Article

Conclusion

Chenru Jiang is a highly qualified candidate for the Best Researcher Award, with a strong track record in impactful AI research, significant publications, and practical algorithm development. Their expertise in deep learning and 3D computer vision positions them at the forefront of innovation in these fields. Addressing the areas of improvement, particularly in independent leadership and community engagement, would further strengthen their case for recognition. Overall, Chenru demonstrates exceptional potential and merit for this award.

 

Asif Hamid- Deep learning – Best Researcher Award

Posted on by Network Science

Asif Hamid- Deep learning – Best Researcher Award

Mr. Asif Hamid  distinguished academic and researcher in the field  Deep learning. He has accumulated over four years of experience in writing and publishing research articles for journals and conferences. This experience has provided him with a deep understanding of various writing styles, from scholarly articles to book chapters and industry-focused documentation. His role as a reviewer for many prestigious conferences has also sharpened his critical thinking and editorial abilities.

His expertise is not limited to writing; he is skilled in Python and MATLAB programming, which are crucial for his research projects. He possesses basic skills in HTML and is proficient with MS Office tools—Word, Excel, and PowerPoint—as well as LaTeX software, all vital for creating research papers and presentations. Additionally, his ability to utilize internet applications and implement deep learning techniques demonstrates his aptitude for integrating cutting-edge technology into his research activities.

🌐 Professional Profiles

Educations📚📚📚

He is currently pursuing a Ph.D. at the Islamic University of Science and Technology (IUST) in Awantipora, Jammu & Kashmir, India, a program he began in 2020. Prior to this, he earned his Master of Technology degree in Control and Instrumentation Systems from Jamia Milia Islamia (JMI) in India, where he distinguished himself by securing a CGPA of 9.3 out of 10, placing him in the top 1% of his class. His foundational education was completed at Baba Ghulam Shah Badshah University in Rajouri, Jammu & Kashmir, where he received his Bachelor of Technology degree in Electronics and Communication Engineering, achieving a percentile score of 75.6, which also placed him in the top 1% of his peers.

Conference Papers

• Asif Hamid Bhat, Rafiq, D., Nahvi, S. A., & Bazaz, M. A. (2022, May). Discovering low-rank
representations of large-scale power-grid models using Koopman theory. In 2022 Trends in
Electrical, Electronics, Computer Engineering Conference (TEECCON). IEEE.. [Link]
• Asif Hamid Bhat, Rafiq, D., Nahvi, S. A., & Bazaz, M. A. (2022, July). Power Grid parameter
estimation using Sparse Identification of Nonlinear Dynamics. In 2022 International
Conference on Intelligent Controller and Computing for Smart Power (ICICCSP) (pp. 1-6).
IEEE. [Link]
• Asif Hamid Bhat, Rafiq, D., Nahvi, S. A., & Bazaz, Neural network-based time stepping

Awards and Achievements

He has received numerous accolades and support for his academic pursuits. Since 2020, he has been a recipient of the MHRD (Ministry of Human Resource Development, Government of India) fellowship for his Ph.D. studies in the Department of Electrical Engineering at the Islamic University of Science and Technology in Awantipora, Jammu & Kashmir, India, supported by grant number IUST0119013135. In 2019, he successfully qualified the GATE (Graduate Aptitude Test in Engineering) for Electronics and Communication Engineering, scoring 31.67 out of 100. Furthermore, in 2017, he qualified for the M.Tech. program at Jamia Milia Islamia, Delhi, by passing the entrance examination, demonstrating his consistent excellence and competence in his field.

WORKSHOP / SEMINAR / TRAINING / STC attended

1. Presented Discovering low-rank representations of large scale power-grid models using Koopman
theory paper in Electrical, Electronics, Computer Engineering Conference IEEE held on 26-27
may 2022 at Reva University.
2. Presented Power Grid parameter estimation using Sparse Identification of Nonlinear Dynamics
paper in the INTERNATIONAL CONFERENCE ON INTELLIGENT CONTROLLER AND
COMPUTING FOR SMART POWER, IEEE 2022 organized by the Department of Electrical
and Electronics Engineering, Sreenidhi Institute of Science And Technology, Hyderabad,
India during 21–23 July 2022.
3. Reviewer for IEEE international conference on applied intelligence and sustainable
computing 2023.
4. Attend in faculty development program entitled “Research Methodology + Publication Ethics”
organised by Department of computer science and engineering IUST, Awantipora form 7-11
Feb 2022.

📝🔬Publications📝🔬

  • Hierarchical deep learning-based adaptive time stepping scheme for multiscale simulations

    Engineering Applications of Artificial Intelligence
    2024-07 | Journal article
    DOI: 10.1016/j.engappai.2024.108430
    CONTRIBUTORS: Asif Hamid; Danish Rafiq; Shahkar Ahmad Nahvi; Mohammad Abid Bazaz

  • Neural network-based time stepping scheme for multiscale partial differential equations

    2023 7th International Conference on Computer Applications in Electrical Engineering-Recent Advances (CERA)
    2023-10-27 | Conference paper
    DOI: 10.1109/cera59325.2023.10455439
    CONTRIBUTORS: Asif Hamid; Danish Rafiq; Shahkar Ahmad Nahvi; Mohammad Abid Bazaz

  • Deep learning assisted surrogate modeling of large-scale power grids

    Sustainable Energy, Grids and Networks
    2023-06 | Journal article
    DOI: 10.1016/j.segan.2023.101031
    Part ofISSN: 2352-4677
    CONTRIBUTORS: Asif Hamid; Danish Rafiq; Shahkar Ahmad Nahvi; Mohammad Abid Bazaz

  • Power Grid parameter estimation using Sparse Identification of Nonlinear Dynamics

    2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP)
    2022-07-21 | Conference paper
    DOI: 10.1109/iciccsp53532.2022.9862464
    CONTRIBUTORS: ASIF HAMID BHAT