Dear Research Communities Team, 

Thank you for welcoming me to the Research Communities! I am excited to join this platform and share my work with fellow researchers and professionals. 

 About Me: 

I am Bayuh Asmamaw Hailu, a Researcher, Statistician, and Geospatial Analyst with a strong background in public health, epidemiology, and data science. I hold a Master of Public Health (MPH) in Epidemiology and Biostatistics from Wollo University, Ethiopia, and a Bachelor of Science (BSc) in Statistics from Addis Ababa University. Currently, I work as a Data Analyst/Research Assistant at the Research Center for Inclusive Development in Africa (RIDA) and Planning and budget team leader at Wollo University, where I contribute to projects focused on health, nutrition, and development across Africa. 

Expertise and Skills: 

My expertise lies in advanced statistical analysis, geospatial mapping, and machine learning. I am proficient in using software such as R, STATA, SPSS, ArcGIS, QGIS, SaTScan, GeoDa, and SAGA GIS for data analysis and visualization. I specialize in: 

- Spatial analysis to identify geographic patterns and determinants of health issues. 

- Bayesian methods for trend estimation and prediction using hierarchical method. 

- Multilevel modeling to understand complex hierarchical data. 

- Machine learning techniques, including neural networks, for time—series predictive modeling. 

- Principal Component Analysis (PCA) to extract key variables from complex datasets.

- Join point regression (Annual Average Percentage Change (AAPC)) to extract the trend.

 Research Interests: 

My research focuses on addressing public health challenges, particularly in low- and middle-income countries. My key areas of interest include: 

1. Maternal and Child Health: Mapping and analyzing trends in anemia, malnutrition, and adverse birth outcomes. 

2. Nutrition and Diet Quality: Investigating inequalities in dietary diversity and their impact on child health. 

3. Infectious Diseases: Studying the spatial distribution and determinants of HIV/AIDS and malaria. 

4. Health Disparities: Exploring regional and racial disparities in cancer incidence and mortality. 

5. Predictive Modeling: Using machine learning and time-series analysis to forecast health outcomes and inform interventions. 

Experience: 

I have contributed to several high-impact research projects, including: 

- Subnational mapping of anemia and its determinants in West and Central Africa, funded by the Bill & Melinda Gates Foundation. 

- Mapping diet quality and inequalities among Ethiopian children, funded by UNICEF. 

- Evaluating CMAM programs to improve the management of acute malnutrition. 

- Predicting adverse birth outcomes in the United States using multilayer perceptron neural networks. 

 Publications: 

I have authored and co-authored multiple peer-reviewed articles in reputable journals, including: 

- "Adolescent marriage, maternity, and limited access to education in 106 Countries: Bayesian analysis of prevalence, trend, and prediction" (Scientific Reports, Nature). 

- “Geospatial Distribution and Multilevel Determinants of Inadequate Minimum Dietary Diversity and Its Consequences for Children Aged 6-23 Months in Sub-Saharan Africa” (PLOS ONE). 

- "Geospatial Distribution and Multilevel Determinants of Inadequate Minimum Dietary Diversity and Its Consequences for Children Aged 6-23 Months in Sub-Saharan Africa" (PLOS ONE). 

- "Mapping and determinants of consumption of egg and/or flesh foods and zero vegetables or fruits among young children in Sub-Saharan Africa" (Scientific Reports, Nature). 

- "Spatial heterogeneity and factors influencing stunting and severe stunting among under-5 children in Ethiopia: spatial and multilevel analysis" (Scientific Reports, Nature). 

 Current Projects: 

- Predicting adverse birth outcomes in the United States: Using time-series machine learning models to forecast trends up to 2030.   (under review)

Next Project:

- Geospatial Disparities in Maternal and Child Health: An Integrated Analysis of Multi-Source Data to Quantify Burden, Risk Factors, and Equity Gaps in Low- and Middle-Income Countries

 Why I Joined the Research Communities: 

I joined the Research Communities to connect with like-minded researchers, share my findings, and collaborate on projects that address global health challenges. I am particularly interested in contributing to discussions on health disparities, predictive modeling, and geospatial analysis. 

I look forward to engaging with the community, learning from others, and contributing to meaningful research that improves health outcomes worldwide. 

Best regards, 

Bayuh Asmamaw Hailu

Email: bayuhasmamaw@gmail.com 

ORCID: (https://orcid.org/0000-0002-7810-2774)

GitHub: https://github.com/Bayuh23