Ayano Hiranaka
Papers
3
Total Citations
21
H-Index
3
About
Ayano Hiranaka is a rising star in embodied AI and human-robot interaction, whose work is redefining how robots learn and assist in everyday life. Her research centers on three key frontiers: brain-robot interfaces, sample-efficient robot learning, and large-scale simulation benchmarks for human-centered tasks. Hiranaka’s major contributions include **NOIR** (Neural Signal Operated Intelligent Robots), a pioneering system that allows humans to command robots via brain signals for daily activities—a breakthrough in assistive robotics. She also developed **SEED**, a framework combining primitive skills with human evaluative feedback to overcome the sample inefficiency and safety challenges of long-horizon reinforcement learning in real-world settings. Most notably, Hiranaka co-created **BEHAVIOR-1K**, a comprehensive benchmark of 1,000 everyday activities grounded in a human survey, providing a standardized testbed for embodied AI research. Her work, already garnering citations across top venues, has been recognized for its practical impact and vision. Hiranaka’s research not only advances fundamental algorithms but also brings us closer to robots that seamlessly integrate into our homes, making her a key figure to watch in the next generation of robotics.
Research Focus
Key Achievements
Top Papers
- 1NOIR: Neural Signal Operated Intelligent Robots for Everyday Activities8 citations · 2023
- 2Primitive Skill-Based Robot Learning from Human Evaluative Feedback7 citations · 2023
- 3