I’m a curious researcher fascinated by the complexity of our inner experiences and the world around us, driven by the purpose of improving our health and well-being.

• 💻🔬 Methodologically, I am exploring how explainable machine learning can be used as a scientific tool to model complexity. Within public health and epidemiology, these tools have potential to help us uncover the complex patterns, mechanisms, and dynamics of diseases emerging from the interplay of biopsychosocial factors.
• 🎓🦠 Academically, I have contributed to the fields of bioinformatics, immunology, and infectious diseases (mainly HIV and COVID-19). More recently, I’ve broadened my focus to investigate how mental health and societal factors interact with and affects us.
• 🤔💡 Personally, I am committed to challenging limiting assumptions within statistics and biomedical research. I do this by integrating insights from diverse fields such as philosophy, cognitive and contemplative science, causal inference, artificial intelligence, and complexity science.
• 🔓📢 Socially, I advocate for open-source and reproducible research. I also actively explore innovative formats for scientific communication and education, aiming to make complex knowledge accessible to the public.