Elom A. Amematsro

Kempner Research Fellow, Kempner Institute, Harvard University

I study how intelligent systems—brains and robots—learn flexible, hierarchical control. My work bridges reinforcement learning and statistical inference with computational motor neuroscience and robotics, aiming for theory that both explains neural computation and scales to embodied agents.

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Research at a glance

• Hierarchical RL & Inference — Compositional skills, credit assignment, and uncertainty for sequential control.
• Computational Motor Control — How neural dynamics organize action, from flexible sequencing to adaptation.
• Robot Learning — Embodied tests (sim + hardware); dexterous manipulation and adaptive control.