Xuanjiang Chen | Building Energy Management | Research Excellence Award

Published on by Business Global Awards

Research Excellence Award

Xuanjiang Chen
Guangzhou Metro Design & Research Institute Co., Ltd.

Xuanjiang Chen
Affiliation Guangzhou Metro Design & Research Institute Co., Ltd.
Country China
Scopus ID 57970218200
Documents 2
Citations 14
h-index 2
Subject Area Building Energy Management
Event Business Global Awards

Xuanjiang Chen is a researcher affiliated with Guangzhou Metro Design & Research Institute Co., Ltd., China, whose scholarly work is primarily associated with Building Energy Management. The Research Excellence Award article presents an academic overview of his publicly indexed research profile, highlighting publications indexed in Scopus, bibliometric indicators, research interests, and scholarly recognition. The profile is written in a neutral, encyclopedic style suitable for academic reference.[1][2]

Abstract

Xuanjiang Chen has contributed to research concerning building energy management and engineering-related studies supporting sustainable infrastructure development. His indexed publications demonstrate participation in technical research addressing energy efficiency, optimization methodologies, and engineering applications. Bibliometric indicators available through Scopus provide measurable evidence of scholarly dissemination and citation activity.[1][3]

Keywords

Building Energy Management, Energy Efficiency, Smart Buildings, Sustainable Infrastructure, Engineering Design, Energy Optimization, Urban Transportation, HVAC Systems, Environmental Engineering, Green Buildings.

Introduction

Building Energy Management represents a multidisciplinary research field integrating engineering, environmental science, automation, and data-driven optimization to improve energy utilization in modern infrastructure. Researchers in this discipline contribute toward reducing operational costs, minimizing environmental impacts, and improving sustainability through innovative engineering solutions. Scholarly publications indexed in international databases provide an objective basis for evaluating academic productivity and scientific influence.[3]

Research Profile

According to publicly available Scopus indexing information, Xuanjiang Chen has authored two indexed scholarly documents that have collectively received fourteen citations, resulting in an h-index of 2. These metrics indicate measurable scholarly visibility while reflecting focused contributions within a specialized engineering domain.[1]

  • Primary research area: Building Energy Management.
  • Institution: Guangzhou Metro Design & Research Institute Co., Ltd.
  • Country: China.
  • Indexed publications and citation record available through Scopus.

Research Contributions

The available scholarly record indicates contributions to engineering research associated with energy-efficient building operation, sustainable facility management, and optimization techniques. Such studies contribute to the broader objectives of improving building performance, reducing energy consumption, and supporting environmentally responsible urban infrastructure. These research themes remain highly relevant to sustainable development initiatives and contemporary engineering practice.[3][2]

Publications

The research portfolio currently includes two Scopus-indexed publications addressing technical aspects of building energy management. Publication records demonstrate participation in peer-reviewed scholarly communication and provide an accessible basis for evaluating research quality and citation performance.[1]

Research Impact

Bibliometric indicators such as citation counts and the h-index are commonly employed to assess scholarly visibility and influence. While quantitative metrics do not fully represent research quality, they provide useful evidence regarding academic dissemination, citation recognition, and engagement by the wider scientific community. Xuanjiang Chen’s indexed profile reflects emerging scholarly impact within his specialized research area.[2]

Award Suitability

Based on publicly available scholarly information, Xuanjiang Chen demonstrates qualifications appropriate for consideration within research recognition programs emphasizing engineering innovation, academic productivity, and measurable scholarly contribution. His publication record, citation performance, and specialized research interests support evaluation for recognition under the Business Global Awards framework using transparent academic assessment criteria.[1][3]

Conclusion

Xuanjiang Chen represents a researcher whose scholarly activities contribute to the advancement of building energy management and sustainable engineering practices. His indexed publications and citation record provide objective indicators of academic engagement while supporting recognition through international research award initiatives. Continued scholarly activity may further strengthen his academic profile and scientific impact.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Xuanjiang Chen, Author ID 57970218200. Scopus.
    https://www.scopus.com/pages/authors/57970218200
  2. X Chen, S Lin, S Zhang, et al. (2023). Software-defined networking enabled optical data center network with flexible QoS provisioning.
    https://www.sciencedirect.com/science/article/pii/S0030401822007763
  3. X Chen, S Lin, Y Zhang, et al. (2025). Review and Decision-Making Tree for Methods to Balance Indoor Environmental Comfort and Energy Conservation During Building Operation.
    https://www.mdpi.com/2071-1050/17/15/7016

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.

Lei Yang | Energy Big Data Analytics | Best Researcher Award

Published on by Business Global Awards

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

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

👤 Profile

🎓 Education

Yang Lei completed both his Master’s and Bachelor’s degrees at Hunan University, earning his MSc in Computer Technology (2014–2016) and his BSc in Applied Mathematics (2010–2014). His graduate coursework focused on key technical areas including algorithm design, data mining, distributed computing, advanced data structures, graph theory, and network security. His academic path reveals a consistent excellence in logic, problem-solving, and practical computing theory.

💼 Professional Experience

Yang Lei has a multifaceted professional background spanning cloud computing, education, financial engineering, and healthcare analytics. Notable roles include Project Manager at Shenzhen Medical Information Center (2019–2021), Big Data Engineer at Hualang Education (2021–2022), and Research Analyst at GF Securities (2017–2019). In the public sector, he contributed to China Unicom’s cloud innovation projects, while in academia, he now teaches data structures, Python programming, big data, and cloud computing. Across each role, Yang has delivered impact through strategic data modeling, cloud platform development, and AI-driven systems.

🔬 Research Interests

Yang’s research interests center on data mining, machine learning, medical big data analytics, financial forecasting algorithms, and smart agriculture systems. He has led or contributed to several innovative projects, including:

Post-structural processing of multi-modal medical records using NLP and Hadoop

Hadoop-based smart healthcare platforms and community-wide data governance

Quantitative forex and stock trading strategies using black forest, neural network, and Bayesian algorithms

Development of IoT-driven smart agriculture and AI-powered smart locks

He also participated in projects funded by National Natural Science Foundation and co-developed a weather prediction system with the National Supercomputing Center.

🏅 Awards and Leadership

National Third Prize in Physics Olympiad (High School)

Second Prize in National University Mathematical Modeling Competition

Hunan Province Outstanding Undergraduate Graduate

Multiple university-level Merit Scholarships
In student leadership, he served as Class Representative, Deputy Head of the Student Union, and Vice President of a university association.

📚 Publication Top Notes

“Lei, Yang (2020). ‘Predictive Algorithms for Forex Markets Using Bayesian Models’. Journal of Financial Data Science. [Cited by: 12].”