Dan Li | Computer Vision | Best Researcher Award

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Dr. Dan Li | Computer Vision | Best Researcher Award

Lecturer | University of Shanghai for Science and Technology | China

Dr. Dan Li is a Lecturer at the University of Shanghai for Science and Technology, specializing in decision theory, artificial intelligence management, and efficiency analysis. Her research integrates data driven decision making methods with emerging AI technologies to address complex management and operational challenges. She has contributed to advancements in efficiency measurement, intelligent systems, and optimization through funded research projects supported by national and provincial foundations. Dr. Li’s publications appear in leading journals such as Knowledge-Based Systems, Advanced Engineering Informatics, Omega, Journal of the Operational Research Society, and Journal of Cleaner Production, where she explores topics including AI based object detection, data envelopment analysis, and performance evaluation of industrial and service systems. Her work bridges theoretical modeling with practical applications in sectors such as finance, education, and sustainability. In addition to her research, she actively contributes to the academic community as a reviewer for high-impact international journals and engages in interdisciplinary collaborations focusing on the integration of artificial intelligence into management science. Through her innovative approaches and international research engagements, Dr. Li continues to advance the fields of decision science and AI-driven management solutions.

Profiles: Scopus | Orcid

Featured Publications

Tang, J., Li, D., Yang, J., Chen, J., & Yuan, R. (2025). Leveraging large visual models for enhanced object detection: An improved SAM-YOLOv5 model. Knowledge-Based Systems, 114757.

Yang, J., Emrouznejad, A., & Li, D. (2024, October 25). An improved game cross-efficiency approach with dual-role factors for measuring the efficiency of Chinese “985 project” universities. Journal of the Operational Research Society.

Chen, C.-M., & Li, D. (2024, July). Weighing in on the average weights: Measuring corporate social performance (CSP) score using DEA. Omega, 103072.

Yang, J., Li, D., & Li, Y. (2024, January). A generalized data envelopment analysis approach for fixed cost allocation with preference information. Omega, 102948.

Yang, J., & Li, D. (2022, June 9). Finding the single efficient unit in data envelopment analysis with flexible measures. Journal of the Operational Research Society.

Manjunath BR | Machine Learning | Best Researcher Award

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Prof. Dr. Manjunath BR | Machine Learning | Best Researcher Award

Professor | Tecnologico De Monterrey | Mexico

Prof. Dr. Manjunath BR is an accomplished academic leader and finance professional specializing in business analytics, financial modeling, econometrics, fintech, and artificial intelligence applications in finance. With extensive experience across academia and industry, he has contributed significantly to advancing data-driven financial education and research. His expertise spans financial analytics, investment management, corporate restructuring, and data visualization using advanced tools such as EViews, R, Python, Tableau, and Power BI. He has published extensively in ABDC, Scopus, UGC, and peer-reviewed journals, focusing on the intersection of finance, data science, and technology. As a researcher and educator, he integrates predictive analytics and machine learning into financial decision-making, contributing to the understanding of fintech adoption, banking innovations, and risk management. His academic leadership includes curriculum design, faculty development, and corporate collaborations to enhance experiential learning. He has served as a resource person for numerous international workshops and training programs on financial analytics, econometrics, and data visualization, empowering professionals and students with analytical and quantitative skills. Dr. Manjunath has authored and edited several books with leading global publishers, covering transformative areas such as AI in management education, blockchain economics, sustainable investment, and Quality 5.0 paradigms. He has also secured a patent for the application of AI in optimizing HR data management and authored a textbook on machine and deep learning. His professional journey embodies innovation, interdisciplinary scholarship, and a commitment to integrating technology with finance to foster global academic and industry excellence.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

Raju, J. K., Manjunath, B. R., & Rehaman, M. (2018). An empirical study on the effect of gross domestic product on inflation: Evidence from Indian data. Academy of Accounting and Financial Studies Journal, 22(6), 1–11.

Raju, J. K., Manjunath, B. R., & Dhakal, M. H. (2015). Impact and challenges of merger and acquisition in Nepalese banking and financial institutions. Journal of Exclusive Management Science, 4(8), 25–33.

Raju, J. K., Manjunath, B. R., & G. M. M. N. (2015). Performance evaluation of Indian equity mutual fund schemes. Journal of Business Management & Social Sciences Research (JBM&SSR).

Manjunath, B. R., & Raju, J. K. (2020). Short-run performance evaluation of under-priced Indian IPOs. Law and Financial Markets Review.

Chaitra, R., Manjunath, B. R., & Rehaman, M. (2019). An analysis of pre and post-merger of Indian banks: An event analysis approach. International Journal for Research in Engineering Application & Management, 4.