Postdoctoral researcher in Computer Science and Human-Computer Interaction at the Fairness, Accountability, Transparency, and Ethics in AI (FATE) group, Microsoft Research, New York City.
Research focuses on uncovering societal harms from deploying machine learning (ML) systems, understanding their root causes, and envisioning remedies.
Particularly interested in characterizing ML supply chains and developing practical tools and policy solutions for ML practitioners.
Employs social, organizational, and political-economic lenses informed by technical realities through in-depth qualitative studies in ML production and deployment environments.
Primarily studies ML systems using image data (computer vision) or tabular data for classification or regression tasks.
Uses mixed methodologies including empirical studies, method/tool development, literature surveys, and policy reflections.