Mbasa Joaquim Molo | System | Best Researcher Award

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Mr. Mbasa Joaquim Molo | System | Best Researcher Award

Mr. Mbasa Joaquim Molo | System | PhD Student at University of Pisa | Italy

Mr. Mbasa Joaquim Molo is a highly accomplished Ph.D. student at the University of Pisa, Italy, with extensive expertise in Computer Science, particularly in cloud computing, federated learning, edge AI, and IoT-based anomaly detection. He has earned recognition for his rigorous research and international collaborations, working on projects that span healthcare ecosystems, smart infrastructure, and AI-driven monitoring systems. His educational background includes advanced studies in computer science with hands-on experience in distributed systems, AI algorithms, and machine learning techniques. Professionally, Mr. Molo has contributed to multiple research projects with global teams, demonstrating strong analytical skills, programming proficiency, and innovative problem-solving capabilities. His research interests encompass knowledge distillation, decentralized edge learning, smart greenhouse monitoring systems, and federated genomics infrastructures for precision medicine. He possesses significant research skills in AI model development, anomaly detection, cloud resource management, data analysis, and comparative evaluation of learning strategies, which have been applied in high-impact international projects. Mr. Molo’s work has resulted in several high-quality publications in reputed journals and conferences, reflecting his dedication to advancing the field. His contributions have been acknowledged through citations, highlighting the impact and relevance of his research. Additionally, he holds memberships in prestigious professional organizations such as IEEE and ACM, where he actively participates in community initiatives, mentoring, and collaborative research. Mr. Molo has also received awards and recognition for his innovative contributions in AI, cloud computing, and smart systems research, demonstrating his leadership potential and commitment to excellence. He continues to explore novel approaches to integrating edge AI and federated learning into practical applications, aiming to enhance system efficiency, security, and scalability. His demonstrated ability to lead research projects, publish in high-impact venues, and collaborate internationally underscores his potential as a future leader in computer science research. In conclusion, Mr. Mbasa Joaquim Molo represents an exemplary researcher whose academic achievements, technical expertise, and professional contributions position him as a significant contributor to advancing AI, cloud computing, and intelligent system technologies on a global scale.

Academic Profile: ORCID | Scopus | Google Scholar

Featured Publications:

  1. Molo, M. J., Badejo, J. A., Adetiba, E., Nzanzu, V. P., Noma-Osaghae, E., & Others. (2021). A review of evolutionary trends in cloud computing and applications to the healthcare ecosystem. Applied Computational Intelligence and Soft Computing. 32 citations.

  2. Adetiba, E., Akanle, M., Akande, V., Badejo, J., Nzanzu, V. P., & Molo, M. J. (2021). FEDGEN testbed: A federated genomics private cloud infrastructure for precision medicine and artificial intelligence research. International Conference on Informatics and Intelligent Applications, 78–91. 13 citations.

  3. Okokpujie, K., Kennedy, G. C., Nzanzu, V. P., Molo, M. J., Adetiba, E., & Badejo, J. (2021). Anomaly-based intrusion detection for a vehicle CAN bus: A case for Hyundai Avante CN7. Journal of Southwest Jiaotong University, 56(5), 144–156. 10 citations.

  4. Nzanzu, V. P., Adetiba, E., Badejo, J. A., Molo, M. J., Akanle, M. B., & Mughole, K. D. (2022). Fedargos-v1: A monitoring architecture for federated cloud computing infrastructures. IEEE Access, 10, 133557–133573. 9 citations.

  5. Molo, M. J., Carlini, E., Ciampi, L., Gennaro, C., & Vadicamo, L. (2024). Teacher-student models for AI vision at the edge: A car parking case study. Proceedings, 508–515. 8 citations.