Akanksha Saran
The University of Texas at Austin, Microsoft (United States)
Papers
6
Total Citations
131
H-Index
5
About
Akanksha Saran is a robotics and human-robot interaction researcher whose work centers on leveraging human social cues — particularly gaze, acoustic signals, and natural teaching behaviors — to make robots more intelligent and socially aware. Her most influential contribution, "Human Gaze Following for Human-Robot Interaction" (2018, 56 citations), introduced a novel approach to predicting human gaze fixations, enabling robots to better infer human intentions and engagement. This was complemented by her widely recognized review, "Human Gaze Assisted Artificial Intelligence" (2020, 47 citations), which synthesized gaze-related research across computer vision, natural language processing, and robotics, establishing her as a leading voice in the field. Saran's work extends beyond gaze: she has explored how acoustic cues from human teachers can enrich robot learning, and how optimal viewpoint selection can improve robotic failure detection. Her research on teacher gaze patterns and social learning principles reflects a broader mission — creating robots that learn from humans the way humans learn from each other. Through her multidisciplinary contributions, Saran has meaningfully advanced the goal of intuitive, socially intelligent human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1Human Gaze Following for Human-Robot Interaction56 citations · 2018
- 2Human Gaze Assisted Artificial Intelligence: A Review47 citations · 2020
- 3Enhancing Robot Learning with Human Social Cues10 citations · 2019
- 4Viewpoint selection for visual failure detection8 citations · 2017
- 5Understanding Teacher Gaze Patterns for Robot Learning8 citations · 2019
- 6