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Maja Rudolph

Research Scientist

 Maja Rudolph

About Me

As a Research Scientist at the BCAI, I work on probabilistic machine learning with the lead application of modeling the emissions of car engines under real driving behavior. My research is focused on embeddings – methods for learning interpretable representations from data. The unsupervised models we develop lie at the intersection of Bayesian machine learning and deep learning. Bayesian modeling helps communicate modeling choices and to reason about uncertainty while neural networks provide the flexibility to model complex interactions in the data. Before joining Bosch, I obtained a PhD in Computer Science from Columbia University.

My Research Fields

  • Probabilistic Modeling
  • Embedding Methods
  • Unsupervised Learning