About me

I’m a lecturer of health informatics at Wollo University since September 2022. I have studied Master of Public Health(MPH) in health informatics from University of Gondar. Currently, as a teacher and researcher, my primary focus revolves around utilizing public data repositories for conducting research. I find great value in the abundance of publicly available datasets, which provide opportunities to explore various aspects of public health and generate evidence-based insights. By leveraging these repositories, I aim to delve into critical research questions, analyze trends, and uncover patterns that contribute to our understanding of public health dynamics. This approach allows me to apply my expertise in data analysis, programming, and statistical techniques to extract meaningful information from diverse public health datasets. In preparation for my future PhD studies, I possess a strong passion for public health and a keen interest in machine learning, programming, and AI in health. I aim to leverage these skills to contribute to cutting-edge advancements in healthcare. Specifically, I am eager to explore the application of machine learning and AI techniques to enhance public health interventions, with a focus on maternal and child health, family planning, and chronic disease. Additionally, I aspire to address health disparities and promote health equity by utilizing machine learning algorithms to understand and mitigate social determinants of health. Throughout my PhD journey, I will prioritize ethical considerations and aim to ensure responsible and inclusive practices in the application of AI and machine learning in public health research and practice. Ultimately, my goal is to make a meaningful impact on public health outcomes, reduce health inequities, and push the boundaries of knowledge in the field. I am also deeply intrigued by the concept of explainable AI. As a potential research focus for my PhD, I am interested in exploring methodologies and techniques that can enhance the interpretability and transparency of AI models in healthcare. I recognize the importance of understanding how AI algorithms arrive at their decisions, especially in critical healthcare applications. By investigating explainable AI, I aim to develop methods that provide insights into the reasoning and decision-making processes of AI systems, empowering healthcare professionals and stakeholders to trust and utilize these technologies more effectively.