Dr. Micheal Arowolo | Machine Learning | Best Researcher Award
Assistant Professor | Xavier University of Louisiana | United States
Dr. Micheal Olaolu Arowolo is an accomplished scholar, researcher, and educator in the field of computer science, with expertise in machine learning, health informatics, and bioinformatics. He currently serves as an Assistant Professor of Health Informatics at Xavier University of Louisiana, where he teaches master’s students in areas such as population health, statistics in health sciences, and healthcare quality. He earned his Ph.D. in Computer Science from Landmark University in Nigeria, building on a Master’s degree in Computer Science from Kwara State University and a Bachelor’s degree from Al-Hikmah University. He later advanced his academic career as a Post-doctoral Research Scholar at the University of Missouri’s Bond Life Sciences Center, where he contributed to the development of deep learning and machine learning models aimed at predicting relevant gene names in pathway figures for health practitioners. Dr. Arowolo’s teaching and research experience spans institutions in both the United States and Nigeria, where he has lectured and supervised students across a broad range of subjects, including artificial intelligence, data communication and networking, object-oriented programming, and computational theory. His research efforts have produced impactful publications in reputable journals indexed by Elsevier, IEEE, ISI, and Web of Science. He has also developed applied solutions for the United Nations Sustainable Development Goals, particularly SDG 11, by applying machine learning models to domains such as healthcare, telecommunications, and banking. His contributions to academic excellence helped Landmark University improve its global ranking significantly. An active member of the global research community, Dr. Arowolo belongs to several professional organizations, including IEEE, ACM, ISCB, and IAENG. He also serves as a reviewer and editorial board member for internationally recognized journals such as Heliyon, IEEE Access, and Journal of Big Data. His dedication to academic mentorship is reflected in his supervision of numerous graduate and undergraduate projects, guiding students to adopt innovative approaches to machine learning and computational methods. Recognized among the top 500 scholars in Nigeria by SciVal-Scopus, Dr. Arowolo has received certifications in SQL, Linux, Oracle, project management, and network administration. Through a blend of research, teaching, and leadership, he continues to contribute to knowledge creation, innovation, and the advancement of computational science and health informatics worldwide.
Featured Publications:
Arowolo, M. O., & co-authors. (n.d.). Enhancing cyber threat detection with an improved artificial neural network model. Data Science and Management.
Arowolo, M. O., & co-authors. (n.d.). Computational intelligence in big data analytics. In Book chapter.
Arowolo, M. O., & co-authors. (n.d.). A comprehensive evaluation of large language models in mining gene relations and pathway knowledge. Quantitative Biology.
Arowolo, M. O., & co-authors. (n.d.). Internet of things (IoT): Concepts, protocols, and applications. In Book chapter.
Arowolo, M. O., & co-authors. (n.d.). Adsorptive removal of synthetic food dyes using low-cost biochar: Efficiency prediction, kinetics and desorption index evaluation. Bioresource Technology Reports.
Arowolo, M. O., & co-authors. (n.d.). Gene name recognition in gene pathway figures using Siamese networks. In Conference proceedings.
Arowolo, M. O., & co-authors. (n.d.). Enhancing healthcare data security: An intrusion detection system for web applications with SVM and decision tree algorithms.