Rose-Mary Owusuaa Mensah Gyening

Computer Science

About

Rose-Mary Owusuaa Mensah Gyening is a lecturer at the Department of Computer Science. She holds BSc(Hons) in Computer Science from KNUST, MSc Computer Science from Rheinische Friedrich-Wilhelms-Universität Bonn. She holds PhD Computer Science from KNUST. She has keen interest in machine learning, robotics and IoT, human Computer Interaction and Cybersecurity.From 2016 to July 2020, She was a lecturer at the Department of Computer Science, Garden City University College where she taught courses such as Computer Security and Cryptography, Datacenter Administration, Distributed Computing, Fundamentals of Computing, Computer Professional Ethics and Database Management Systems. She also served as the ICT Coordinator, Garden City University College, Kumasi and was responsible for the introduction of new IT related courses and supervision of the teaching of CCNA and computer proficiency programs.She has supervised several undergraduate theses and now supervising masters students as well. Due to her passion for robotics and the Internet of things, she has undertaken many projects and supervised students in this area. Notable among them are: RoCA, a humanoid assistive technology for children with Autism, IoT Based Soil Moisture, Temperature and Humidity Measuring System for Farmers, Smart home, Automatic Water Pumping Systems, Smart Weather Monitoring System and Solar Tracking System.She is currently a member of the following professional bodies:

Research Summary

(inferred from publications by AI)

The researcher has conducted extensive work across multiple domains, blending advanced AI techniques with applications in life sciences and physical sciences. Their focus is on integrating innovative solutions to address complex real-world challenges, from advancing agricultural innovations using smart technologies to developing robust data security frameworks for secure data handling. The researcher's work also extends into the realm of healthcare, employing cutting-edge AI for disease detection and management, as well as improving environmental monitoring through anomaly detection systems and predictive analytics. Their overarching theme is the intersection of AI across diverse fields to address challenges in agriculture, health, environment, and social sciences, showcasing a commitment to practical solutions that enhance technology's impact on society.

Research Themes

All (22 Papers)

Life Sciences (4 Papers)

Physical Sciences (14 Papers)

Health Sciences (4 Papers)

All Papers

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

Heterogeneous signcryption with proxy re-encryption and its application in EHR systems(2022)

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

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

Preliminary Observations from Interactions among Ghanaian Autistic Children and Rosye, a Humanoid Robotic Assistive Technology(2018)

Social Robotic Systems in Autism Therapy: Survey and Design Considerations(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)

Stance Prediction and Analysis of Twitter data : A case study of Ghana 2020 Presidential Elections(2023)

Impact of Climate Change on Groundwater Level Changes: An Evaluation Based on Deep Neural Networks(2025)

Machine Learning Impact Assessment Of Climate Factors On Daily Covid-19 Cases(2022)

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

Augmented Reality Indoor Navigation with Computer Vision(2022)

MACHINE LEARNING IMPACT ASSESSMENT OF CLIMATE FACTORS ON DAILY COVID-19 CASES(2022)

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

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

Deep learning based capsule networks for breast cancer classification using ultrasound images(2024)

Deep Neural Networks for Skin Cancer Classification: Analysis of Melanoma Cancer Data(2025)

AfriSign: African sign languages machine translation(2025)

Trends and advances in image-based mosquito identification and classification using machine learning models: A systematic review(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

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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.

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