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Consultant Profile

Dr Clement Twumasi (PhD|CStat|MPhil|BSc.)

Areas of Consultancy:
Bayesian methods
Censuses and surveys
Clinical trials
Design and analysis of experiments
Epidemiology
Exploratory data analysis
Forecasting
GLMs and other non-linear models
Multivariate analysis
Non-parametric statistics
Numerical analysis and optimisation
Probability
Reliability
Sampling
Simulation
Statistical computing
Statistical inference
Survival analysis
Time series

Region of consultancy:
Worldwide

Profile

Dr Clement Twumasi is a Senior Medical Statistician at the University of Oxford, Nuffield Department of Medicine (NDM), Experimental Medicine Division, and a Chartered Statistician (CStat) of the Royal Statistical Society. He previously worked as a Clinical Trials Statistician at Imperial College London, Postdoctoral Biostatistics Research Assistant at the University of Oxford Department of Statistics, and Biostatistics Research Assistant at the Oxford University Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Science (NDORMS). He holds a PhD in Mathematics as a Vice Chancellor’s Scholar at Cardiff University and has extensive experience across medical statistics, infectious disease modelling, agent-based modelling, and data science. He is also a statistical consultant and data scientist for AI Rehab LLC (USA). His expertise spans, but is not limited to: Bayesian methods, clinical trials, computational/mathematical biology, simulations, time-series analysis, survival analyses and multi-state Markov modelling, and machine learning. Beyond academia, he is committed to promoting statistical education through his free online programming school and well-subscribed YouTube channel (dubbed “Clement Twumasi Educative Channel”), teaching R programming and advanced statistical methods to global audiences. In addition to his academic research contributions and publications, he serves as a reviewer for high-impact Q1 journals such as the International Journal of Forecasting (IJF), PLOS One, and PLOS Computational Biology.

Background

Dr Clement Twumasi has an extensive academic and professional background spanning mathematics, statistics, and biomedical research. He earned his PhD in Mathematics from Cardiff University, specialising in infectious disease modelling and computational statistics, following an MPhil in Statistics (GPA 4.0/4.0, awarded Best Research in Mathematics in Ghana, 2018) and a BSc in Statistics with Mathematics from the University of Ghana. He later served as a Postdoctoral Biostatistician at the University of Oxford Department of Statistics and currently works as a Senior Medical Statistician at the University of Oxford, supporting vaccine-related research within the Oxford Biomedical Research Centre (BRC) across multiple departments. He has held research and consulting roles at leading UK institutions, including Oxford and Imperial College London, contributing to NIHR- and MRC-funded projects on vaccines, infectious diseases, and clinical trials. His academic excellence has been recognised through several honours, including the Cardiff University Vice Chancellor’s Scholarship, the UK Global Talent Visa (Exceptional Talent), Chartered Statistician (CStat) status from the Royal Statistical Society, and selection for the prestigious Heidelberg Laureate Forum (2021) as one of the world’s most exceptional young mathematicians and computer scientists. Beyond research, Dr Twumasi serves as a reviewer for top-tier journals such as the International Journal of Forecasting, PLOS One, and PLOS Computational Biology. He is an active member of professional societies including the Royal Statistical Society, Operational Research Society, Society for Mathematical Biology, and Oxford Medical Statistics Network (OxStat). He has published widely in Q1 journals, delivered invited talks, and leads initiatives promoting statistical literacy and mentorship worldwide.

Specialisms

GLMs, GLMMs, and other non-linear models, Clinical trials, Epidemiology, Stochastic Simulation, Classical Bayesian methods and Approximate Bayesian Computation, Forecasting & Backcasting, Predictive Modelling, Survival analysis, Time series analysis, Probability & Statistical inference, Multivariate analysis, Non-parametric statistics, Agent-based Modelling, Infectious Disease Modelling, Exploratory data analysis, Mathematical Biology, and Design and analysis of experiments, Functional Data Analysis, etc.

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