Manjunath BR | Machine Learning | Best Researcher Award

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.

Wael Badawy | Data Science | Pioneer Researcher Award

Prof. Wael Badawy | Data Science | Pioneer Researcher Award

Head of Data science Department | Egyptian Russian University | Egypt

Prof. Wael Badawy, Ph.D., P.Eng., SFAHE, SIEEE, SACM, is a distinguished academic, researcher, engineer, and business leader with over twenty-eight years of international experience spanning academia, research, innovation, and technology commercialization. He has served in key academic and executive positions, including Executive Director of ABM College in Canada, Professor at several universities in Egypt, the United Kingdom, and Canada, and Adviser for Innovation and Entrepreneurship at Umm Al Qura University in Saudi Arabia. His expertise encompasses cybersecurity, artificial intelligence, computer engineering, information technology management, and digital transformation. Prof. Badawy has authored more than four hundred scientific publications, thirty-four patents, and over fifty books and proceedings, and has delivered numerous invited lectures and tutorials worldwide. Recognized with over ninety national and international awards, including distinctions from IEEE, Alberta Venture, the Global Business Leaders Magazine, and the QS Reimagine Education Awards, he has played a pivotal role in establishing and accrediting educational programs, serving on technical and quality assurance committees, and leading initiatives for national research and innovation strategies. As a Senior Fellow of the Advanced Higher Education and a Professional Engineer in Canada, Prof. Badawy continues to advance research excellence, technological innovation, and higher education development through visionary leadership, mentorship, and global collaboration.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

Badawy, W. (2025). The ethical implications of using children’s photographs in artificial intelligence: Challenges and recommendations. AI and Ethics, 5(2).

Maged, S., Mohamed, A., & Badawy, W. (2025, May 10). Audiogram-based tinnitus detection using deep learning: A comparative study of CNN architectures. In Proceedings of ICMISI 2025. IEEE.

Elnady, N., Adel, A., & Badawy, W. (2025, May 10). Enhancing kidney stone detection using YOLOv9: A deep learning approach. In Proceedings of ICMISI 2025. IEEE.

Elnady, N., Adel, A., & Badawy, W. (2025, April 13). Advancing brain tumor detection with YOLOv9: A comprehensive evaluation. In Proceedings of ICCIT 2025. IEEE.

Soliman, S. S., Abd El-Samie, F. E., Abd El-atty, S. M., Badawy, W., & Eshra, A. (2025). DNA nanotechnology for cell-free DNA marker for tumor detection: A comprehensive overview. Nucleosides, Nucleotides & Nucleic Acids, 44(4), 233–249.