Academic Directory

The researcher's work is centered on integrating computational modeling techniques across various scales to advance our understanding of cancer biology. Their approach combines genomics with insights from evolutionary and neurobiological studies. They employ multiscale modeling to simulate dynamic processes across different spatial and temporal scales, aiming to predict treatment efficacy through the application of machine learning models.

### Summary of Research Focus #### COVID-19 Research - **Stability Analysis**: Various compartments for COVID-19 models. - **Cost-Effectiveness Studies**: With delayed diagnosis analysis in Ghana. - **Viral Infections**: Including SARS-CoV-2, fractional-order TB and COVID-19 models. --- ### Mathematical Models and Differential Equations - Fractional differential equation solutions for Q fever, dengue fever, etc. - Modeling Ebola, Zika virus, etc., using different compartments and kernels. - Numerical methods and simulations for various disease transmission dynamics. --- ### Rabies Epidemiology and Control - Optimal control and cost-effectiveness analysis of rabies models with multiple classes. --- ### Virology and Vectors - Studies on bacterial infections (e.g., Q fever, monkeypox), viral vectors (e.g., trihybrid nanofluids). --- ### Chaotic Image/Signal Encryption - Multiplicative attributes from cyclic codes over Galois fields for encryption techniques. --- ### SARS-CoV-2 and COVID-19 Research - Fractional-order models and optimal control strategies for different diseases. - Includes dengue fever, HIV/AIDS, etc., with cost-effectiveness analysis. --- ### Poxviruses and Visceral Leishmaniasis (PLI) - Modeling PLI dynamics and fractional-order TB models in humans and animals. --- ### Vector-Borne Infectious Diseases - Studies on malaria, tick-borne diseases, etc., using various mathematical frameworks. - Includes dynamics with thermal radiation and stratification. --- This structure organizes the diverse research topics into relevant categories, ensuring clarity and conciseness.

This research focuses on understanding and controlling complex networked systems across various contexts, such as biological networks, robot swarms, and control theory applications. A unified framework is developed to analyze how these systems can be controlled through external inputs or adaptive mechanisms, particularly emphasizing large-scale networked systems for real-world implementation.

The researcher's work integrates theoretical models for quantum systems with interdisciplinary applications across physics, computer science, and optimization, particularly in machine learning contexts. Their research employs mixed methods, combining experiments with computational modeling, to advance understanding of quantum metrology and systems, while also exploring practical implementations through optimization algorithms. This approach bridges the gap between fundamental theory and real-world applications, focusing on precision and accuracy within quantum devices and systems.

The researcher's work is centered around advancements in bio-inspired drug delivery systems, particularly for wound healing, chronic wounds, and diabetes care. Their focus includes developing novel formulations for drug delivery (e.g., composite films, bioformulations) with a strong emphasis on biocompatible materials such as PEG-based films and multiscale approaches like yeast films and polysaccharides. They also explore sustainable and multiscale systems for treatment, such as bioresorbable meshes and multiscale drug delivery strategies. These efforts are driven by a commitment to improving health outcomes through innovative therapeutic interventions.

The researcher focuses on the application of human biological measurements and anthropometric techniques across diverse fields such as forensic anthropology, reconstructive facial surgery, medical imaging, dermatoglyphics, demographics, and preeclampsia research. These studies aim to identify physical traits like height and ethnicity using tools like percutaneous ultrasound, foot dimensions, hand morphology, airway structures, ergonomic measurements, and breast cancer treatment response patterns. The work bridges academic disciplines with practical societal applications, contributing to both scientific advancements and real-world problem-solving across forensics, surgery, medicine, demography, and social sciences.

The researcher has conducted extensive studies across several key areas, including cancer screening, disability support, vaccination prevention, neurodegenerative diseases, and medical education. Their work spans multiple domains focused on global health equity and individual needs. By examining diverse aspects of health challenges, the researcher aims to provide a comprehensive understanding to improve healthcare outcomes worldwide.

The researcher's work focuses on a comprehensive exploration of several key areas in physical and life sciences, including the development of advanced textiles, photocatalytic processes, biopolymer composites, additive manufacturing technologies, environmental sustainability, and agricultural applications. Their research spans themes such as textile material evaluations, energy efficiency, biochemical processes, nanotechnology applications, and sustainable practices, reflecting a multidisciplinary approach to advancing materials and energy solutions.

The researcher has made significant contributions to the field of applied mathematics through their work on differential equations, numerical analysis, mathematical physics, and optimization, with applications ranging from control theory to climate modeling. Their studies bridge fundamental questions across these disciplines, demonstrating how mathematical theories inform real-world phenomena, thereby advancing both theoretical understanding and practical problem-solving approaches.

The researcher has made significant contributions across a diverse range of areas, including the development of advanced deep learning and explainable AI techniques, the enhancement of numerical linear algebra methods for efficient data analysis, and their application in complex decision-making frameworks using machine learning. Their work bridges theoretical advancements with practical solutions, particularly in time-series forecasting and system modeling.

The researcher focuses on examining maternal mental health during pregnancy and postpartum in the domain of health sciences, with a particular emphasis on predictors of postpartum depression among new mothers, as demonstrated through a multicenter study in Kumasi, Ghana, employing Bayesian analysis.