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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 & a data scientist for an international start-up company (on a part-time basis). 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 is a Chartered Statistician with extensive academic & professional experience spanning mathematics, statistics & 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) & a BSc in Statistics with Mathematics from the University of Ghana. He later served as a Postdoctoral Biostatistician at the University of Oxford and currently works as a Senior Medical Statistician Oxford University, supporting BRC funded vaccine & health research across multiple departments. He has held research & consulting roles at Oxford and Imperial College London, contributing to NIHR- and MRC-funded projects on vaccines, infectious diseases, and clinical trials. Some of his achievements include the Cardiff University Vice-Chancellor’s Scholarship, UK Global Talent Visa (Exceptional Talent), Chartered Statistician (CStat) status from the Royal Statistical Society, and selection for the Heidelberg Laureate Forum (2021) as one of the world’s outstanding young mathematicians. He serves as a reviewer for PLOS One, PLOS Computational Biology, and the International Journal of Forecasting, & an active member of several professional societies (e.g., the RSS, OR Society & Society for Mathematical Biology). As an accredited RSS Statistical Consultant, he provides high-level consultancy & training to individuals and organisations across sectors: • Academic: statistical training workshops, collaborative research, CPD activities, curriculum development, & postgraduate or scholarship application support. • Healthcare: clinical trial design and analysis, biostatistical consulting, health data analytics & infectious disease modelling. • Industry and Policy: statistical advisory services, data-driven decision support, predictive modelling & data science applications.

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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