Kate Takyi

Computer Science

About

Kate Takyi attained her BSc. Degree in Computer Science from Kwame Nkrumah University of Science and Technology, Ghana in 2009 and worked as Network Support Officer at Noble Gold Bibiani Limited from 2011 to 2013. She attained her Master’s Degree in Network Technology and Management (MSc) from Amity University Gurgaon, Haryana - India in 2016. She has worked on a project “Modular Framework for network security” and proposed a model for enhancing security for organizations with several branch offices. She attained her PhD. Degree at Lovely Professional University, Punjab – India in Computer Applications. She is currently a lecturer in the Computer Science Department of Kwame Nkrumah University of Science and Technology.She is intrested in collaborative research in fields of STEM educaction. Her research areas of interest include Machine Learning, Data Science Wireless Networks,Internet of Things, Network Communications, Network traffic Classification, Network security, and Network Management. She supervises a lot of students both at the undergraduate and postgraduate levels in all areas and categories mentioned above. She is a member of Ghana Science Association and Women in Science, Technology, Engineering and Mathematics (Wistem). She personally mentors students both in and outside of Ghana.

Research Summary

(inferred from publications by AI)

The researcher's work centers on advancing AI and machine learning applications across diverse domains, employing innovative techniques such as enhanced feature extraction, anomaly detection, network security, sentiment analysis, augmented reality, and biological imaging. Their research integrates methodologies like deep learning models, graph-based approaches, optimization algorithms, and bioinformatics to address challenges in smart agriculture, network security, software engineering, healthcare, biology, and public health.

Research Themes

All (16 Papers)

Life Sciences (2 Papers)

Physical Sciences (13 Papers)

Health Sciences (1 Papers)

All Papers

Cocoa beans classification using enhanced image feature extraction techniques and a regularized Artificial Neural Network model(2023)

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

A Semi-Supervised QoS-Aware Classification for Wide Area Networks with Limited Resources(2019)

Real-time application clustering in wide area networks(2020)

An Improved QoS Aware Clustering Approach for Network Traffic Classification(2020)

The use of knapsack 0/1 in prioritizing software requirements and Markov chain to predict software success(2023)

Clustering Techniques for Traffic Classification: A Comprehensive Review(2018)

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

Sentiment analysis and classification of Ghanaian football tweets from the 2022 FIFA World Cup(2024)

Augmented Reality Indoor Navigation with Computer Vision(2022)

LightGBM-RF: A Hybrid Model for Anomaly Detection in Smart Building(2022)

A Hybrid Model for Anomaly Detection in Smart Building(2023)

Pneumonia Detection on Chest X-ray Using Deep Convolutional Neural Networks(2024)

AfriSign: African sign languages machine translation(2025)

Advanced Mobile Money Fraud Detection Using CNN-BiLSTM and Optimized SGD with Momentum(2025)

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

Collaboration Network

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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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