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I am a curious researcher passionate about untangling complexity and enhancing health and well-being through scientific inquiry. My methodological approach focuses on applying explainable machine learning as a tool to model complexity, particularly in the fields of public health and epidemiology. My academic contributions span bioinformatics, immunology, and infectious diseases, mainly HIV and COVID-19, while I also explore how mental health and societal factors can influence disease onset. I strive to challenge the limiting assumptions within statistics and biomedical research by integrating insights from various disciplines including philosophy, cognitive science, and artificial intelligence. Furthermore, I advocate for open-source and reproducible research, actively engaging in innovative scientific communication formats to make research accessible to the general public.
Focuses on clinical, social, and cognitive psychology.