Dominic Asamoah

Computer Science

About

Dr. Dominic Asamoah received his B.Sc. (Hons) degree in Computer Science and MPhil Computer Science in 1986, and 2010 respectively. He Joined the department of Computer Science in 2002. He completed his PhD in Computer Science from KNUST, Ghana, in 2017 with specialization in Computer Visions. He is currently a SENIOR LECTURER at the Department of Computer Science, KNUST. Prior to his appointment as Lecturer at KNUST, Dr. Dominic Asamoah worked as Systems Analyst and Programmer in a lot of Computer Firms both home and abroad. He was a consultant. In the field of computing and security. Dr. Asamoah also worked as Systems Administrator and Business Analyst with AMMES INT. in UK. After joining KNUST, he studied Advance Computing in South West University – Nanjing in China. Dr. Dominic Asamoah worked as a Computer Consultant in the corporate for about sixteen years before joining the academia. His areas of research interest include Computer Visions, Computer and Data Security, Cloud Computing, Imaging, Artificial Intelligence, Computer Architecture and, Computer Programming and Algorithm Development.

Research Summary

(inferred from publications by AI)

The researcher has focused on integrating advanced analytical techniques across diverse domains such as healthcare, education, logistics, and telecommunications, aiming to enhance data-driven solutions for real-world challenges. Through innovative approaches that combine signal processing, optimization algorithms, and AI/ML, the work contributes significantly to areas like security, ergonomics, sleep disorders, and social impact assessments.

Research Themes

All (21 Papers)

Physical Sciences (14 Papers)

Social Sciences (7 Papers)

All Papers

Measuring the Performance of Image Contrast Enhancement Technique(2018)

Assessment of Data Quality on Expanded Programme on Immunization in Ghana: The Case of New Juaben Municipality(2015)

Feature representation in analysing childhood vaccination defaulter risk predictors: A scoping review of studies in low-resource settings(2025)

Advancing Knowledge on Machine Learning Algorithms for Predicting Childhood Vaccination Defaulters in Ghana: A Comparative Performance Analysis(2025)

Business Decision Support System based on Sentiment Analysis(2019)

Enhancing Port Scans Attack Detection Using Principal Component Analysis and Machine Learning Algorithms(2022)

Meta-Heuristics Approach to Knapsack Problem in Memory Management(2019)

Achieving Confidentiality in Electronic Health Records using Cloud Systems(2018)

Measuring the Severity of Fungi Caused Disease on Leaves using Triangular Thresholding Method(2017)

Knapsack problem: A case study of garden city radio (GCR), Kumasi, Ghana(2011)

Optimizing Memory using Knapsack Algorithm(2017)

Establishing the Blink Cycle of the Eye using OTSU Method and Gaussian Filter(2017)

Intelligent Vehicular Traffic Light Control using Hidden Markov Model(2017)

Implementing Lock Free Data Structure for Shared-Memory Systems using Linked List(2017)

Human Fatigue Characterization and Detection Using the Eyelid State and Kalman Filter(2019)

Evaluating the Impact of Full Virtualized High- Performance Computing Platform on Large Scale Scientific Data using Quantum Espresso(2020)

Kalman Filter As A Threshold In Estimating The Level Of Fatigue Based On Eyelid Movement(2016)

A Novel Approach to Pre-Impact Measurement from Impact Investing Using Random Forest and Deep Neural Networks(2021)

Error Detection and Correction in Wireless Sensor Networks Using Enhanced Reverse Conversion Algorithm in Healthcare Delivery System(2022)

Twi Speech Processing: Techniques and Applications(2024)

Prevention of student attrition: a data-backed approach to school counselling using Delphi technique and multiple classification algorithms(2025)

Collaboration Network

fb410575-4c58-4343-9954-57ae1760d322

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.

Back to Search