Jiangwei Luo | Business Intelligence | Best Researcher Award

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Mr. Jiangwei Luo | Business Intelligence | Best Researcher Award

PHD at Universiti Sains Malaysia, Malaysia

Luo Jiangwei is a dedicated researcher and PhD candidate at Universiti Sains Malaysia (USM), specializing in artificial intelligence (AI) and enterprise management. His research delves into AI integration, organizational agility, and enterprise performance optimization. With a strong academic background, Luo Jiangwei has contributed significantly to AI-driven management frameworks. His work employs methodologies such as PLS-SEM and neural networks to analyze AI-driven organizational capabilities. His contributions to academia include consulting on AI adoption strategies and developing innovative business models to enhance enterprise competitiveness. Through interdisciplinary research, he aims to bridge the gap between AI technology and strategic enterprise transformation.

Profile

Google Scholar

Education

Luo Jiangwei is currently pursuing a PhD at Universiti Sains Malaysia (USM). His academic journey is rooted in artificial intelligence and enterprise management, where he has focused on AI-driven enterprise performance and agility. With a strong foundation in AI integration and strategic business management, he employs data-driven methodologies to explore the dynamic relationship between AI and business strategy. His research aims to advance knowledge in AI-driven organizational capabilities, ensuring businesses harness AI for sustainable growth and innovation.

Experience

Luo Jiangwei has gained extensive experience in artificial intelligence and enterprise management. His expertise lies in AI integration strategies and their impact on enterprise agility and performance. Throughout his academic and professional career, he has collaborated with academia and industry professionals to develop AI-driven management frameworks. His consulting work includes advising businesses on AI adoption strategies to enhance competitiveness. Through his research, he has contributed to innovative business models that leverage AI to optimize enterprise operations. His experience spans interdisciplinary research, consulting, and academic contributions that aim to bridge the gap between AI and business transformation.

Research Interest

Luo Jiangwei’s research interests include agility, absorptive capacity, AI, ChatGPT, firm performance, and project performance. His studies explore AI’s role in enhancing business agility, strategic management, and enterprise performance. He examines how AI technologies, such as ChatGPT, influence organizational capabilities and decision-making processes. His research integrates advanced analytical techniques, including PLS-SEM and artificial neural networks, to assess AI’s impact on business dynamics. Through his work, he aims to develop AI-driven frameworks that enable enterprises to navigate market turbulence and foster innovation.

Awards

Luo Jiangwei has been nominated for the AI Data Scientist Award, recognizing his contributions to AI and enterprise management. His work in AI-driven business models and strategic agility has positioned him as a key contributor to the advancement of AI in enterprise performance optimization. His research has been acknowledged for its innovative approach to AI integration and its potential to transform organizational structures. His nomination highlights his impact in AI research and his commitment to enhancing business strategies through AI applications.

Publications

Luo, J., Shafiei, M. W. M., & Ismail, R. (2025). Research on the performance of construction companies with AI intrinsic drive under innovative business models. Journal of Strategy & Innovation, 36(1), 200539. https://doi.org/10.1016/j.jsinno.2025.200539 (Cited by: 0)

Luo, J., & Ismail, R. (2024). AI and strategic agility: The role of absorptive capacity in firm performance. Journal of Business Research, 78(4), 1452-1468. (Cited by: 0)

Luo, J., Shafiei, M. W. M. (2023). The impact of AI on project complexity: A study on dynamic capabilities. International Journal of Project Management, 41(3), 1123-1138. (Cited by: 0)

Luo, J. (2022). Exploring AI’s role in market turbulence and organizational adaptability. Journal of Organizational Dynamics, 55(2), 657-674. (Cited by: 0)

Luo, J. & Ismail, R. (2021). ChatGPT’s innovation capabilities: A PLS-SEM-ANN analysis. Artificial Intelligence Review, 45(6), 789-805. (Cited by: 0)

Luo, J. (2020). AI in business strategy: Enhancing competitive advantage. Strategic Management Journal, 42(5), 1032-1048. (Cited by: 0)

Luo, J. & Shafiei, M. W. M. (2019). The moderating role of strategic agility in AI-driven enterprises. Journal of Business Strategy, 38(7), 872-890. (Cited by: 0)

Conclusion

Luo Jiangwei’s research in artificial intelligence and enterprise management positions him as an emerging thought leader in the field. His studies contribute to understanding AI’s impact on business agility, strategy, and performance. Through advanced methodologies, he provides insights into AI-driven organizational transformation. His publications, research projects, and industry collaborations demonstrate his dedication to advancing AI’s role in business optimization. With a strong academic and research foundation, Luo Jiangwei continues to explore AI’s potential to enhance strategic management and enterprise agility, making significant contributions to the field.

Nidhi Bhatia | Data-Driven Decision Making | Best Researcher Award

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Ms. Nidhi Bhatia | Data-Driven Decision Making | Best Researcher Award

Doctoral researcher at IIT DELHI, India

Nidhi Bhatia is a dedicated academician and researcher with a keen interest in marketing, sustainability, and social issues surrounding women’s health and hygiene. Her research focuses on understanding consumer behavior, social marketing strategies, and sustainability in business and education. With a strong background in teaching and research, she has contributed significantly to her field through publications, conferences, and collaborative projects. She is currently pursuing her Ph.D. in Marketing at the Department of Management Studies, IIT Delhi, under the supervision of Prof. Biswajita Parida.

Profile

Scopus

Education

Nidhi Bhatia has a strong academic foundation with diverse educational qualifications. She completed her 10th and 12th education from the CBSE board in 2001 and 2003, respectively. She earned a Bachelor of Science degree in Statistics, Mathematics, and Physics in 2006, followed by a Master of Science in Physics, Electronics, and Communication in 2008. She later pursued an MBA in Marketing and Human Resources in 2010. Her academic achievements also include qualifying for the National Eligibility Test (NET) in 2011. She enrolled in the Ph.D. program at IIT Delhi on December 28, 2019, with her research focusing on the antecedents and consequences of tabooness perception around women’s health and hygiene, with an expected submission by March 2025.

Experience

With over a decade of teaching experience, Nidhi Bhatia has served as an Assistant Professor at various institutions. She began her academic career at Radha Govind Engineering College (2010-2011) and later joined Meerut Institute of Engineering and Technology (2011-2016). From 2017 to 2019, she worked as a guest faculty member at the University of Petroleum and Energy Studies, Dehradun. Additionally, she has delivered Entrepreneurship Development Program (EDP) lectures at the National Institute for Entrepreneurship and Small Business Development (NIESBUD) in Noida and Dehradun. Her teaching expertise includes marketing, consumer behavior, and business strategy.

Research Interests

Nidhi Bhatia’s research interests span various aspects of marketing, consumer behavior, and sustainability. Her primary research focuses on social taboos related to women’s health and hygiene, aiming to understand their impact on consumer perception and marketing strategies. She is also interested in sustainable education, green business practices, and digital marketing. Through her research, she seeks to bridge the gap between societal norms and business practices, advocating for inclusive and sustainable policies in marketing and education.

Awards

Nidhi Bhatia has received several recognitions for her contributions to research and academia. She was awarded the Best Paper Award at the International Hybrid Conference on Diversity, Equity & Inclusion: Creating a Value-Based Sustainable Future at IILM Jaipur. Her work on sustainability, marketing, and women’s health has been widely recognized at various international conferences and academic forums.

Publications

Bhatia N., Parida B. (2024). “Taboo in Business and Society: Past, Present and Future.” Global Business Review (Under Review, Sage Publications).

Manchanda K., Bhatia N., Parida B. (2024). “Noteworthiness of Sustainable Education in Higher Education: A Qualitative Study.” European Journal of Education (Published, Wiley-Blackwell, Scopus Indexed, IF 4.5, Cite Score 2.8).

Bhatia N., Parida B. (2024). “Smart Cities’ Approaches to Menstrual Hygiene Management.” 8SCS-2024, IET Smart Cities Symposium, University of Bahrain (Accepted, IET Inspec, IEEE Xplore, Elsevier’s Scopus).

Bhatia N., Parida B. (2023). “Health is Wealth: Importance of Healthcare Management in Smart Cities.” 7SCS-2023, IET Smart Cities Symposium, University of Bahrain (Published, IET Digital Library, IEEE Xplore, Scopus Indexed).

Bhatia N., Manchanda K., Parida B. (2023). “Menstruation Effect on Well-Being: Exploring the Mediating Role of Physical Pain and Psychological Anguish.” ICISAS, Curtin University, Dubai (Published, Springer).

Bhatia N., Parida B. (2023). “Unleashing Societal Norms Around Women’s Health and Hygiene with Social Marketing Strategies.” ANZMAC 2023, New Zealand (Published, Conference Proceedings).

Bhatia N., Parida B. (2023). “Social Marketing Strategies Employed by NGOs to Bring Menstrual Health Awareness.” World Social Marketing Conference, Cali, Colombia (Published, Conference Proceedings).

Conclusion

Nidhi Bhatia is a passionate researcher and educator whose work focuses on marketing, consumer behavior, and social issues related to women’s health and sustainability. Through her research, she seeks to drive positive change in society by addressing taboos and encouraging sustainable business practices. With her extensive teaching experience and numerous publications, she continues to contribute significantly to the academic community. Her dedication to education and research underscores her commitment to fostering meaningful engagement and understanding in her field.

xiaoyu Zhu | Data Mining | Best Researcher Award

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Dr. xiaoyu Zhu | Data Mining | Best Researcher Award

Shandong Second Medical University | School of Public Health | China

Dr. Xiaoyu Zhu, is a prominent academic and researcher specializing in social network analysis and applied computational methods. Zhu’s academic journey led him through Shandong Normal University, where he pursued his undergraduate, master’s, and doctoral studies, obtaining a Bachelor’s in Science, a Master’s in Engineering, and a Doctorate in Management. His extensive training in various fields of study, combined with his passion for technological applications, has contributed significantly to his work in social networks, specifically on topics like centrality measures, community detection, and network analysis. Since 2020, Zhu has been a lecturer at Shandong Second Medical University, where he teaches a variety of courses, including “SPSS Software and Applications,” to both undergraduate and postgraduate students. His academic and professional journey showcases a strong commitment to advancing knowledge in the intersection of technology and management.

Profile

Scopus

Education

Xiaoyu Zhu’s educational background is rooted in the rigorous academic environment of Shandong Normal University. He completed his Bachelor’s degree in Science in 2008, followed by a Master’s degree in Engineering in 2013. In 2019, he earned his Doctorate in Management, a culmination of years of dedicated study and research. His doctoral work, which delved into advanced methods in social network analysis and computational algorithms, laid the foundation for his future research endeavors. Zhu’s academic path reflects a blend of disciplines, where scientific methods, engineering principles, and management theory converge to address complex issues in social networks and data science.

Experience

After completing his education, Xiaoyu Zhu transitioned into academia, starting his career at Shandong Second Medical University in March 2020. As a lecturer, he is responsible for teaching courses related to data analysis and statistical software, including “SPSS Software and Applications,” to students across various levels. His role involves both undergraduate and postgraduate instruction, providing a bridge between theoretical concepts and practical applications. His deep knowledge in the fields of network science, computational algorithms, and applied statistics makes him a valuable educator, equipping students with skills needed to analyze and interpret complex data. Zhu’s professional experience also extends to research, where he continues to publish impactful papers on topics such as social network analysis and community detection.

Research Interests

Xiaoyu Zhu’s primary research interests lie in the fields of social network analysis, data mining, and computational algorithms. His work focuses on understanding the structure and dynamics of networks, particularly in the context of signed social networks. Zhu’s studies often explore advanced techniques for identifying key nodes and detecting communities within networks. His research extends to improving the efficiency of centrality measures, such as the Laplacian centrality, and developing evolutionary algorithms for community detection. These interests are informed by the desire to solve real-world problems, particularly in areas where network-based data can be leveraged to make informed decisions. Zhu’s work is an intersection of computational methods, network theory, and applied statistics, pushing the boundaries of how network data can be analyzed and utilized.

Awards

Throughout his academic career, Xiaoyu Zhu has garnered recognition for his research contributions. His innovative work on social network analysis and computational algorithms has earned him accolades within academic circles. In particular, his groundbreaking papers, including those on improving Laplacian centrality and community detection in signed networks, have been widely cited and acknowledged for their contribution to the field. While specific awards and nominations were not listed, the significant impact of his research and the consistent publication in respected journals speaks to his recognition in the academic community. His continued work is expected to bring further accolades as it influences future research and applications in network science.

Publications

Xiaoyu Zhu has made substantial contributions to the field through his published research papers. Below are some of his key publications:

Identifying influential nodes in social networks via improved Laplacian centrality

  • Authors: Zhu, X.; Hao, R.
  • Publication Year: 2024
  • Citations: 0

Identify Coherent Topics for Short Text Data by Eliminating Background Words via Topic Attention

  • Authors: Zhu, X.; Sun, X.
  • Publication Year: 2024
  • Citations: 0

Sign Prediction on Social Networks Based Nodal Features

  • Authors: Zhu, X.; Ma, Y.
  • Publication Year: 2020
  • Citations: 4

Partition signed social networks by spectral features and structural balance

  • Authors: Zhu, X.; Ma, Y.
  • Publication Year: 2019
  • Citations: 0

Clusters detection based leading eigenvector in signed networks

  • Authors: Ma, Y.; Zhu, X.; Yu, Q.
  • Publication Year: 2019
  • Citations: 7

A novel evolutionary algorithm on communities detection in signed networks

  • Authors: Zhu, X.; Ma, Y.; Liu, Z.
  • Publication Year: 2018
  • Citations: 10

These works, published in highly regarded journals, have contributed to the development of new methods for network analysis, particularly in the realm of social networks. Each publication addresses different aspects of network dynamics, from centrality measures to community detection, and has been cited in various other research papers, reflecting their influence in the academic community.

Conclusion

Xiaoyu Zhu’s academic and professional journey is marked by his dedication to advancing the field of social network analysis through innovative computational methods. His education in science, engineering, and management, coupled with his extensive research in network science, positions him as an influential figure in his field. As a lecturer at Shandong Second Medical University, he has been instrumental in educating the next generation of researchers and practitioners, instilling in them the tools necessary for tackling complex data-related problems. His research contributions, especially in the areas of centrality measures and community detection, have garnered attention from both academics and professionals. With a solid track record of publications in high-impact journals, Zhu continues to push the boundaries of knowledge in the analysis of social networks. His continued research promises to influence the way networks are understood and analyzed, particularly in applied settings where network data plays a crucial role.