Events

Engineering Intelligent Physical Human-Robot Interactions

Electrical and Computer Engineering
Lecture / Panel
 
For NYU Community
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Speaker:

Keya Rajesh Ghonasgi
University of Texas at Austin (UT)

Title:

"Engineering Intelligent Physical Human-Robot Interactions"

Abstract:

Technology for human use capitalizes on our ability to learn from interactions with the environment. Robotics technology has advanced significantly in the past few decades making physical human-robot interaction (HRI) a safe and promising new mode through which humans can learn and act upon their environment. At the same time, advances in artificial intelligence (AI) have provided us with frameworks for how robotic devices can control their behavior at a high level. As a result, we can now harness both human learning and robot learning abilities to engineer meaningful physical interactions that go beyond conventional technological solutions. In this talk, I will explore how physical HRI can be interpreted through the lens of neuroscience and translated into engineering solutions that can intelligently affect the human-robot system's behavior. I begin with a deep dive into human-exoskeleton interaction for motor training protocols using a curriculum learning-based approach. In particular, I will address the challenges in human data interpretation, exoskeleton control, and curriculum design. Additionally, I will examine how the fields of engineering design, AI, and neuroscience can be simultaneously leveraged to engineer effective physical interactions across a variety of potential HRI applications.

Bio:

Keya Ghonasgi is a doctoral candidate in the Mechanical Engineering department at the University of Texas at Austin (UT). Her research vision is to harness human and robot learning abilities to engineer intelligent human-robot interactions with applications including assistance, training, and augmentation. At UT Austin, she is a member of the Rehabilitation and Neuromuscular Robotics lab directed by Dr. Ashish Deshpande and collaborates with the Learning Agents Research Group directed by Dr. Peter Stone. In 2018, she earned her M.S. in Mechanical Engineering from Columbia University under Dr. Sunil Agrawal's guidance. Keya has been recognized as a 2022 Rising Star in ME and a 2023 CalTech Young Investigator. Her research has been supported through a graduate fellowship awarded by UT Austin (2022-23), an NSF M3X grant, and research collaborations with Meta Reality Labs and Google Brain.