Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learning

International Conference on Learning Representations
Kimia Hamidieh
Kimia Hamidieh

Kimia is a Ph.D. student in Computer Science at U of T and Vector Institute. Her research interests involve devising strategies for learning fair representations with respect to certain protected attributes from imbalanced and long-tailed distribution data. Currently, she is conducting research focusing on fairness in self-supervised representation learning. Previously, she graduated from Sharif University of Technology with a B.Sc. in Computer Engineering and interned at IST Austria.