publication
Paper Accepted at IEEE AFRICON 2024
Sep 15, 2024
Our work on 'Energy-Efficient Edge Computing for Agricultural IoT' has been accepted for presentation at IEEE AFRICON 2024 in Nairobi, Kenya.
37
Publications
8
h-index
2
Active Grants
4
Lab Members
About Me
Passionate About Engineering Education & Research
I am an Associate Professor of Computer Engineering at the University of Uyo, Nigeria. My research focuses on developing practical solutions at the intersection of embedded systems, Internet of Things (IoT), and machine learning applications for real-world challenges. With over a decade of experience in academia and research, I lead projects that bridge theoretical foundations with practical implementations, particularly in areas relevant to developing economies.
I am committed to training the next generation of engineers who will drive technological innovation in Africa. My teaching philosophy emphasizes hands-on learning, practical problem-solving, and research-based education.
15+
Years in Academia
45+
Publications
20+
Students Mentored
5+
Research Grants
Research Interests
Exploring the intersection of hardware and software to create intelligent, efficient systems.
Artificial Intelligence
Developing machine learning and deep learning models for various applications including cybersecurity threat detection, healthcare diagnostics, and predictive analytics.
Cybersecurity
Research on detecting and mitigating cybersecurity threats in IoT networks, mobile payment systems, and cloud computing environments using hybrid ML approaches.
Cyber-Physical Systems
Investigating the security and efficiency of cyber-physical systems, including smart grids, embedded systems, and Industry 4.0 applications.
Software Engineering
Developing robust software solutions for enterprise applications, e-procurement systems, identity management, and workflow automation in institutional settings.
Featured Publications
Selected research contributions in embedded systems, IoT, and machine learning.
Hybrid CNN–BiLSTM–DNN Approach for Detecting Cybersecurity Threats in IoT Networks
BA Agbor, BUA Stephen, P Asuquo, UO Luke, V Anaga
Computers, 2025
This paper presents a hybrid deep learning approach combining CNN, BiLSTM, and DNN for detecting cybersecurity threats in IoT networks with high accuracy.
DOI22 citations
Customer churn prediction using machine learning models
G Sam, P Asuquo, B Stephen
Journal of Engineering Research and Reports, 2024
A comprehensive study on predicting customer churn using various machine learning models, providing insights for business retention strategies.
39 citations
Active Projects
Current research initiatives and funded projects.
Hybrid Deep Learning for IoT Cybersecurity Threat Detection
TETFundTF/2023/001
2023 — 2026
Principal Investigator
Developing CNN-BiLSTM-DNN hybrid models for real-time detection of cybersecurity threats in IoT networks, with applications in smart homes and industrial IoT.
Green AI for Healthcare Diagnostics
University GrantUNIUYO/RG/2024/012
2024 — 2025
Principal Investigator
Applying energy-efficient AI model selection strategies for computer-aided detection of diseases including Mpox, breast cancer, and metabolic conditions.
Secure Mobile Payment Systems for Financial Inclusion
NITDANG/ICT/2024/045
2024 — 2026
Co-PI
Analyzing vulnerabilities and developing secure frameworks for mobile payment applications in countries with low financial inclusion.
Recent News
grant
TETFund Research Grant Awarded
Jul 20, 2024
Received TETFund Institutional Based Research grant for the Smart Agricultural Monitoring project, supporting research in precision agriculture.
talk
Keynote at National Engineering Conference
May 10, 2024
Delivered keynote address on 'The Future of IoT in Nigerian Agriculture' at the Nigerian Society of Engineers annual conference.
Interested in Collaboration?
I welcome opportunities for research collaboration, graduate student supervision, and industry partnerships. Let's work together to solve real-world engineering challenges.