M.S. Student, Applied Statistics (Biostatistics) · Georgia State University, Atlanta, GA, USA
My research develops flexible probability distributions and empirical likelihood methods for survival analysis, with a focus on improving statistical inference for biomedical data under small-sample and complex settings. It integrates distribution theory and likelihood-free inference, with applications in biomedical research and reliability studies.
I am a Master's student in Applied Statistics with a concentration in Biostatistics at Georgia State University, working under the supervision of Prof. Yichuan Zhao. My work centres on developing statistical models and likelihood-free inference methods for biomedical survival data, particularly in small-sample settings.
My current work introduces the Quadratic-Transformed Exponential-Gamma (QTEG) distribution and extends it using jackknife empirical likelihood methods to achieve likelihood-free inference, particularly in small-sample biomedical settings.
I hold a Master of Professional Studies in Analytics (Statistical Modeling) from Northeastern University, Toronto, Canada (2025), and an M.Sc. in Statistics from Ekiti State University, Nigeria (2021), where I served as an Assistant Lecturer supervising over 40 undergraduate research projects. I also hold a B.Sc. in Statistics from Ekiti State University (2016). I am a Fellow of the Commonwealth Academy of Leadership and Management (FCALM), UK.
My long-term goal is to develop advanced statistical methodology that integrates distribution theory, empirical likelihood, and biomedical and public health applications.
Provides academic support to undergraduate students enrolled in College Algebra (MILE Programme). Assists with conceptual understanding, problem-solving strategies, and exam preparation in a structured learning environment.
Conducts methodological research under Prof. Yichuan Zhao on distribution theory and empirical likelihood inference, contributing to the QTEG distribution thesis project and related manuscripts.
My thesis constitutes a three-stage methodological program building from distribution development through advanced inference to model validation, with each stage grounded in biomedical survival analysis.
Introduces a new class of flexible lifetime distributions based on a quadratic transformation of the exponential-gamma model, designed for modelling skewed and heavy-tailed biomedical survival data with tractable statistical properties.
Develops jackknife empirical likelihood (JEL and AJEL) methods as a likelihood-free inference framework for parameter estimation, improving accuracy for biomedical time-to-event data under small-sample conditions.
Proposes a goodness-of-fit testing framework based on characterisation-driven U-statistics within the empirical likelihood paradigm, providing a formal tool for validating distributional assumptions in biomedical survival analysis.
Constructs Bayesian predictive models for six cardiovascular conditions using PyMC and MCMC, deployed as an interactive clinical decision-support application incorporating full uncertainty quantification.
Launch AppA selection of publications is listed below. For a complete list, visit my Google Scholar or ResearchGate profile.
Selected media coverage of research and professional recognition.
Full academic CV including education, publications, presentations, teaching experience, and technical skills.
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