Kwabena Owusu-Agyemang

Computer Science

About

Kwabena Owusu-Agyemang is a Lecturer at the Department of Computer Science with research and professional experience in machine learning and blockchain technology. He obtained his Doctoral degree in Software Engineering with specialization in Machine Learning and master’s degree in Information Technology Management from Coventry University.As an accomplished educator and machine learning engineer, He possess a strong drive to utilize state-of-the-art technologies in order to advance research and foster innovation. His proficiency lies in the application of machine learning algorithms and techniques to tackle intricate problems across various domains. He has demonstrated expertise in creating and implementing data-driven solutions that optimize performance and improve decision-making processes. He is dedicated to creating a collaborative and engaging learning environment that prioritizes academic excellence and real-world application. Throughout His career, He has an established record of publishing influential research papers, delivering impactful lectures, and leading successful interdisciplinary projects. He excels at effectively communicating complex concepts to students, colleagues, and professionals in the industry.Despite his many achievements, Kwabena remains humble and dedicated to his work. He continues to be an active researcher and is always looking for new ways to advance the field of machine learning and improve the understanding of the models and its application in the industry.Email Address : kwabenaoa@knust.edu.gh

Research Summary

(inferred from publications by AI)

The researcher's work centers on advancing privacy-preserving technologies across diverse domains, integrating deep learning with privacy techniques to address challenges in distributed computing, AI for cancer detection, cybersecurity, brain tumor classification, network security, smart grid resilience, and food science. Contributions include enhanced robustness against adversarial attacks using advanced neural networks and deep learning frameworks.

Research Themes

All (23 Papers)

Physical Sciences (18 Papers)

Life Sciences (5 Papers)

All Papers

MSCryptoNet: Multi-Scheme Privacy-Preserving Deep Learning in Cloud Computing(2019)

Privacy preservation in Distributed Deep Learning: A survey on Distributed Deep Learning, privacy preservation techniques used and interesting research directions(2021)

MSDP: multi-scheme privacy-preserving deep learning via differential privacy(2021)

Guaranteed distributed machine learning: Privacy-preserving empirical risk minimization(2021)

Insuring against the perils in distributed learning: privacy-preserving empirical risk minimization(2021)

<scp>DHS‐CapsNet</scp>: Dual horizontal squash capsule networks for lung and colon cancer classification from whole slide histopathological images(2021)

Employing transfer learning for breast cancer detection using deep learning models(2025)

Botnet attacks classification in AMI networks with recursive feature elimination (RFE) and machine learning algorithms(2023)

An improved man-in-the-middle (MITM) attack detections using convolutional neural networks(2024)

A bilateral filtering-based image enhancement for Alzheimer disease classification using CNN(2024)

MLAF-CapsNet: Multi-lane atrous feature fusion capsule network with contrast limited adaptive histogram equalization for brain tumor classification from MRI images(2021)

A Neural Architecture Search CNN for Alzheimer’s Disease Classification(2024)

Enhancing Brain Tumor Segmentation with Transformer-Based Models: A Study on the BraTS 2020 Dataset(2025)

Cofopose: Conditional 2D Pose Estimation with Transformers(2022)

Multimodal Brain Tumor Segmentation Using Transformer and UNET(2023)

Adoption of Blockchain Technology to Streamline the Claims Settlement in the Health Insurance Industry in Ghana(2023)

Enhancing AMI network security with STI model: A mathematical perspective(2024)

Multi-Class Triplet Loss With Gaussian Noise for Adversarial Robustness(2020)

An Evaluation of the Effectiveness of the MCA Rural Banks Computerization and Interconnectivity Project Implementation: A Comparative Case Study of Amanano and Odotobri Rural Bank Limited(2015)

An evaluation of the effectiveness of the MCA rural banks computerization and interconnectivity project implementation: a comparative case study of two rural banks in Ghana(2015)

Rsencarver": Enhancing File Carving Techniques with Error Correction Using the Reed Solomon Algorithm(2023)

Deit-Mi: Advancing Malware Detection and Classification with Data-Efficient Image Transformers(2023)

MeatScan: An image dataset for machine learning-based classification of fresh and spoiled cow meat(2025)

Collaboration Network

18be8ecb-d808-49fa-9e5c-47c2555a0170

Research Collaboration Map

Collaboration Frequency

Less

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.

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