I am a third-year Computer Sciences PhD student at UW-Madison, where I am co-advised by Aws Albarghouthi and Loris D’Antoni.

My work is motivated by the question of how we can ensure that technology – especially machine learning – is deployed in fair, trustworthy, and socially responsible ways. In particular, I’m interested in the idea that machine learning outcomes often hinge on arbitrary factors in data collection and model training. My research so far has addressed this question by certifying test-time model robustness to small perturbations in the training dataset.


  • November 2022 - I was selected as a 2023 WISCIENCE Public Service Fellow in the direct service pathway
  • November 2022 - I will be attending my first in-person confernce (NeurIPS 2022) at the end of the month
  • June 2022 - I spent the summer at Hima Lakkaraju’s AI4Life lab at Harvard to work on explainable ML
  • April 2022 - I gave a talk on my work certifying data-bias robustness in decision trees at the UW-Madison CS Research Symposium
  • December 2021 - My first paper, Certifying Robustness to Programmable Data Bias in Decision Trees, was published at NeurIPS!


Certifying Robustness to Programmable Data Bias in Decision Trees
Anna P. Meyer, Aws Albarghouthi, and Loris D’Antoni
NeurIPS 2021
[pdf] [slides] [video] [code]