Academic Directory

This researcher has made significant contributions to the theoretical foundations of computing by exploring the interplay between quantum algorithms, human-AI collaboration dynamics, and machine learning convergence with biological systems. Their work bridges computational complexity theory with applications in network science, biology, and social networks, advancing our understanding of how computational methods can be applied across diverse domains without listing specific papers or themes.

Emotional Intelligence & Performance: Research examining the impact of emotional intelligence on academic performance and its relationship with factors such as study habits and motivation. Obesity & Diet: A comparative study analyzing dietary patterns and energy intake levels in urban Ghanaian neighborhoods using self-reported data on food consumption. COVID-19 epidemiological studies: An investigation into COVID-19's spread across West Africa, focusing on the use of smooth transition autoregressive models to analyze temporal changes in cases. Vehicle Emissions & Fuel Efficiency: A statistical analysis of fuel efficiency metrics among vehicles, highlighting trends and contributing factors such as engine type and driving conditions. Agricultural Innovations & Practices: An application of discriminant analysis to identify which inputs or practices are most effective for agricultural productivity in Ghana. Transportation Planning & Optimization: Various optimization techniques explored, including clustering studies on paratransit routes and algorithms for route planning, aiming to improve traffic efficiency. Behavioral Health & Interventions: A study using hierarchical models to predict outcomes related to maternal and child health, focusing on factors influencing birth outcomes in Nigeria. Global Maternal & Child Health: An analysis of risk factors that contribute to maternal mortality in vulnerable populations using machine learning techniques. Malaria Research & Control: Modeling malarity prevalence patterns in West Africa using Bayesian models to assess disease transmission dynamics. Statistical Inference & Risk Analysis: A comparative study of estimators used for calculating coronary heart disease risk, evaluating their performance and accuracy. Traffic Safety & Footage: An exploration of pedestrian footbridge usage patterns as a proxy for traffic safety, focusing on factors influencing foot traffic. Noise Management & Regulations: A systematic review of noise management practices in urban areas, using statistical models to assess the effectiveness of existing regulations against noise-induced health risks. Urban Transport & Accessibility: Research into paratransit route optimization and clustering studies to enhance accessibility and efficiency among urban residents. Neonatal Skin Health & Health Outcomes: An investigation into the role of dietary factors in neonate health, focusing on conditions such as iron deficiency in pregnant women. Psychometric Testing & Interventions: A study using discriminant function applications to predict neonatal outcomes, particularly low birth weight neonates, employing a probabilistic framework to assess effectiveness. Forest Ecosystems Research: An analysis of vegetation patterns in the Abokutah region using PCA/SVD methods and robust models for spatial analysis. Hermeneutics & Narrative Identity: A qualitative study examining the influences on low birth weight neonatal outcomes through hermeneutic analysis of narratives, particularly those involving hermeneutics (interpretation) and narrative identity in Ghanaian society. Statistical Methods & Inference: An exploration of the sensitivity and bias of quadratic discriminant functions when used for classification purposes, evaluating their performance in various contexts. Face Recognition & Expression Analysis: A statistical investigation into facial expression patterns under varying conditions using robust methods to assess the accuracy of these models. Global Health & Education Research: A comparative study modeling maternal mortality incidence across different regions using machine learning techniques. Hermeneutics & Identity: Further qualitative studies examining low birth weight neonatal outcomes, focusing on how hermeneutic principles and narrative identity influence such health outcomes in Ghana. Statistical Analysis & Pattern Recognition: An investigation into the sensitivity of quadratic discriminant functions when applied to predict maternal mortality incidence using machine learning methods. Hemistics & Identity: A qualitative study analyzing low birth weight neonatal outcomes from a hermeneutic perspective, focusing on narrative identity and interpretive processes in African communities. Social Issues Research: A comparative analysis of gait speed and physical activity factors among urban populations in Nigeria, identifying how these factors influence health-related outcomes. Aging & Diet Studies: An investigation into the relationship between dietary patterns and age-specific energy needs, particularly regarding iron consumption rates in women as a key factor influencing maternal mortality risk.

This researcher's work focuses on developing integrative theories that combine mathematical modeling with experimental data from cell biology experiments. Their research integrates continuum mechanics, agent-based models, and game theory approaches to explore mechanisms governing cellular behavior in complex biological systems, such as those involving neurons or immune responses. The overarching goal is to understand how cancer cells acquire advantages through mutations and interactions with other cells, employing a multi-scale analysis framework that bridges mathematical theory with experimental observations to inform both theoretical advancements and practical therapeutic strategies.

The researcher's work focuses on integrating complex systems across various domains, including financial markets, economic growth dynamics, and demography, employing advanced mathematical models to understand their interplay in shaping modern societal behaviors.

This research explores how consumer price index (CPI) and exchange rates in Ghana influence market dynamics and volatility, employing GARCH models to analyze their interactions. It contributes to the understanding of how different economic indicators contribute to overall market volatility, offering insights into domestic market behavior and providing a broader context for analyzing other markets.

Research focuses on integrating advanced methodologies across various biological, social, and technological domains to address health and environmental challenges in African regions, employing innovative solutions that span from water fluorides to COVID-19 risk assessments.

The researcher conducts interdisciplinary research spanning environmental science, public health, and food safety. Their work encompasses water quality assessment, waste management, hydrological forecasting, climate change studies, medical conditions like malarials, urban heat island mitigation, and statistical methodologies. They employ innovative tools such as AI for hydrological modeling and machine learning algorithms for academic performance prediction to address complex issues in these fields.

The researcher has conducted extensive work across diverse fields, integrating advanced methodologies to address challenges in fraud detection (machine learning), water quality assessment, Hepatitis B virus studies, COVID-19 epidemiology, eating disorders, and neonatal respiratory health.

The researcher investigates the impact of blended learning technology, particularly online and offline platforms like IBOX, on student outcomes in social sciences education.

The researcher's work is centered around integrating advanced statistical methodologies and theoretical frameworks to address challenges in multiple disciplines. Key areas include: 1. **Meta-Analysis and Systematic Reviews**: Utilizing sophisticated statistical techniques like meta-analysis to synthesize findings from various studies on effect-size estimates, with a focus on normally and contaminated normals. 2. **Global Trade and Economics**: Investigating the impact of Foreign Direct Investment (FDI) in Ghana's economic growth through optimal control models for age-structured Malaria models, incorporating different factors. 3. **Mathematical and Theoretical Epidemiology**: Developing and analyzing age-structured Malaria models across different demographics to understand disease dynamics and transmission. 4. **Education Technology and Assessment**: Exploring online and blended learning methodologies, particularly in the Kwame Nkrumah University of Science and Technology, using machine learning classifiers for water access assessments. 5. **Epidemiological Studies**: Conducting systematic reviews on determinants of low birth weight in specific regions to address health inequalities. 6. **Advanced Statistical Methods and Models**: Employing Bayesian approaches and copulas under data perturbations in financial applications, as well as robust adaptive schemes for longitudinal data analysis. 7. **International Business and FDI**: Analyzing the impact of Foreign Direct Investment on Ghana’s economic growth, focusing on global trends and regional developments. 8. **Sustainable Supply Chain Management**: Optimizing water access through sustainable supply chain management strategies in a Ghanaian university setting. 9. **Economic Theories**: Enhancing economic growth models by optimizing under various production functions to ensure robustness and accuracy. 10. **International Business Contexts**: Focusing on the FDI impact on local economies, including the study of Foreign Direct Investment's role in global trade patterns. The research aims to bridge methodologies across diverse fields, using advanced statistical tools to address complex issues in public health, education, and economics, leveraging technology for enhanced learning and sustainability efforts.

The researcher has focused on developing robust models for assessing and mitigating systemic risks in financial systems, particularly in microfinance and financial inclusion contexts. Their work aims to enhance predictive capabilities for default risk estimation in microfinance institutions while advancing volatility modeling techniques that can capture complex dynamics in financial markets.