Ajith Anil Meera
Papers
10
Total Citations
114
H-Index
4
About
Ajith Anil Meera is a pioneering researcher at the intersection of computational neuroscience and robotics, whose work is reshaping how autonomous agents perceive and act under uncertainty. His primary research areas include active inference, the free energy principle, and brain-inspired learning algorithms for robotic systems. Meera’s major contributions lie in translating neuroscientific theories into practical robotic frameworks, most notably through his seminal survey "Active Inference in Robotics and Artificial Agents: Survey and Challenges" (55 citations), which has become a foundational reference for the field. He developed the Dynamic Expectation Maximization algorithm for state and input estimation, successfully demonstrating its utility in challenging real-world scenarios such as quadcopter flight in wind—providing the first experimental confirmation of the free energy principle’s applicability in robotics. His work on rhythmic precision-modulated action and perception reclaims the concept of saliency by incorporating circular causality, advancing models of visual attention. With over 110 total citations and a growing portfolio of high-impact publications, Meera is establishing himself as a leading voice in bio-inspired autonomous systems, bridging the gap between theoretical neuroscience and embodied artificial intelligence.
Research Focus
Key Achievements
Top Papers
- 1Active Inference in Robotics and Artificial Agents: Survey and Challenges55 citations · 2021
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- 4Reclaiming saliency: Rhythmic precision-modulated action and perception8 citations · 2022
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- 7Towards Metacognitive Robot Decision Making for Tool Selection3 citations · 2023
- 8On the Convergence of DEM’s Linear Parameter Estimator3 citations · 2021
- 9Informative Path Planning for Search and Rescue using a UAV2 citations · 2018
- 10Reclaiming saliency: rhythmic precision-modulated action and perception2 citations · 2022