Here is a list of papers that I have worked on:

  1. Deep Learning Interpretation: Flip Points and Homotopy Methods, Mathematical and Scientific Machine Learning Conference, Proceedings of Machine Learning Research, 2020.
  2. Auditing and Debugging Deep Learning Models via Decision Boundaries: Individual-level and Group-level Analysis, La Matematica, Official Journal of the Association for Women in Mathematics, 2021.
  3. Learning Diverse Gaussian Graphical Models and Interpreting Edges, Proceedings of SIAM International Conference on Data Mining, 2019.
  4. Deep Learning Generalization and the Convex Hull of Training Sets, Deep Learning through Information Geometry Workshop, NeurIPS, 2020. (Invited to Springer Journal on Information Geometry)
  5. Extrapolation Frameworks in Cognitive Psychology Suitable for Study of Image Classification Models, Workshop on Human and Machine Decisions, NeurIPS, 2021.
  6. To What Extent Should We Trust AI Models When They Extrapolate? under review, 2022.
  7. Decision Boundaries and Convex Hulls in the Feature Space that Deep Learning Functions Learn From Images, 2022.
  8. A Homotopy Algorithm for Optimal Transport, 12th Annual Workshop on Optimization for Machine Learning, NeurIPS, 2020.
  9. Using Wavelets and Spectral Methods to Study Patterns in Image-Classification Datasets
  10. Debugging Trained Machine Learning Models Using Flip Points, ICLR Workshop on Debugging Trained Machine Learning Models, 2019.
  11. Interpretable Insights about Medical Image Datasets: Using Wavelets and Spectral Methods, ICML Workshop on Human Interpretability in Machine Learning, 2020.
  12. Social Fairness, Accountability and Transparency of the Data Economy: Using Machine Learning to Combat the Emptiness of Privacy Policies, ICML Workshop on Law & Machine Learning, 2020.
  13. A Sketching Method for Finding the Closest Point on a Convex Hull, 2021.
  14. Federated Learning without Revealing the Decision Boundaries, work in progress, 2021.
  15. Using Wavelets to Analyze Similarities in Image-Classification Datasets, 2020.
  16. Investigating Decision Boundaries of Trained Neural Networks
  17. Refining the Structure of Neural Networks Using Matrix Conditioning
  18. Optimizing Real-time Decisions in Hierarchical Humanitarian Aid Delivery Systems
  19. A Probabilistic Framework and a Homotopy Method for Real-time Hierarchical Freight Dispatch Decisions