My various research interests include:
- Critical Algorithm Studies
- Algorithmic fairness, especially approaches that are not “one-size-fits-all”
- Applied Inverse Optimization
- Formulating more efficient algorithms, and heuristic approaches in domain-specific applications
- Applications of inverse optimization in observing gerrymandering in legislative districts
- Applications of inverse optimization in measuring dataset imbalance in Machine Learning models
- Preference Elicitation Technologies
- With an eye towards retooling preference elicitation towards understanding non-human entities as Latourian agents that hold and enact values
- Politics of labeling practices in preference elicitation methods
- Applied Machine Learning, and STS Perspectives on Being a Practitioner of ML
- Conceptual/data drift, and how it arises and is managed
- “Articulation work” in quantizing settings into which ML is introduced
- Feminist Philosophies of Technoscience
- Particularly, the philosophies of Karen Barad and Susan Leigh Star