Meera Hahn
Papers
3
Total Citations
34
H-Index
3
About
Meera Hahn is a researcher at the forefront of embodied AI and situated robotics, with a focus on enabling robots to understand and act intelligently in diverse, everyday environments. Her work bridges the gap between perception, reasoning, and action, tackling the fundamental challenge of how robots can acquire and apply knowledge without relying on costly simulations or manual engineering. In her most cited work, "Situated Bayesian Reasoning Framework for Robots Operating in Diverse Everyday Environments" (23 citations), she developed a probabilistic framework that allows robots to reason about their surroundings in context, a key step toward robust real-world deployment. Her 2021 paper, "No RL, No Simulation: Learning to Navigate without Navigating" (7 citations), introduced a groundbreaking approach that eliminates the need for simulation environments or online policy interaction—addressing a major bottleneck in robot learning by using static datasets instead. Earlier, her work on "SiRoK: Situated Robot Knowledge" (2018) explored the delicate balance between general knowledge and situational variability. With a growing citation footprint, Hahn’s contributions are shaping a more practical, scalable future for autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2No RL, No Simulation: Learning to Navigate without Navigating7 citations · 2021
- 3