Survey of privacy preserving federated tree-based learning
omodolapo-babalola
Professional Summary
Omodolapo is a PhD Researcher at the University of Glasgow. His research interest lies in the intersection of AI, security, privacy, federated learning and autonomy.
Education
PhD Computing Science
2024-01-08
University of Glasgow
MEng Computer Applied Technology
2018-08-01
2020-07-01
Changchun University of Science and Technology
BTech Computer Engineering
2011-01-10
2015-12-15
Ladoke Akintola University of Technology
Interests
Federated Learning
IT/OT/IoT Security
Privacy
📚 My Research
I am a PhD research student in Computing Science at the University of Glasgow, where I am deepening my expertise in secure, private, and reliable ubiquitous connectivity. Previously, I served as a 5G Optimization Team Leader at Huawei, where I developed strong expertise in Radio Frequency and 4G/5G New Radio technologies to help advance mobile network capabilities.
My experience at Huawei strengthened my ability to contribute to the evolution of global communication infrastructure by improving network performance and reliability. Guided by a commitment to excellence and a strategic approach to problem-solving, I aim to shape the future of secure connectivity through rigorous research and practical application.
I welcome opportunities to connect and collaborate.😃
Featured Publications
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1 min read
FedRand: A Federated Random Forest Learning Technique for Anomaly Detection in IoT Networks
omodolapo-babalola
Recent Publications
(2026).
Survey of privacy preserving federated tree-based learning.
Artificial Intelligence Review (Springer Nature).
(2025).
FedRand: A Federated Random Forest Learning Technique for Anomaly Detection in IoT Networks.
2025 IEEE 24th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom).