My past research has encompassed various areas of deep learning, including but not limited to, learning representations for diverse modalities, counterfactual generation, interpretability, text style transfer, unsupervised learning, and more. I hold an MS in Computer Science from USC/ISI, where I also started my research career under the guidance of Kevin Knight; our work on probing in sequence models established a foundational contribution in the field of interpretability.