Pekka Marttinen

Papers

Total Citations

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About

Pekka Marttinen is a leading researcher at the intersection of machine learning, probabilistic modeling, and health data science. His work focuses on developing scalable Bayesian methods and causal inference techniques to extract meaningful insights from complex, high-dimensional biomedical data. A key contribution is his pioneering research on the climate impacts of healthcare digitalization, as highlighted in his 2025 scoping review, which systematically maps how digital health technologies affect the sector's carbon footprint—a critical area for sustainable healthcare. Marttinen has also advanced computational tools for analyzing electronic health records and genomic data, enabling more accurate disease risk prediction and personalized treatment strategies. His methodological innovations in variational inference and model selection have been widely adopted, with his most cited papers accumulating hundreds of citations. Notable achievements include leading interdisciplinary projects that bridge AI, epidemiology, and environmental health, as well as mentoring a new generation of data scientists. Marttinen’s work not only pushes the boundaries of statistical machine learning but also directly addresses pressing global challenges, making him a pivotal figure in responsible, data-driven healthcare innovation.