How can we make generally intelligent social robots, like Rosey from The Jetsons, exist in society as assistants in our homes and workplaces? As people get busier and older, they need more personalized assistance. To help, robots must be general-purpose, designed to handle various tasks. They must also be capable of zero-shot learning, i.e. able to handle novel tasks. For most people, natural language is the easiest way to communicate with machines. Thus, robots must be able to understand and ground (i.e. link) their perceptual data such as audio (language and sounds), vision, tactile sensations, etc. in the world as actions to complete commanded tasks and to communicate back what happened. That is the focal point of my research: developing cognitive general-purpose social assistive robots capable of zero-shot learning (ZSL) by grounding multimodal sensory inputs into autonomous actions.

On a high level, my interests revolve around the exciting convergence of Natural Language Processing (NLP), Computer Vision (CV), Reinforcement Learning (RL), Robotics, and Human-Robot Interaction (HRI). By integrating RL and probabilistic planning with NLP and CV techniques, I aim to create advanced robotic systems capable of understanding natural language instructions, perceiving the environment through visual cues, and executing complex tasks effectively.

I am driven by the ambitious vision of developing artificially generally intelligent robots, preferably humanoids, that seamlessly assist humans in daily tasks, establishing profound connections with us.

Currently, I am exploring these interdisciplinary fields in labs at the Brown University and the University of Massachusetts Amherst,  gaining practical experience. My ultimate goal is to pursue a Ph.D. in this area and contribute to the frontier of intelligent robotics.