Peishun Ye | Image Classification | Best Researcher Award

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Prof. Peishun Ye | Image Classification | Best Researcher Award

Prof. Peishun Ye, Yulin University, China.

Peishun Ye is a distinguished researcher and educator specializing in artificial intelligence and big data technology. His contributions to AI-driven image classification, particularly through the MobileTransNeXt model, have significantly enhanced remote sensing applications. With a strong academic background and extensive professional experience, he has led multiple research projects, published influential papers, and played a crucial role in advancing AI methodologies. His work continues to inspire and drive progress in the field.

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🎓 Early Academic Pursuits

Peishun Ye’s journey into the world of technology began with a strong academic foundation. He graduated from Shaanxi Normal University in 2005 with a degree in Computer Science and Technology. This formative education laid the groundwork for his expertise in computing, programming, and technological advancements. His passion for innovation and problem-solving led him to pursue further studies, culminating in a Master’s degree in Computer Technology Engineering from Northwestern Polytechnical University in 2016. These academic pursuits provided him with the knowledge and skills necessary to make groundbreaking contributions in the field of artificial intelligence and big data technology.

🏛️ Professional Endeavors

Upon completing his undergraduate degree, Peishun Ye embarked on a professional career at Yulin University. His dedication to research and teaching has made a significant impact on the institution. Over the years, he has been actively involved in scientific exploration and has contributed extensively to the field of computer science. With a focus on artificial intelligence and big data, he has been instrumental in developing new methodologies and refining existing technologies. His work has not only shaped the academic curriculum but also provided industry-driven solutions that address real-world challenges.

💡 Contributions and Research Focus

Peishun Ye’s research is centered on big data technology and artificial intelligence, with a particular emphasis on deep learning models. His latest work introduces MobileTransNeXt, an innovative hybrid deep learning architecture that integrates CNN, Transformer, and BiLSTM to enhance image classification performance in remote sensing applications. MobileTransNeXt has demonstrated exceptional results, achieving 96.90% test accuracy on the UC-MERCED dataset and 95.18% on NWPU-RESISC45. To further optimize these results, he developed the MobileTransNeXt-based DFE model, which extracts features from pretrained MobileTransNeXt and boosts classification accuracy to 98.81% and 95.29% on the respective datasets. His groundbreaking work has set new benchmarks in AI-driven image classification.

🎯 Accolades and Recognition

Throughout his career, Peishun Ye has been recognized for his outstanding contributions to the field of computer science. He has successfully led and completed one key research and development project for the Shaanxi Provincial Department of Science and Technology, as well as two industry-university research projects under the Yulin Science and Technology Bureau—one completed and one still ongoing. His research findings have been widely acknowledged in the academic community, with over ten published papers, including three indexed in EI. These accomplishments underscore his commitment to advancing knowledge and fostering technological innovation.

🌐 Impact and Influence

Peishun Ye’s research has significantly influenced the fields of artificial intelligence and big data analytics. His work on MobileTransNeXt and its advanced DFE-based version has contributed to improving the efficiency and accuracy of remote sensing image classification. By integrating cutting-edge deep learning techniques, his models have opened new avenues for AI applications in environmental monitoring, urban planning, and geospatial analysis. His contributions continue to inspire fellow researchers, students, and industry professionals, driving progress in AI-driven solutions.

 

Publication

  • Title: “A Secure Routing Protocol for Wireless Sensor Networks”​

  • Author: Ye, Peishun

  • Year: 2010​

🎨 Conclusion

Peishun Ye’s journey in academia and research is a testament to his dedication and vision in artificial intelligence and big data. His innovations have set new standards in AI-driven image classification, and his commitment to knowledge dissemination ensures a lasting impact. As he continues to explore new frontiers in AI, his work will undoubtedly contribute to the evolution of technology, leaving a legacy of excellence and inspiration for future generations.


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Sunday Aboyeji | Feature selection | Best Researcher Award

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Mr. Sunday Aboyeji | Feature selection | Best Researcher Award

Mr. Sunday Aboyeji, Shenzhen Institutes of Advanced Technology, China.

Sunday Timothy Aboyeji is an accomplished researcher in computational science and biomedical signal processing. With an impressive academic foundation in physics and communication science, he has pursued groundbreaking research in patient-independent seizure classification using EEG data. His work combines advanced algorithms, deep learning, and explainable AI to enhance the accuracy and interpretability of diagnostic tools for epilepsy and other neurological disorders. His dedication to interdisciplinary collaboration and his contributions to high-impact publications reflect his influence in the field.

 

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Scholar

📚 Early academic pursuits

Sunday Timothy Aboyeji began his academic journey with an unwavering passion for physical and computational sciences. Earning his Bachelor of Technology in Physics/Electronics from the Federal University of Technology, Minna, Nigeria, he graduated with first-class honors and a stellar GPA of 4.61/5.00. His undergraduate thesis, which explored the simulation of radiofrequency radiation effects on the brain, laid the foundation for his future endeavors in biomedical signal processing. He further honed his expertise by completing a Master’s degree in Communication Physics at the Federal University of Technology, Akure, Nigeria, achieving an outstanding GPA of 4.86/5.00. His master’s research on radioclimatic variables and refractivity modeling highlighted his ability to blend theoretical knowledge with practical applications.

🔬 Professional endeavors

Sunday is currently pursuing a Ph.D. in Pattern Recognition and Intelligent Systems at the University of Chinese Academy of Sciences, Shenzhen Institute of Advanced Technology, China. His doctoral dissertation focuses on developing patient-independent EEG-based seizure classification algorithms. Over the course of his research, he has designed cutting-edge solutions integrating signal processing, feature engineering, and deep learning. His projects include unsupervised seizure detection, feature fusion of Gramian angular fields, and domain adaptation frameworks, all aimed at revolutionizing epilepsy diagnosis. Beyond his academic achievements, he is an active member of IEEE and serves as a certified first-aider in Shenzhen, demonstrating his dedication to community service and professional growth.

🧠 Contributions and research focus

Sunday’s research has profoundly impacted computational science and biomedical signal processing. He specializes in the analysis of EEG, EMG, and other complex biomedical signals using advanced algorithms and explainable AI techniques. His groundbreaking work emphasizes the interpretability of deep learning models, enabling better diagnostic tools for epilepsy and other neurological disorders. By transforming biomedical signals into visual spectrograms and leveraging hybrid feature selection frameworks, he has created highly accurate and reliable classification models that support patient care and advance brain-computer interface technology.

🏆 Accolades and recognition

Sunday’s academic excellence has been recognized through multiple awards, including the prestigious Chinese Government Scholarship for his Ph.D. studies. His undergraduate achievements earned him commendations from his university dean. These accolades reflect his dedication to academic rigor and his ability to excel in highly competitive environments. He has also been invited to serve as a peer reviewer for leading journals, further solidifying his reputation as a rising star in his field.

🌍 Impact and influence

Through collaborative efforts with international scholars and researchers, Sunday has contributed to several high-impact publications in journals such as Computers in Biology and Medicine and the IEEE Journal of Biomedical and Health Informatics. His work on robust seizure detection and interpretable machine learning models has set a benchmark for researchers in biomedical signal processing. These contributions not only enhance patient diagnostics but also pave the way for more accessible healthcare technologies.

🌟 Legacy and future contributions

Sunday aspires to leave a legacy as a trailblazer in biomedical signal processing and computational sciences. His ongoing research on domain adaptation frameworks promises to address patient-specific challenges, making diagnostic systems more generalized and inclusive. He envisions leveraging his expertise to develop innovative solutions that enhance the quality of life for individuals with neurological disorders, ensuring his work continues to inspire and benefit the global scientific community.

💡 Dedication to innovation

Sunday’s career exemplifies a commitment to innovation, interdisciplinary collaboration, and societal impact. With his technical skills in Python, TensorFlow, and Pytorch, coupled with a deep understanding of signal processing and pattern recognition, he remains at the forefront of research in his field. His dedication to integrating advanced technology with real-world applications underscores his role as a visionary researcher and advocate for progress in medical diagnostics.

📚 Publications

  • Title: Robust Epileptic Seizure Detection Based on Biomedical Signals Using an Advanced Multi-View Deep Feature Learning Approach
    Authors: Ijaz Ahmad, Zhenzhen Liu, Lin Li, Inam Ullah, Sunday Timothy Aboyeji, Xin Wang, Oluwarotimi Williams Samuel, Guanglin Li, Yuan Tao, Yan Chen, et al.
    Year: 2024

 

  • Title: Automatic Detection of Epileptic Seizure Based on One Dimensional Cascaded Convolutional Autoencoder with Adaptive Window-Thresholding
    Authors: Sunday Timothy Aboyeji, Xin Wang, Yan Chen, Ijaz Ahmad, Lin Li, Zhenzhen Liu, Chen Yao, Guoru Zhao, Yu Zhang, Guanglin Li, et al.
    Year: 2024

 

  • Title: Feature Fusion of Gramian Angular Field Deep Learning EEG-Based Epileptic Seizure Classification
    Authors: Sunday Timothy Aboyeji, Xin Wang, Yan Chen, Ijaz Ahmad, Lin Li, Zhenzhen Liu, Chen Yao, Yu Zhang, Guoru Zhao, Guanglin Li, et al.
    Year: 2024

 

  • Title: Modeling of Atmospheric Primary Radioclimatic Variables in Nigeria for Microwave Radio Propagation Applications
    Authors: Falodun, S.E., Ojo, J.S., Aboyeji, S.T.
    Year: 2021

 

Conclusion

Sunday’s journey exemplifies a relentless pursuit of knowledge and innovation. From his academic excellence in Nigeria to his impactful research at the Shenzhen Institute of Advanced Technology, he has made meaningful strides in advancing patient care through computational science. With a clear vision for the future, his contributions promise to continue shaping the landscape of biomedical signal processing and inspire further advancements in medical diagnostics.

 

Chen Wang | neural network application | Best Researcher Award

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Prof Dr.Chen Wang | neural network application | Best Researcher Award

Prof Dr Chen Wang School of Mining, Guizhou University China

Wang Chen is a distinguished professor at Guizhou University, specializing in mining engineering and resources and environment. He holds a PhD from the China University of Mining and Technology and has significant expertise in mining methods, rock mechanics, mining system engineering, and the kinematic behavior of rock layers in karst regions.

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📚 Recruitment Discipline Direction

Mining Engineering, Resources and Environment

🔬 Main Research Fields and Directions

Mining Methods,Rock Mechanics,Mining System Engineering,Roadway Support,Kinematic Mechanisms of Rock Layers in Karst Mountainous Areas.

💼 Key Research Projects (2018 – Present)

National Natural Science Foundation General Project (52174072)“Study on the Mechanisms of Rock Layer Movement under Repeated Mining in Karst Mountainous Areas,” 2022.01-2025.12, 580,000 RMB, Principal Investigator, ongoing. 💰National Natural Science Foundation Youth Science Fund Project (51904081)“Study on the Mechanisms of Instability Induced by Mining in Shallowly Buried Coal Layers in Karst Terrain,” 2020.01-2022.12, 240,000 RMB, Principal Investigator, ongoing. 🔍

✍️ Journal Articles:

Wang Chen et al. “An Expert System for Equipment Selection of Thin Coal Seam Mining.” (2019) .Wang Chen et al. “Optimal Selection of a Longwall Mining Method for a Thin Coal Seam Working Face.” (2016) .Wang Chen, Zhou Jie. “New Advances in Automatic Shearer Cutting Technology.” (2021) ⚙️

🥇 Achievements

Patents: 5 granted invention patents related to coal mining technology. Awards: Multiple research awards for contributions to mining technology. 🏆

📚 Publications

  1. Title: Study on strength prediction and strength change of Phosphogypsum-based composite cementitious backfill based on BP neural network
    Authors: Wu, M., Wang, C., Zuo, Y., Zhang, J., Luo, Y.
    Year: 2024
    Journal: Materials Today Communications
    Volume: 41
    Article Number: 110331

 

  1. Title: Correction: Determination of working resistance of support parameter variation of large mining height support: the case of Caojiatan coal mine
    Authors: Xue, B., Zhang, W., Wang, C.
    Year: 2024
    Journal: Geomechanics and Geophysics for Geo-Energy and Geo-Resources
    Volume: 10
    Issue: 1
    Pages: 14

 

  1. Title: Determination of working resistance of support parameter variation of large mining height support: the case of Caojiatan coal mine
    Authors: Xue, B., Zhang, W., Wang, C.
    Year: 2024
    Journal: Geomechanics and Geophysics for Geo-Energy and Geo-Resources
    Volume: 10
    Issue: 1
    Pages: 1

 

  1. Title: Evolution of Broken Coal’s Permeability Characteristics under Cyclic Loading–Unloading Conditions
    Authors: Luo, L., Zhang, L., Pan, J., Wang, C., Li, S.
    Year: 2024
    Journal: Natural Resources Research
    Volume: 33
    Issue: 5
    Pages: 2279–2297

 

  1. Title: Preparation and characterization of green lignin modified mineral cementitious firefighting materials based on uncalcined coal gangue and coal fly ash
    Authors: Dou, G., Wang, C., Zhong, X., Qin, B.
    Year: 2024
    Journal: Construction and Building Materials
    Volume: 435
    Article Number: 136799

 

  1. Title: Mining Technology Evaluation for Steep Coal Seams Based on a GA-BP Neural Network
    Authors: Li, X., Wang, C., Li, C., Luo, Y., Jiang, S.
    Year: 2024
    Journal: ACS Omega
    Volume: 9
    Issue: 23
    Pages: 25309–25321

 

  1. Title: Capturing rate- and temperature-dependent behavior of concrete using a thermodynamically consistent viscoplastic-damage model
    Authors: Tao, J., Yang, X.-G., Lei, Y., Wang, C.
    Year: 2024
    Journal: Construction and Building Materials
    Volume: 422
    Article Number: 135791

Conclusion

Wang Chen’s extensive research and numerous publications significantly contribute to the field of mining engineering. His focus on the complexities of karst geology and the development of intelligent mining technologies positions him as a leader in advancing mining safety and efficiency. His ongoing projects reflect a commitment to addressing contemporary challenges in the mining sector, particularly in relation to environmental sustainability and resource management.