Oliver Kornyo
The researcher's work integrates machine learning into various fields within physical sciences, focusing on enhancing energy systems' efficiency, improving network security, advancing data storage technologies, detecting and preventing malware, addressing smart grid vulnerabilities, enhancing cybersecurity, and fostering privacy solutions. Their studies aim to leverage AI/ML across these areas to solve complex challenges, from predicting solar PV energy impacts to developing secure smart grids and managing advanced adversaries with sophisticated algorithms.
Faculty Biography
Dr. Kornyo has over 14 years of experience in the energy sector and IoT Sensors Automation including Advanced Metering Infrastructure (AMI) Solutions and smart metering application management. He has developed state-of-the-art Database Management, software testing in the field of smart metering billing, data mining and simulation techniques in the Utility distribution applications.Currently a Lecturer in KNUST-Computer Science Department. Specialised in System Security and fraud detection techniques. A Lead IT Project Consultant. Was the CEO and a Project Manager with E.E.K Consults & Electricals Limited, in KUMASI. The project Manager for the installation of ‘’Mini- off grid Renewable Solar PROJECT for total A.M.I energy solution in Yeboahkrom and Onaa, a project under the German government and UK Funding respectively, a community in the Ejisu-Juaben Municipal in Ghana. A total monitoring network system, control energy usage from the user point (demand-side) and manage the Solar Energy generation (supply-side) on community households to avoid energy wastage. Oliver also developed the National net metering solution that is being implemented by Electricity Company of Ghana for fraud detection as the company moves towards pre-paid meters. Previously, Oliver worked for the Electricity Supply Company, Ghana and the Ashanti Region Database Administrator for GEDAP Projects. This included System Energy Management of smart metering End To-End solutions, training on Energy conservation and Tariff Calculation principles for energy billing system and application of Artificial Intelligence (AI) in Smart Metering Solutions, database Security Management, controlling billing records for management. He is part of the Ghana GOALS team, surveying, designing and installing the Mini grids with solar e-cooking in 4 Senior High Schools and one community. A research fellow at TCC-KNUST Ghana.
Advanced Data Storage Technologies
Advanced Malware Detection Techniques
Artificial Immune Systems Applications
Cybercrime and Law Enforcement Studies
Electric Vehicles and Infrastructure
Energy and Environment Impacts
Network Security and Intrusion Detection
Privacy-Preserving Technologies in Data
Risk and Safety Analysis
Smart Grid Security and Resilience
A Bibliometric-Scoping Review of Machine Learning and Metaheuristics in Optimization
Open AccessHybrid framework of differential privacy and secure multi-party computation for privacy-preserving entity resolution
Machine Learning-Assisted Innovative Charging Strategy for E-Mobility in Rural Communities Operated by Redundant Energy on Solar Pv Mini-Grids
Open AccessA Hybrid Integrated High Availability Cluster (Ihac) for Enhancing System Resilience and Addressing Persistent Cyber Threats
Open AccessEnhancing AMI network security with STI model: A mathematical perspective
Botnet attacks classification in AMI networks with recursive feature elimination (RFE) and machine learning algorithms
Machine learning of redundant energy of a solar PV Mini-grid system for cooking applications
Integration of Advanced Metering Infrastructure for Mini-Grid Solar PV Systems in Off-Grid Rural Communities (SoAMIRural)
Open AccessRsencarver": Enhancing File Carving Techniques with Error Correction Using the Reed Solomon Algorithm
Open AccessDeit-Mi: Advancing Malware Detection and Classification with Data-Efficient Image Transformers
Open AccessA Fraud Prevention and Secure Cognitive SIM Card Registration Model
Open AccessEnhancing Port Scans Attack Detection Using Principal Component Analysis and Machine Learning Algorithms
Intrusion Detection System Based on Artificial Immune System: A Review
Department of Computer Science
Kwame Nkrumah University of Science and Technology