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Andrew Selasi Agbemenu

Computer Engineering

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About

Andrew Selasi Agbemenu has been a lecturer with the Department of Computer Engineering since 2012. He received his BSc. Degree in Electrical/Electronic Engineering, MSc. in Telecommunication Engineering and his PhD in Computer Engineering from the Kwame Nkrumah Univerisity of Science and Technology.Before joining the department, he worked as a System programmer with the University Information Technology Services, where his core responsibilities were setting up and deploying core open-source technologies for user and email management. He was also responsible for configuring and deploying switching, routing and security solutions.Currently, his research interests are applying AI, Blockchain, and IoT in traceability systems and analogue and mixed-signal design, concentrating on low-power design and data converters. He taught various courses, including VLSI, Fault Diagnosis and Failure Tolerance, Linear Electronic Circuits, Semiconductor Devices and Basic Electronics.

Research Summary

(inferred from publications by AI)

The researcher has made significant contributions across a diverse range of research domains, with a focus on integrating advanced technologies and methodologies. Their work spans key areas such as blockchain security, smart grid optimization, AI-driven solutions in cancer detection, and innovative image processing techniques. Additionally, the researcher explores advanced photolithography methods, network security strategies, diagnostics for health conditions like diabetic foot ulcers, and applications of artificial intelligence in various fields. Their research is characterized by a commitment to enhancing technological efficiency, integrating diverse methodologies across different domains, and addressing both theoretical and applied challenges in technology development.

Research Themes

All Papers

Blockchain interoperability: the state of heterogenous blockchain‐to‐blockchain communication(2023)
Assessing blockchain and IoT technologies for agricultural food supply chains in Africa: A feasibility analysis(2024)
Adaptive Storage Optimization Scheme for Blockchain-IIoT Applications Using Deep Reinforcement Learning(2022)
A Survey on Network Optimization Techniques for Blockchain Systems(2022)
An Overview of Technologies for Improving Storage Efficiency in Blockchain-Based IIoT Applications(2022)
Optimising peer-to-peer topology for blockchain-based industrial internet of things networks using particle swarm optimisation(2025)
A storage-efficient learned indexing for blockchain systems using a sliding window search enhanced online gradient descent(2024)
Optimizing Blockchain Querying: A Comprehensive Review of Techniques, Challenges, and Future Directions(2024)
A Framework for Full Decentralization in Blockchain Interoperability(2024)
Artificial intelligence-based strategies for sustainable energy planning and electricity demand estimation: A systematic review(2024)
An artificial intelligence‐based non‐intrusive load monitoring of energy consumption in an electrical energy system using a modified K‐Nearest Neighbour algorithm(2024)
An Implementation of an optimized dual-axis solar tracking algorithm for concentrating solar power plants deployment(2022)
Software-Defined Networks for Optical Networks Using Flexible Orchestration: Advances, Challenges, and Opportunities(2022)
Flexible open network operating system architecture for implementing higher scalability using disaggregated software‐defined optical networking(2023)
Software-Defined Networks for Optical Networks using Flexible Orchestration : Advances, Challenges and Opportunities(2022)
A new research agenda for African generative AI(2023)
Diversity in Stable GANs: A Systematic Review of Mode Collapse Mitigation Strategies(2025)
Attn‐DeCGAN: A Diversity‐Enhanced CycleGAN With Attention for High‐Fidelity Medical Image Translation(2025)
Design of a fully integrated VHF CP‐PLL frequency synthesizer with an all‐digital defect‐oriented built‐in self‐test(2022)
Design of a Fully Integrated VHF CP-PLL Frequency Synthesizer with an All-Digital Defect-Oriented Built-In Self-Test.(2022)
Predictive AI Maintenance of Distribution Oil‐Immersed Transformer via Multimodal Data Fusion: A New Dynamic Multiscale Attention CNN‐LSTM Anomaly Detection Model for Industrial Energy Management(2025)
Multi‐Wound Classification: Exploring Image Enhancement and Deep Learning Techniques(2025)
Deep learning for efficient high-resolution image processing: A systematic review(2025)
Author response for "Attn-DeCGAN: A Diversity-Enhanced CycleGAN With Attention for High-Fidelity Medical Image Translation"(2025)
A COMPARATIVE STUDY OF COMMON EDGE DETECTION OPERATORS IN DIGITAL IMAGE PROCESSING(2021)
AfroPALM - Afrocentric palm oil adulteration learning models: An end-to-end deep learning approach for detection of palm oil adulteration(2024)
Afropalm - Afrocentric Palm Oil Adulteration Learning Models: An End-to-End Deep Learning Approach for Detection of Palm Oil Adulteration in West Africa(2024)
On the design and implementation of efficient antennas for high frequency‐radio frequency identification read/write devices(2021)
On the Design and Implementation of Efficient Antennas for HF RFID Readers(2020)
BAG2 Assisted Hierarchical Analog Layout Synthesis for Planar Technologies(2023)
BAG2-assisted analog layout synthesis for TSMC 65 nm and GPDK 45 nm(2024)
Drowsing Driver Alert System for Commercial Vehicles(2019)
Enhancing speech recognition through diverse shared features accent classification(2025)
Author response for "Diversity in Stable GANs: A Systematic Review of Mode Collapse Mitigation Strategies"(2025)
CDBi‐LSTM: A Hybrid Deep Learning Model With Attention‐Based Fusion for Efficient DDoS Detection in IoT Environments(2025)

Collaboration Network

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About This Profile

This profile is generated from publicly available publication metadata and is intended for research discovery purposes. Themes, summaries, and trajectories are inferred computationally and may not capture the full scope of the lecturer's work. For authoritative information, please refer to the official KNUST profile.