Hi, this is Fahad, I am glad you have made it to my page. I am a Biostatistician, working as an assistant professor of biostatistics and data science at Arizona State University. I completed an M.S. and Ph.D. in Statistics from TEXAS TECH, respectively. Before moving to the US as a graduate student at TEXAS TECH, I obtained my B.S. in Mathematics and M.S. in Applied Mathematics from Dhaka University. I worked as a Postdoctoral research scientist in Biostatistics from University of Colorado School of Medicine of CU Anschutz and also worked as an ORISE fellow in Machine Learning at NCTR, FDA. Also I worked as a Biostatistical consultant at TTUHSC and the NEM Research Institute of Rutgers New Jersey Medical School.

My research interest evolves in many areas within Statistics, Machine Learning/AI model development and implementation, Biomedical Data Science, Stochastic Epidemiology, and Biostatistics. Inspired by Debabrata Basu's groundbreaking contributions to statistics, I delved deeper into the field, immersing myself in his methodologies and insights. I pursued advanced studies in statistics, ultimately becoming a dedicated statistician committed to pushing the boundaries of knowledge in the discipline.  Moreover, I am interested to develop trustworthy, deployable AI systems that meaningfully improve early detection and decision-making in public health settings. 

As a biostatistician, my research program centers on developing and applying rigorous statistical and computational methods to advance population health, with a particular emphasis on chronic disease prevention, management, and outcomes. I focus on integrating large-scale observational data, electronic health records, and real-world evidence to generate robust, reproducible insights that inform primary care practice and healthcare delivery. My work includes the design and analysis of pragmatic studies, risk prediction modeling, causal inference in longitudinal settings, and the evaluation of interventions aimed at improving equity, quality of care, and patient-centered outcomes. Through close collaboration with clinicians, epidemiologists, and health system leaders, I aim to translate methodological innovation into actionable evidence that strengthens healthcare systems and improves health outcomes at both individual and population levels.