Understanding and Assessing Human Informational Needs for Human-Centered Explainable AI

I my research, I have developed models and metrics for characterizing and assessing human informational needs in human-autonomy interaction settings. These approaches are grounded in concepts from human factors and cognitive psychology. Some of the main contributions of this work are:

Bi-Directional Communication for Value Alignment

I have also worked towards developing and evaluating algorithmic approaches that enable bi-directional communication between humans and agents. In this work, we have focused in particular on settings where humans aim to align the objectives of autonomous agents, encoded as reward functions, with their own objectives, which is called value alignment. Some of the main contributions of this work are:

Work of the Future

Since 2018, I have been a member of MIT's Work of the Future Task Force. As part of this work, I have visited over 50 factories across the United States and worldwide with interdisciplinary research teams in order to study how and if robots are being adopted in manufacturing and the impacts of new technologies on work. Some highlights from this work include: