Micheal Arowolo | Machine Learning | Best Researcher Award

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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.

Profile:  Scopus | ORCID | Google Scholar

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.

Kyunghyune Rhee | Machin Learning Security | Best Researcher Award

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Prof Dr. Kyunghyune Rhee | Machin Learning Security | Best Researcher Award

Prof. Pukyong National University, South Korea

Dr. Kyung-Hyune Rhee is a Full Professor in the Division of Computer and Artificial Intelligence Engineering at Pukyong National University, Busan, South Korea. He holds a Ph.D. in Mathematics from KAIST and has extensive experience in academia and research, with work spanning across the USA, Japan, Australia, and the Philippines. Dr. Rhee has held various academic and leadership roles, including Head of Departments and Visiting Scholar positions. His research interests include blockchain, cybersecurity, and vehicular cloud computing, with numerous publications in high-impact international journals and conferences over the last five years. He is an active member of several professional societies.

 

Professional Profiles:

scopus

Education 🎓

Ph.D. in Mathematics, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea (1988-1992)🎓 M.Sc. in Applied Mathematics, KAIST, Daejeon, Korea (1984-1985)🎓 B.Sc. in Mathematics Education, KyungPook National University, Daegu, Korea (1978-1982)

Membership in Professional Societies 👥

Member of IEEE Computer Society👥 Member of IASTED (The International Association of Science & Technology for Development)👥 Member of International Association Cryptology Research👥 Vice President, The Korean Multimedia Society (KMMS)👥 Former President of the Korean Information Institute of Security and Cryptology (KIISC)👥 Associate Editor of Journal of KMMS

Countries of Work Experience🌏

USA, Australia, Japan, Korea, and The Philippines

 Employment Record 🏢

Employer: Pukyong National University, Busan, Korea💼 Position: Full Professor, Division of Electronic, Computer and Telecommunication Engineering, College of Engineering🔹 Roles: Head of Dept. of Computer Science (M. Sc /M. Eng and Ph.D. Courses), Graduate School; Head of Dept. of Information Security (M. Sc /M. Eng and Ph.D. Courses), Graduate School

Dr. Kyung-Hyune Rhee for Best Researcher Award

Strengths for the Award:

  1. Extensive Academic and Professional Experience: Dr. Kyung-Hyune Rhee has an impressive academic background, with a Ph.D. in Mathematics from the Korea Advanced Institute of Science and Technology (KAIST), and a long-standing career in both academia and research. His role as a Full Professor at Pukyong National University, with responsibilities including leading graduate departments and programs, showcases his leadership and expertise in the field.
  2. Diverse International Exposure: Dr. Rhee has worked in several countries, including the USA, Australia, Japan, Korea, and the Philippines, which has broadened his research perspective and allowed him to collaborate with international scholars. His positions at prestigious institutions like the University of Tokyo, Kyushu University, and the University of Adelaide highlight his global recognition.
  3. Prolific Research Contributions: Dr. Rhee has a substantial number of publications, particularly in the fields of information security, cryptography, and machine learning. His research covers a wide range of topics, including blockchain, deep learning, vehicular cloud computing, and privacy-preserving protocols. The diversity of his research topics demonstrates his adaptability and relevance to current technological challenges.
  4. Leadership in Professional Societies: Dr. Rhee holds memberships in prominent professional societies such as IEEE Computer Society and the International Association for Cryptologic Research. His leadership roles, including Vice President of the Korean Multimedia Society and former President of the Korean Information Institute of Security and Cryptology, underline his influence and standing in the research community.
  5. Recognition and Editorial Responsibilities: His role as an associate editor for the Journal of KMMS and other editorial duties further establish his authority in the field, as he contributes to shaping the direction of academic research in multimedia and security.

Areas for Improvement:

  1. Recent Research Output: While Dr. Rhee’s research contributions are significant, there seems to be a concentration of publications from a few years ago. To remain highly competitive for the Best Researcher Award, a consistent stream of high-impact research in recent years would strengthen his profile.
  2. Focus on Emerging Trends: As the field of AI and security evolves, continuing to address emerging trends such as quantum computing security, AI ethics, and the intersection of AI with other technologies could enhance the relevance and impact of his research.
  3. Collaboration with Industry: Increasing collaboration with the industry could lead to practical applications of his research, offering solutions to real-world problems and potentially increasing the societal impact of his work.
✍️Publications Top Note :

Transparent and Accountable Training Data Sharing in Decentralized Machine Learning Systems
Computers, Materials and Continua, 2024
This open-access article discusses mechanisms for transparent and accountable data sharing in decentralized machine learning systems, addressing concerns of data integrity and privacy.

Towards Trustworthy Collaborative Healthcare Data Sharing
Proceedings of the 2023 IEEE International Conference on Bioinformatics and Biomedicine, 2023
This conference paper explores collaborative data sharing in healthcare using blockchain to ensure trustworthiness and security.

A Blockchain-Based Auditable Semi-Asynchronous Federated Learning for Heterogeneous Clients
IEEE Access, 2023
This open-access article presents a blockchain-based approach to federated learning, focusing on the challenges of heterogeneity in client data and asynchronous updates.

A Blockchain-Assisted Distributed Edge Intelligence for Privacy-Preserving Vehicular Networks
Computers, Materials and Continua, 2023
This paper addresses privacy concerns in vehicular networks using blockchain-assisted edge intelligence, contributing to the field of smart transportation.

A Blockchain-Based CCP Data Integrity Auditing Protocol for Smart HACCP
Lecture Notes in Electrical Engineering, 2023
This conference paper proposes a blockchain-based protocol for auditing data integrity in smart Hazard Analysis and Critical Control Points (HACCP) systems.

BPFL: Blockchain-Enabled Distributed Edge Cluster for Personalized Federated Learning
Lecture Notes in Electrical Engineering, 2023
This paper introduces BPFL, a framework that leverages blockchain for secure and personalized federated learning in distributed edge networks.

Personalized Federated Learning for Heterogeneous Data: A Distributed Edge Clustering Approach
Mathematical Biosciences and Engineering, 2023
This open-access article discusses a distributed edge clustering approach for personalized federated learning, addressing challenges posed by heterogeneous data sources.

Commentary: Integrated Blockchain-Deep Learning Approach for Analyzing the Electronic Health Records Recommender System
Frontiers in Public Health, 2023
This commentary explores the integration of blockchain and deep learning for analyzing electronic health records, emphasizing the importance of data security in healthcare.

A Joint Framework to Privacy-Preserving Edge Intelligence in Vehicular Networks
Lecture Notes in Computer Science, 2023
This conference paper presents a framework for privacy-preserving edge intelligence in vehicular networks, contributing to advancements in smart and secure transportation systems.

Conclusion:

Dr. Kyung-Hyune Rhee is a highly accomplished researcher with a robust track record in the field of information security and cryptography. His diverse academic background, extensive publication record, and leadership roles in professional societies make him a strong candidate for the Best Researcher Award. By continuing to innovate and publish cutting-edge research while expanding his collaborations, Dr. Rhee will maintain and enhance his position as a leader in his field.