
About
Martin Becker is an Assistant Professor at the University of Rostock and currently affiliated with Nima Aghaeepour’s lab at Stanford University. His research bridges machine learning and medical multiomics, with a focus on Bayesian modeling, distributed analytics, and exceptional model mining.
- University of Würzburg & UT Austin (Computer Science & Mathematics)
- Doctoral Work: DMIR Group (L3S Research Center Hanover & University of Würzburg)
His work spans participatory sensing, citizen science, and medical applications, including the development of the EveryAware platform for sensor data integration and the DeepScan project for large-scale behavioral analysis. Current research at Stanford applies machine learning to maternal immunology, Alzheimer’s diagnostics, and multiomics health modeling.
Recent publications demonstrate methodological advances in unsupervised AI, subgroup discovery, and immune response modeling, with applications in pregnancy outcomes, telomere dynamics, and neonatal health.
Contact: mgbckr@stanford.edu
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