Embodied AI in Humanoid Robots: Progress, Social Interaction Dynamics, and Barriers to Scaling an Emerging Industry
Humanoid robots are rapidly evolving from pre-programmed mechanical systems into socially aware, AI-driven agents capable of operating in human environments. Early generations of humanoids relied on scripted dialog, rule-based conversation trees, and domain-specific speech modules, systems that produced predictable but limited human–robot interactions. These robots could speak, but they could not listen, adapt, or reason.
Recent advances in large language models, embodied AI agents, multi-modal perception, and cloud-scale training have transformed this landscape. Modern humanoid robots can now engage in naturalistic, context-aware conversation, interpret visual and auditory cues, plan actions, learn from demonstrations, and execute complex tasks with higher autonomy. These capabilities are reshaping the social dynamics between humans and robots, enabling more fluid collaboration, trust formation, and shared problem-solving.
Yet despite this progress, the humanoid robotics industry faces significant challenges in scaling hardware, safety, battery life, reliability, and economically viable use-cases. This talk will provide a balanced overview of recent technical breakthroughs, the realities of implementation, and the engineering barriers that must be addressed for humanoid robots to move from controlled pilots to widespread deployment.
Following the talk, all attendees are invited to dinner to be held at a nearby restaurant.
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- 901 G St. NW
- Washington, District of Columbia
- United States 20001
- Building: Martin Luther King Jr. Memorial Library
- Room Number: 401-A Conference Room
- Starts 03 December 2025 05:00 AM UTC
- Ends 15 December 2025 05:00 AM UTC
- No Admission Charge
Speakers
Sudhir Shenoy
Biography:
Sudhir K. Shenoy, Ph.D., is an engineer and researcher specializing in human–robot interaction, adaptive machine intelligence, and the ethical and societal impacts of emerging technologies. He most recently served as an Associate Program Officer at the National Academies of Sciences, Engineering, and Medicine, where he supported major engineering and defense initiatives across multiple boards, including the Board on Army Research and Development, the National Materials and Manufacturing Board, the Computer Science and Telecommunications Board, and the National Academy of Engineering. In this role, he contributed to consensus studies, coordinated workshops and roundtables, and synthesized technical research for federal sponsors.
Dr. Shenoy holds an M.S. and Ph.D. in Computer Engineering from the University of Virginia, where his research developed an emotion-adaptive social robot framework integrating Theory of Mind and model-based reinforcement learning. His work has been presented at leading venues including IEEE RO-MAN, ACM/IEEE HRI, and ICRA. Throughout his doctoral training, he taught and supported more than 2,000 students across 16 undergraduate and graduate engineering and policy courses, developing robotics and ethics curricula, mentoring project teams, and earning both the Outstanding Graduate Teaching Assistant Award (twice) and the Outstanding Ph.D. Student Award, the School of Engineering's highest honor for graduating doctoral students.
Dr. Shenoy is active in professional service and science policy, currently serving as Chair of the Professional Activities Committee for the IEEE Washington DC Section and Chair of the ASME Washington DC Section. He also serves on IEEE's AI Policy Committee and R&D Committee. He is a member of Omicron Delta Kappa, Sigma Xi, and the Washington Academy of Sciences.
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Agenda
6:00 - 6:15 PM - Introductions
6:15 - 7:30 PM - Embodied AI in Humanoid Robots
7:30 - 8:00 PM - Conclusion and Q&A