Research
- Design and analysis of loss functions for machine learning
- Geometry of losses and property elicitation
- Evaluation of Generative Models
- Theory of convex surrogate losses
Publications:
- Proper Losses for Discrete Generative Models - (with Rafael Frongillo, and Bo Waggoner), ICML 2023
- On the Compatibility of Privacy and Fairness - (with Rachel Cummings, Varun Gupta, and Jamie Morgenstern), in UMAP 2019
Experience:
- National Center for Atmospheric Research - Machine Learning Research Intern, Summer 2023
- Georgia Institute of Technology - Machine Learning Undergraduate Research Asssitant, 2018-2019
- Technical University of Munich - Research Intern, Summer 2017
Projects:
Teaching Experience:
- University of Colorado- Boulder
- Fall 2023: CSCI 5454 Graduate Algorithms (GTA)
- Spring 2023: CSCI 5454 Graduate Algorithms (GTA)
- Fall 2021: CSCI 5454 Graduate Algorithms (GTA)
- Spring 2021: CSCI 3104 Algorithms (GTA)
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