Kate Takyi
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.
Faculty Biography
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.
Anomaly Detection Techniques and Applications
Augmented Reality Applications
Blockchain Technology Applications and Security
COVID-19 diagnosis using AI
Hand Gesture Recognition Systems
Identification and Quantification in Food
Imbalanced Data Classification Techniques
Internet Traffic Analysis and Secure E-voting
Network Security and Intrusion Detection
Sentiment Analysis and Opinion Mining
Smart Agriculture and AI
Software Engineering Research
MeatScan: An image dataset for machine learning-based classification of fresh and spoiled cow meat
Open AccessAdvanced Mobile Money Fraud Detection Using CNN-BiLSTM and Optimized SGD with Momentum
Open AccessAfriSign: African sign languages machine translation
Open AccessAn improved man-in-the-middle (MITM) attack detections using convolutional neural networks
Open AccessPneumonia Detection on Chest X-ray Using Deep Convolutional Neural Networks
Sentiment analysis and classification of Ghanaian football tweets from the 2022 FIFA World Cup
Open AccessThe use of knapsack 0/1 in prioritizing software requirements and Markov chain to predict software success
Cocoa beans classification using enhanced image feature extraction techniques and a regularized Artificial Neural Network model
A Hybrid Model for Anomaly Detection in Smart Building
Open AccessAdoption of Blockchain Technology to Streamline the Claims Settlement in the Health Insurance Industry in Ghana
Open AccessAugmented Reality Indoor Navigation with Computer Vision
Open AccessLightGBM-RF: A Hybrid Model for Anomaly Detection in Smart Building
Real-time application clustering in wide area networks
An Improved QoS Aware Clustering Approach for Network Traffic Classification
A Semi-Supervised QoS-Aware Classification for Wide Area Networks with Limited Resources
Open AccessTable of contents
Open AccessClustering Techniques for Traffic Classification: A Comprehensive Review
Open AccessDepartment of Computer Science
Kwame Nkrumah University of Science and Technology