Zhiguo Shi | Big Data Analytics | Outstanding Scientist Award

Published on by Business Global Awards

Outstanding Scientist Award

Zhiguo Shi
Big Data Research Center, University of Science and Technology Beijing, China
Zhiguo Shi
Affiliation Big Data Research Center, University of Science and Technology Beijing
Country China
Scopus ID 57199774338
Documents 79
Citations 386
h-index 9
Subject Area Big Data Analytics
Event Business Global Awards

Zhiguo Shi, a professor and doctoral supervisor associated with the Big Data Research Center at the University of Science and Technology Beijing. His academic and professional activities are primarily concentrated in the fields of big data analytics, intelligent systems, digital governance, urban data infrastructure, and artificial intelligence applications. Over the course of his academic career, Shi has contributed to research initiatives, technological innovation programs, government-supported digital infrastructure projects, and standards development activities related to large-scale data systems and intelligent computing environments.[1]

Abstract

Zhiguo Shi has established an academic profile centered on the integration of big data systems, intelligent analytics, urban digital infrastructure, and artificial intelligence applications. His research activities have included participation in national and regional research initiatives, development of government-oriented data governance systems, and publication of scholarly work related to data-driven intelligent systems. Shi has additionally contributed to the formulation of technical standards and platform-level innovation projects connected to public-sector digital transformation and smart city technologies.[2]

Keywords

Big Data Analytics, Artificial Intelligence, Intelligent Systems, Smart Cities, Urban Data Platforms, Digital Governance, Data Infrastructure, Machine Learning, Scientific Research, Data Standardization

Introduction

The increasing importance of data-driven technologies in governance, industry, and scientific research has led to expanded academic attention toward big data analytics and intelligent computational systems. Researchers working in this field often contribute not only through theoretical advances, but also through the implementation of scalable data infrastructures and applied innovation initiatives. Within this context, Zhiguo Shi has been associated with multiple projects involving data governance, AI-enabled applications, and intelligent urban systems in China.[1]

Zhiguo Shi obtained his doctoral degree in engineering from the Institute of Software of the Chinese Academy of Sciences in 2008. Following his doctoral studies, he joined the University of Science and Technology Beijing and progressed through academic positions including lecturer, associate professor, and professor. His leadership roles have included service as Director of the Big Data Research Center and participation in multiple scientific committees and laboratory initiatives focused on data systems and future city technologies.[3]

Research Profile

Zhiguo Shi’s research profile combines academic scholarship with applied technological development in public-sector and industrial environments. His documented research interests include big data systems, intelligent computing architectures, data governance methodologies, machine learning applications, and smart urban management technologies.[2]

He has supervised and participated in multiple nationally funded scientific projects, including initiatives supported by the National Natural Science Foundation of China and collaborative technology programs related to public digital infrastructure. His research activities have addressed psychological modeling through expression sequence analysis, blockchain-enabled governance platforms, AI industry service systems, and urban knowledge-base development projects for emerging smart city ecosystems.[4]

  • Big data analytics and intelligent systems research
  • Government-oriented data governance and management systems
  • Artificial intelligence infrastructure and application platforms
  • Urban digitalization and smart city technologies
  • Technical standards and data platform engineering

Research Contributions

Zhiguo Shi has contributed to the advancement of data infrastructure systems and public-sector digital governance through a combination of academic research and applied technological development. He has participated in the drafting and implementation of technical standards associated with government data platforms and digital governance frameworks.[2]

His professional activities also include leadership roles in major operational projects involving Beijing’s large-scale data management systems. These initiatives included platform operation services, data aggregation capabilities, AI infrastructure deployment, and smart sensing systems intended to support administrative efficiency and digital governance modernization.[4]

In addition to platform engineering activities, Shi has participated in interdisciplinary innovation efforts associated with future city technologies, intelligent robotics competitions, and vertical large-model applications. These activities demonstrate a continuing focus on translating academic knowledge into scalable technological applications.

Publications

Zhiguo Shi has authored and co-authored numerous scholarly publications related to big data systems, intelligent analytics, and applied artificial intelligence. His publication portfolio includes journal articles, conference proceedings, technical reports, and standards-oriented contributions.[1]

  • More than 79 indexed academic documents
  • Research publications in big data and intelligent systems
  • Participation in government and industry technical standards
  • Multiple invention patents associated with digital systems research
  • Collaborative research contributions in smart governance technologies

Selected scholarly outputs and indexing records are associated with DOI-based academic referencing systems and Scopus indexing databases.

Research Impact

Zhiguo Shi can be observed through his combination of academic publishing activity, project leadership, technology deployment, and educational contributions. His work has supported the development of operational data systems and governance technologies in Beijing and other emerging urban innovation environments.[2]

Zhiguo Shi has also received recognition in teaching and innovation-related activities. These include distinctions connected to higher education teaching performance, scientific advancement, and applied technology competitions. His contributions illustrate the interdisciplinary relationship between academic scholarship and public digital transformation.[3]

Award Suitability

Zhiguo Shi demonstrates characteristics commonly associated with recognition through scientific achievement awards. His documented contributions include interdisciplinary research, scientific publication activity, leadership in major data infrastructure projects, participation in national and regional innovation programs, and contributions to technical standardization.[2]

His involvement in large-scale public digital systems and intelligent platform development further reflects the practical relevance of his research activities. These accomplishments align with evaluation criteria frequently associated with international scientific recognition programs focused on innovation, impact, research productivity, and technological advancement.[4]

Conclusion

Zhiguo Shi has developed a multidisciplinary academic and technological profile centered on big data analytics, intelligent systems, digital governance, and smart urban technologies. Through research publications, project leadership, standards development, and applied innovation activities, he has contributed to the evolving landscape of data-driven infrastructure and intelligent public systems. His academic record and professional engagement support the relevance of his recognition within the context of the Outstanding Scientist Award presented through the Business Global Awards framework.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Zhiguo Shi, Author ID 57199774338. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57199774338
  2. H Chang, S Han, Z Shi, S Hu 2023 9th International Conference on Systems and Informatics (ICSAI), 2023. Limited resources multi-object tracking by utilizing motion cue from the meanshift algorithm
    https://ieeexplore.ieee.org/abstract/document/10423322/
  3. S Hu, X Zhang, Z Shi 2023 2nd International Conference on Machine Learning, Control …, 2023.> Student Expression Recognition Algorithm Based on TransConv
    https://ieeexplore.ieee.org/abstract/document/10475474/
  4. X Yao,. & Z Shi, XJ Du. Concurrency and Computation: Practice and Experience, (2023) Android malware detection based on sensitive features combination
    https://onlinelibrary.wiley.com/doi/abs/10.1002/cpe.7555

Lei Yang | Energy Big Data Analytics | Best Researcher Award

Published on by Business Global Awards

Mr. Lei Yang | Energy Big Data Analytics | Best Researcher Award

Mr. Lei Yang, College of Business Foreign Languages, Shenzhen Polytechnic University, China

Yang Lei, born in September 1988, is a distinguished researcher and educator specializing in big data analytics, artificial intelligence, and cybersecurity within the energy sector. With a robust academic foundation and extensive industry experience, he has significantly contributed to the development of intelligent systems for healthcare, finance, and smart infrastructure. Currently serving as a full-time computer science lecturer at Shenzhen Polytechnic University, Yang Lei is dedicated to advancing research in data mining and deep learning, aiming to address complex challenges in modern energy systems.

🎓 Education

Yang Lei’s academic journey began with a Bachelor of Science in Applied Mathematics from Hunan University (2010–2014), where he developed a strong analytical foundation. He further pursued a Master’s degree in Computer Technology at the same institution (2014–2016), focusing on the intersection of computational methods and real-world applications. This combination of mathematical rigor and technological proficiency has been instrumental in his multidisciplinary research endeavors.

💼 Professional Experience

Yang Lei’s professional career encompasses roles that bridge academia and industry. At Shenzhen Polytechnic University (2022–present), he imparts knowledge in data structures, big data, cloud computing, and Python programming. Previously, as a Big Data Engineer at Shenzhen Hualang Education Investment Co., Ltd. (2021–2022), he analyzed educational data to identify investment opportunities. His tenure at Shenzhen Medical Information Center (2019–2021) involved constructing a medical big data platform, while at GF Securities (2017–2019), he developed quantitative trading strategies. Earlier, at Guangzhou Unicom (2016–2017), he managed cloud platform development and product operations.

🔬 Research Interests

Yang Lei’s research interests lie at the confluence of data mining, deep learning, and cybersecurity, particularly within energy systems. He focuses on developing robust algorithms to enhance the resilience of smart grids and renewable energy infrastructures against cyber threats. His work often involves leveraging machine learning techniques to predict and mitigate risks associated with false data injection attacks, aiming to ensure the stability and security of modern energy networks.

🏆 Awards and Recognitions

Yang Lei’s contributions have been recognized through various grants and projects. Notably, he received funding from the Special Foreign Languages Research Project of the 2023 Annual Plan for Guangdong Provincial Philosophical and Social Sciences Program (GD23WZXC02-17), the Shenzhen Philosophy and Social Science Planning Project for 2022 (SZ2022D057), and research and teaching projects at Shenzhen Polytechnic University (7025310580). These accolades underscore his commitment to advancing research in data analytics and cybersecurity.

📚 Publications

Adversarial False Data Injection Attacks on Deep Learning-Based Short-Term Wind Speed Forecasting.

Cybersecurity Challenges in PV-Hydrogen Transport Networks: Leveraging Recursive Neural Networks for Resilient Operation.

weixu liu | data analysis | Best Researcher Award

Published on by Business Global Awards

Assist Prof Dr. weixu liu – data analysis – Best Researcher Award

Department of Computer Science/Anhui Medical University | China

         Profile

🎓Early Academic Pursuits 

Education and Training

He, born on September 9, 1987, in China, has always been deeply passionate about the field of computer science. His academic journey began with a strong foundation in the sciences, which ultimately led him to pursue higher education in this dynamic field. He obtained his doctoral degree (Ph.D.) from the prestigious Zhejiang University in 2022. His research during this period focused on advanced data analysis, specifically in the realm of big data, machine learning, and non-destructive evaluation, laying the groundwork for his future contributions to both academia and industry. His academic achievements were not limited to his formal education; he was actively involved in various research projects and initiatives, even before formally joining the academic workforce.

💼Professional Endeavors 

Academic Positions

After completing his Ph.D., He embarked on a professional career that quickly saw him rise to prominence. In June 2014, he joined Anhui Medical University as an associate professor, deputy director, and master supervisor in the Department of Computer Science. His role at Anhui Medical University not only involves teaching and mentoring the next generation of computer scientists but also leading groundbreaking research projects. His expertise in big data analysis has enabled him to make significant strides in machine learning, structural health monitoring, and non-destructive evaluation. His professional journey is marked by his leadership in various projects, including ten research projects that have been either completed or are currently ongoing.

📚Contributions and Research Focus on Community-Based Collaborative Urban Regeneration Processes

His contributions to the field of computer science are both vast and impactful. He has obtained more than ten authorized national invention patents, over twenty utility model patents, and more than ten national computer software copyrights. His research interests primarily revolve around big data analysis, with a specific focus on machine learning and non-destructive evaluation. He has published over 20 peer-reviewed journal articles, including 8 in SCI and SCIE indexed journals. His work has garnered a citation index of 8 on platforms like Scopus, Web of Science, and PubMed, reflecting the significance and influence of his research in the global scientific community.

🏆Accolades and Recognition 

Throughout his career, He has received numerous awards and recognitions that underscore his excellence in research and innovation. He has been honored with a third-class prize for teaching achievements in Anhui Province, a testament to his dedication to education. Additionally, he has been recognized with eight other awards for his contributions to the field of computer science. As a senior member of the China Instrument and Control Society and a member of the Chinese Society for Vibration Engineering, His expertise is widely acknowledged by his peers. His role as a reviewer for multiple journals and conferences further highlights his standing in the academic community.

🌍 Impact and Influence 

Community Impact

His work has had a profound impact on both academia and industry. His research has led to the successful completion of multiple projects with significant funding, including a notable conversion of scientific and technological achievements worth 500,000 RMB. His involvement in national-level projects, such as the National Natural Science Foundation and various R&D plans, demonstrates his influence in shaping the future of computer science research in China. Moreover, his role as an educator and mentor has empowered countless students to pursue careers in this field, thereby extending his influence to the next generation of computer scientists.

🔮Legacy and Future Contributions 

Looking ahead, He is poised to continue his groundbreaking work in the field of big data analysis. His legacy is already being built through his contributions to research, innovation, and education. As an associate professor, deputy director, and master supervisor at Anhui Medical University, he will undoubtedly continue to mentor and inspire students and researchers alike. His future contributions are likely to focus on expanding the applications of big data analysis, particularly in the areas of machine learning and structural health monitoring. With a strong foundation and a track record of excellence, His impact on the field of computer science will continue to grow, cementing his legacy as a leading figure in the world of data analysis.

📚Publications

An efficient approach for guided wave structural monitoring of switch rails via deep convolutional neural network-based transfer learning

Authors: Liu, W., Tang, Z., Lv, F., Chen, X

Journal: 2021 IEEE 2nd International Conference on Pattern Recognition and Machine Learning,

Evolution of Knowledge Structure in an Emerging Field Based on a Triple Helix Model: The Case of Smart Factory

Authors: Liu, D., Zhu, Y.P.

Journal: Measurement Science and Technology,

Sliding Window Dynamic Time-Series Warping-Based Ultrasonic Guided Wave Temperature Compensation and Defect Monitoring Method for Turnout Rail Foot

Authors: Tang, Z., Ma, J., Liu, W., Zhang, P., Lv, F.

Journal: IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control,

Application of compressed sensing in the guided wave structural health monitoring of switch rails

Authors: Tang, Z., Liu, W., Yan, R., Lv, F., Chen, X.

Journal: Measurement Science and Technology,

High‐sensitivity ultrasonic guided wave monitoring of pipe defects using adaptive principal component analysis

Authors: Ma, J., Tang, Z., Lv, F., Zheng, Y., Zheng, Y.

Journal: Sensors,