Maja Waldron

Hello, I am an Assistant Professor of Statistics at the University of Wisconsin-Madison. My research develops statistical methods for trustworthy and efficient AI, with a focus on uncertainty quantification, conformal prediction, deep probabilistic modeling, and generative models. I completed my PhD under the supervision of David Blei.
My recent publications are available on Google Scholar.

Research Group

My group studies statistical foundations for modern AI systems, with a focus on uncertainty quantification, conformal prediction, generative modeling, and reliable prediction in data-scarce settings. Students at UW-Madison who are interested in these topics are encouraged to join our weekly reading group, where we read and discuss recent research papers on topics of interest.

Selected Work
  • CAOS: Conformal Aggregation of One-Shot Predictors, ICML 2026.
    Develops finite-sample uncertainty guarantees for one-shot prediction settings using conformal methods. This work is part of a broader research direction on uncertainty quantification and reliable prediction with limited labeled data.
Teaching
Background

Before joining UW–Madison, I was a research scientist at Bosch Research, where I worked on deep probabilistic modeling and anomaly detection. I served as a technical lead of the Bosch Center for AI (at the time Europe's largest AI lab with 150+ Ph.D. researchers) and contributed to the development of the center's strategy on foundation models. My work has led to methodological contributions published at PAMI, ICML, and ICLR, as well as to numerous patent applications.

Contact

Office: 6643 Morgridge Hall, UW-Madison
Email: maja.waldron@wisc.edu

Maja Waldron