Mr. Pingjie Ou | artificial intelligence | Best Researcher Award

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Mr. Pingjie Ou | artificial intelligence | Best Researcher Award

Student, Guangxi University, China

Pingjie Ou is a passionate master’s student at Guangxi University, China, specializing in edge computing, cloud computing, and machine learning. With a strong academic foundation and growing research portfolio, he is actively contributing to next-generation computing paradigms. His early contributions in deep reinforcement learning applications for vehicular networks have already gained traction within the academic community. 🧠💡

Professional Profile

Scopus

🎓 Education Background

Pingjie Ou is currently pursuing his master’s degree at Guangxi University, one of the prominent institutions in China. His academic focus lies in electrical and computer engineering, with emphasis on distributed computing and artificial intelligence. 📘🏫

💼 Professional Experience

Although a student, Pingjie Ou has engaged in substantial research activities under funded projects including The National Natural Science Foundation of China (No. 62162003) and GuikeZY24212059 supported by the Guangxi Province. His active involvement in real-time research scenarios demonstrates promising professional potential. 🔬📊

🏅 Awards and Honors

As an emerging scholar, Pingjie Ou has not yet accumulated major awards but has gained recognition through impactful publications and research citations. His growing citation record and h-index reflect the potential for future accolades. 🏆📈

🔍 Research Focus

His core research interests include edge computing, cloud computing, vehicular networks, and machine learning. He is particularly focused on cooperative caching, resource management, and optimizing network efficiency using artificial intelligence approaches such as deep reinforcement learning. 🚗☁️📶

🧾 Conclusion

Pingjie Ou is a driven young researcher dedicated to advancing intelligent computing technologies. With strong academic grounding, collaborative research exposure, and early citation impact, he stands as a promising candidate for recognition in the domain of computer science and engineering. His scholarly journey is on a clear upward trajectory. 🚀📚

📚 Publication Top Note

  1. PDRL-CM: An efficient cooperative caching management method for vehicular networks based on deep reinforcement learning
    📅 Published Year: 2025
    📖 Journal: Ad Hoc Networks
    🔗 10.1016/j.adhoc.2025.103888

 

Dr. Keyong Hu | artificial intelligence | Best Researcher Award

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Dr. Keyong Hu | artificial intelligence | Best Researcher Award

Teacher, Hangzhou Normal University, China

Dr. KeYong Hu is an accomplished academic and researcher specializing in artificial intelligence and new energy technology. He earned his Ph.D. from the Zhejiang University of Technology in 2016 and is currently serving as an Associate Professor at Hangzhou Normal University, within the School of Information Science and Technology. Dr. Hu has contributed significantly to the intersection of AI and energy systems, with numerous publications in international journals, showcasing his expertise in predictive modeling and intelligent optimization.

Publication Profile

ORCID

🎓 Education Background

Dr. KeYong Hu completed his doctoral studies at the Zhejiang University of Technology, Hangzhou, China, where he received his Ph.D. in 2016. His academic training laid a strong foundation in computational intelligence and energy-related engineering applications.

💼 Professional Experience

Dr. Hu holds the position of Associate Professor at Hangzhou Normal University, Hangzhou, Zhejiang, China, affiliated with the School of Information Science and Technology. He has been actively involved in teaching, mentoring, and high-impact research since earning his doctorate.

🏆 Awards and Honors

While specific awards are not listed, Dr. Hu’s prolific publishing record in top-tier peer-reviewed journals like Mathematics, Heliyon, Sustainability, and Computers and Electrical Engineering underscores his recognition and influence in the fields of AI and energy optimization.

🔬 Research Focus

Dr. Hu’s research centers on the integration of artificial intelligence with new energy technologies, particularly photovoltaic power forecasting, energy system optimization, and cross-modal data analysis. His innovative use of algorithms such as Copula functions, Transformers, and Dung Beetle Optimization showcases his depth in AI-driven energy analytics.

✅ Conclusion

Dr. KeYong Hu stands out as a forward-thinking researcher contributing impactful work at the intersection of artificial intelligence and sustainable energy. Through his academic leadership and research contributions, he continues to shape the future of intelligent energy systems in China and beyond. 🌍📈

📚 Top Publications 

🔗 Two-Stage Distributionally Robust Optimal Scheduling for Integrated Energy Systems Considering Uncertainties in Renewable Generation and Loads
Journal: Mathematics | Year: 2025
Cited by: Check on Google Scholar

🔗 Short-term Photovoltaic Forecasting Model with Parallel Multi-Channel Optimization Based on Improved Dung Beetle Algorithm
Journal: Heliyon | Year: 2024
Cited by: Check on Google Scholar

🔗 Distributed Regional Photovoltaic Power Prediction Based on Stack Integration Algorithm
Journal: Mathematics | Year: 2024
Cited by: Check on Google Scholar

🔗 Automatic Depression Prediction via Cross-Modal Attention-Based Multi-Modal Fusion in Social Networks
Journal: Computers and Electrical Engineering | Year: 2024
Cited by: Check on Google Scholar

🔗 Short-Term Photovoltaic Power Generation Prediction Based on Copula Function and CNN-CosAttention-Transformer
Journal: Sustainability | Year: 2024
Cited by: Check on Google Scholar

Assoc. Prof. Dr. Feng Xie | intelligence systems | Best Researcher Award

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Assoc. Prof. Dr. Feng Xie | intelligence systems | Best Researcher Award

School of Information Science and Technology / Sanda University, China

Dr. Feng Xie is an accomplished Associate Professor at the School of Information Science and Technology, Sanda University, China . With a career that bridges academia and industry, he has been at the forefront of intelligent transportation systems, urban mobility, and smart city innovations. As a tech entrepreneur and researcher, he has led over 500 consultancy projects globally and holds numerous patents and software copyrights. His expertise spans traffic management, AI applications, IoT, and big data analytics, with significant contributions that have earned him prestigious awards and talent program recognitions.

Publication Profile

ORCID

🎓 Education Background:

Dr. Xie earned his Ph.D. from Nanyang Technological University, Singapore , in 2002 and completed his postdoctoral research at Tongji University, China , in 2005. His academic foundation is rooted in transportation engineering, computer science, and intelligent systems, providing the basis for his interdisciplinary approach to research and technology deployment.

💼 Professional Experience:

Currently serving as an Associate Professor at Shanghai Shanda University, Dr. Xie has also been the founder of Shanghai Van-Chance Trans. Technologies (2010–2022), where he led large-scale smart transportation projects across Asia. He worked extensively with government and industry partners, such as Singapore’s Land Transport Authority and IKEA, and directed projects like the world’s largest underground parking facility. He has also held leadership roles in cross-border technology associations and has developed systems used in cities like Beijing, Hangzhou, and Wuhan.

🏆 Awards and Honors:

Dr. Feng Xie has been recognized with several prestigious awards, including the IES Engineering Achievement Award in 2004 for his contributions to Singapore’s i-Transport project and the Shanghai Science Progress Award in 2013. He has also been selected for elite talent programs such as the Shanghai “3310” Overseas High-level Talent Program and Nanjing “321” Leading Technology Entrepreneurship Talent Program. His innovative work has resulted in 5 patents and 9 software copyrights, solidifying his impact in both academic and applied research domains.

🧠 Research Focus:

Dr. Xie’s research is centered on Intelligent Transportation Systems (ITS), AI-driven traffic management, smart parking, indoor positioning, urban planning, and emerging tech applications in IoT and quantitative finance. His efforts in traffic simulation, traveler behavior modeling, and data-driven urban development have influenced policies and technologies in smart mobility across multiple major cities. He has collaborated with Tongji University, published in Transportation Research Board journals, and contributed to key projects with global relevance.

✅ Conclusion:

With a unique blend of academic rigor and entrepreneurial innovation, Dr. Feng Xie exemplifies leadership in intelligent systems and sustainable urban technology 🌍. His work has profoundly shaped how modern cities approach mobility, data analytics, and smart infrastructure development. He continues to push the boundaries of AI, transportation science, and cross-border collaboration, earning him a rightful nomination for the Best Researcher Award.

📚 Top Publications :

PDCG-Enhanced CNN for Pattern Recognition in Time Series Data
Journal: Elsevier – Expert Systems with Applications
Year: 2022 | Cited by: 38 articles

Modeling Traveler Behavior Using Hybrid RP/SP Data and Path-Size Logit Models
Journal: Transportation Research Record: Journal of the Transportation Research Board
Year: 2012 | Cited by: 65 articles

AI-Based Traffic Incident Management Systems: A Case Study of Singapore’s i-Transport Project
Journal: IEEE Transactions on Intelligent Transportation Systems
Year: 2014 | Cited by: 79 articles

Urban Traffic Simulation Using GPS Data Fusion and Adaptive Signal Optimization
Journal: Journal of Transportation Engineering, ASCE
Year: 2016 | Cited by: 45 articles

Smart Parking Systems Powered by IoT and AI: A Case Study of Guinness Record Facility
Journal: Sensors (MDPI)
Year: 2020 | Cited by: 54 articles