Name: David Banahene
Pronouns: he/him
Institution: University of South Carolina
Department: Epidemiology and Biostatistics
Biography:
I am David Banahene, currently enrolled in a Ph.D. program in Biostatistics at the Arnold School of Public Health, University of South Carolina, where I also serve as a Graduate Instructional Assistant. I hold an M.Sc. in Mathematics from The University of Texas Rio Grande Valley and a B.Sc. in Statistics from Kwame Nkrumah University of Science and Technology. This multidisciplinary background uniquely positions me at the intersection of applied mathematics, data science, and public health. My journey began in an underprivileged community in Ghana, where I witnessed firsthand the devastating impact of poor healthcare infrastructure, particularly on child mortality rates. This experience ignited my passion for leveraging data to drive impactful healthcare policies. I’ve honed this skill set through roles such as Data Quality Monitor at Ghana Statistical Services and Registration Officer at the Ghana National Identification Authority. My master’s thesis, “”An Investigative Study of Potential Factors that Contribute to High Under-Five Mortality Rate in Africa,”” underscores my commitment to using data analytics to tackle urgent public health issues.
Academic Status: PhD Student
Year in program: 1st
Research Area/Department: Applied Mathematics; Biology; Data Science; Engineering; Machine Learning/AI; Mathematics; other
Other, specify: Biostatistics , statistics
Major/Specialty: Biostatistics
Degrees Earned or in Progress: Biostatistics, PhD (In progress) MSc. Mathematics ( completed) BSc. Statistics ( completed)
What courses or academic preparation have you completed to prepare for a summer internship experience?
Mathematical Modeling Ordinary differential Equation Statistical Learning Statistical Methods Linear Models. Numerical Analysis Mathematical Statistics
Have you published any research or worked on research/technical projects? No
Where has your research been published or where have you conducted research/technical projects?
Please describe your research/academic interests:
My research interests are at the confluence of Applied Mathematics, Biostatistics, and Public Health. They have been carefully curated to combine rigorous mathematical modeling and advanced statistical techniques, all aimed at solving pressing healthcare challenges. My Ph.D. in Biostatistics is a manifestation of this interdisciplinary focus, where I apply statistical methods to decode complex healthcare data, thereby providing actionable insights for policy interventions.
Computational and Data Science Areas:
Applied Mathematics; Computational Science Applications, i.e., Bioscience, Cosmology, Chemistry, Environmental Science, Nanotechnology, Climate, etc.; National Security; Data Analytics and Visualization; High-Performance Computing; Machine Learning and AI
Research Synergy:
My academic journey, which currently culminates with a Ph.D. in biostatistics at the University of South Carolina, has been a carefully orchestrated combination of statistics, mathematics and computational sciences, each chosen to complement my core objective: to use data science to revolutionize public health. My master’s thesis “”An Investigative Study of Potential Factors Contributing to the High Mortality Rate in Africa”” proves my commitment to using computational methods for social benefit. Why is this aligned to the DOE laboratories? The main fields of DOE – Applied Mathematics, Data Science and Machine Learning/AI – not only reflect my academic pursuits, but also reflect the interdisciplinary approach I have adopted in my research. I have a rich depth of analytics expertise reinforced by practical applications in public health, making me an ideal candidate for collaborative efforts in DOE laboratories. The SRP program’s emphasis on long-term collaboration is an ideal platform to combine my data-based public health research with the latest technologies and resources of the DOE laboratories. I am especially interested in contributing to projects that transcend traditional disciplinary boundaries, as is the case with my own work. This internship is not just an opportunity for me; I see it as a confluence of mutual interests and objectives, where both I and DOE laboratories can benefit from a rich exchange of ideas and methods.
Motivation:
My motivation for participating in the SRP 2024 Workshop stems from a deeply personal commitment to leveraging data science for public health transformation. Born and raised in a community in Ghana, I’ve witnessed firsthand the devastating effects of inadequate healthcare infrastructure on child mortality rates. These early-life experiences fueled my academic journey, culminating in a Ph.D. in Biostatistics focused on mathematical modeling and advanced statistical techniques for healthcare data analysis. The SRP program’s interdisciplinary approach, emphasizing Applied Mathematics, Data Science, and AI, aligns perfectly with my own research interests and professional aspirations. It offers a unique platform to not only apply but also expand my skill set, working alongside leading scientists from DOE National Laboratories. I’m particularly attracted to the program’s emphasis on fostering long-lasting collaborations, resonating with my career goal of creating scalable public health solutions through data-driven approaches.
Lightning Talk Title: Harnessing Data Science for Advancing Public Health.