Pamela Massiel Chiroque Solano

I am a statistician dedicated to the advancement of precision medicine and personalised healthcare through the integration of statistical learning, Bayesian modelling and artificial intelligence.
My work focuses on developing interpretable models to predict individual treatment effects, enabling more informed and personalised medical decision-making.

My research combines advanced statistical theory with modern machine learning paradigms to address complex, real-world data challenges in health, ecology, and environmental monitoring.

These challenges include missing data, time-to-event and longitudinal structures, and non-Gaussian response distributions such as categorical, discrete, or inflated outcomes.

With more than 18 years of continuous research and academic experience, my expertise includes:

• Advanced statistical modelling - longitudinal data analysis, survival models, time-varying coefficients
• Machine learning and AI - predictive modelling, metaheuristic feature selection, explainable AI
• Bayesian inference and dynamic and hierarchical models - quantification of uncertainties and multi-level data integration
• Application areas - precision medicine, environmental monitoring and epidemiology.