Zhang Bofeng | Data Mining | Best Researcher Award

Zhang Bofeng | Data Mining | Best Researcher Award

Prof. Dr. Zhang Bofeng, Shanghai Polytechnic University, China .

Professor Zhang Bofeng is a renowned expert in intelligent systems, data mining, and cognitive computing 🌐. With a focus on innovative solutions for challenges such as earthquake prediction, human-machine interaction, and web services optimization, his work bridges theoretical research and real-world applicationsΒ πŸ”. Zhang has led numerous high-impact projects, including those funded by the National Natural Science Foundation of China and the Shanghai Municipal Science and Technology CommissionΒ πŸ†. His contributions to fields like AI, BCI, and cloud computing have advanced scientific knowledge and improved technological capabilities, making him a leader in his field 🧠✨.

Publication Profile

Scopus

Education and Experience

  • πŸŽ“Β Ph.D.: Shanghai Jiao Tong University – Specializing in intelligent systems
  • πŸŽ“Β Postdoctoral Fellowship: Intelligent CAD Systems, funded by China Postdoctoral Science Foundation
  • πŸ‘¨β€πŸ«Β Professor: Shanghai University – Leading innovative projects in AI and cognitive computing
  • πŸ†Β Research Leadership: Directed high-impact national and international projects in data mining, BCI, and web services

Suitability For The Award

Prof.Dr. Zhang Bofeng, a renowned professor with a Ph.D. and a prolific research career, exemplifies excellence in advancing science and technology. His extensive contributions span intelligent systems, data mining, human-machine interaction, and cloud computing, showcasing his multidisciplinary expertise. With over 18 major research projects supported by prestigious grants, Zhang has delivered groundbreaking innovations in decision-support systems, service optimization, and adaptive technologies. His work not only addresses complex theoretical challenges but also offers practical solutions with significant societal impact. These achievements make Zhang Bofeng a highly suitable candidate for the Best Researcher Award, recognizing his unparalleled dedication to research and innovation.

Professional Development

Professor Zhang Bofeng’s career reflects a relentless pursuit of innovation and knowledge-sharingΒ πŸ“ˆ. His projects span intelligent CAD systems, earthquake prediction models, and cutting-edge web services optimization 🌍. Zhang’s expertise in combining AI theories with real-world applications has fueled advancements in cloud computing, BCI systems, and mobile e-commerce recommendationsΒ πŸ’»πŸ“±. Through collaboration with prestigious organizations like the National Natural Science Foundation of China and the Shanghai Municipal Science and Technology Commission, he consistently pushes technological boundariesΒ πŸ”¬. His contributions have significantly shaped fields like cognitive computing and intelligent perception systems 🧠✨.

Research Focus

Professor Zhang Bofeng’s research centers on intelligent systems and their applications 🌟. He specializes in data mining and knowledge discovery, cognitive computing for human-machine interaction, and advanced web services compositionΒ πŸ“Š. His work also addresses practical challenges in education platforms, mobile e-commerce, and earthquake prediction through innovative computational modelsΒ πŸ—ΊοΈ. By integrating AI, BCI, and cloud computing methodologies, Zhang focuses on creating adaptive, user-centered technologies that improve quality of life and advance scientific understandingΒ πŸŒπŸ”.

Awards and Honors

  • πŸ…Β China Postdoctoral Science Foundation AwardΒ (1999)
  • πŸ†Β Shanghai Municipal Education Commission Youth Science AwardΒ (2003)
  • 🌟 National Natural Science Foundation Major Research GrantΒ (2006)
  • πŸŽ–οΈΒ Shanghai Pujiang Program RecognitionΒ (2009)
  • πŸ†Β Innovation Program of Shanghai Municipal Education Commission AwardΒ (2012)
  • πŸ…Β Specialized Research Fund for the Doctoral Program of Higher EducationΒ (2024 )

Publication Top Notes

  • Selecting reliable instances based on evidence theory for transfer learningΒ – 5 citations,Β 2024Β πŸ“˜βœ¨
  • Dynamic bipartite network model based on structure and preference featuresΒ –Β Β 2024Β πŸ“ŠπŸ”
  • FRLN: Federated Residual Ladder Network for Data-Protected QoS PredictionΒ –Β Β 2024Β πŸ”’πŸ“ˆ
  • Deep latent representation enhancement method for social recommendationΒ – 2 citations,Β 2024 🧠🀝
  • Predictive Modeling and Feature Analysis for Clinical Prognosis in Hemorrhagic Stroke Patients Using Machine LearningΒ – 0 citations,Β 2024Β πŸ₯πŸ–₯️
  • TEDC: Temporal-aware Edge Data Caching with Specified Latency PreferenceΒ –Β 2024Β β³πŸ“‚
  • User Profiling for Personalized Service Recommendation with Dual High-order Feature LearningΒ –Β 2024Β πŸ“‘πŸŒŸ
  • Named entity recognition method of blockchain patent text based on deep learningΒ – 1 citation,Β 2024Β πŸ”—πŸ§ 

Assist Prof Dr. NAIF AL MUDAWI | Data Mining | Best Researcher Award

Assist Prof Dr. NAIF AL MUDAWI | Data Mining | Best Researcher AwardΒ 

Assist Prof Dr. NAIF AL MUDAWI, Najran University, Saudi Arabia

Dr. Naif Almudawi is an esteemed Assistant Professor in the Department of Computer Science and Information Systems at Najran University, Saudi Arabia. πŸŽ“ With a PhD from the University of Sussex, UK, specializing in cloud computing adoption for public organizations, Dr. Almudawi has demonstrated exceptional expertise in his field. His academic journey began with a Master’s degree in Computer Science from La Trobe University, Australia, where he was actively involved in the Australian Computer Science committee. 🌏 Dr. Almudawi’s career includes roles as a lecturer and assistant professor at Najran University, where he contributes to the advancement of computer science education and research. πŸ›οΈ He has published numerous peer-reviewed papers in prestigious journals, reflecting his commitment to advancing knowledge in computer science.

Professional Profile:

ORCID

 

Education:

  • Bachelor of Computer Science, King Khalid University, Saudi Arabia πŸŽ“ (March 2007) – GPA: 4.48/5
  • Master of Computer Science, La Trobe University, Australia πŸŽ“ (July 2011) – GPA: 3.5/4
  • Ph.D. in Computer Science, University of Sussex, UK πŸŽ“ (April 2021)

Professional Experience:

  • Teacher at Wadi Aldwasser Scientific Institute (July 2008 – March 2009) 🏫
  • Lecturer at Najran University (September 2011 – Present) πŸ‘¨β€πŸ«
  • Assistant Professor at Najran University (September 2021 – Present) πŸ‘¨β€πŸ«

Personal Skills:

  • Networking & Communication 🀝
  • Leadership 🌟
  • Programming Languages: HTML, PHP, Java, C++, JavaScript πŸ’»
  • Project Management πŸ“ˆ
  • Languages: Arabic, English πŸ—£οΈ

Honours and Awards:

  • Full scholarship from the Ministry of Higher Education, Saudi Arabia πŸŽ“ (2009)
  • Certificate of Appreciation from the Saudi Cultural Mission in Australia πŸ‡ΈπŸ‡¦ (2011)
  • Full scholarship from Najran University πŸŽ“ (2018)

Committee and Membership:

  • Coordinator, Department of Computer Science, Najran University πŸ›οΈ (since 2021)
  • Units Coordinator, Computer Department, Najran University πŸ›οΈ
  • Supervise final year projects, Najran University πŸŽ“
  • Design course syllabuses, Najran University πŸ“
  • Member of Quality Assurance, Examination Moderation, and Student Advisor Committees πŸ› οΈ (since 2012)
  • Member, IEEE Computer Society πŸ€– (since 2018)
  • Member, Digital Transformation Committee, Najran University πŸ–₯️ (since 2021)
  • Vice Dean, Department of Computer Science, Najran University πŸ›οΈ (since 2022)

Research Interests:

  • Cloud Computing ☁️
  • Internet of Things (IoT) 🌐
  • Network Communication πŸ“Ά
  • Web Application Design & Development 🌐
  • Digital Transformation 🏒

Publication top Notes:

 

Enhanced Data Mining and Visualization of Sensory-Graph-Modeled Datasets through Summarization

Predictive Analytics for Sustainable E-Learning: Tracking Student Behaviors

Vehicle Detection and Classification via YOLOv8 and Deep Belief Network over Aerial Image Sequences

Intelligent ADL Recognition via IoT-Based Multimodal Deep Learning Framework

Intelligent Localization and Deep Human Activity Recognition through IoT Devices

Smart Home Automation-Based Hand Gesture Recognition Using Feature Fusion and Recurrent Neural Network