Keita Mori

The University of Tokyo, Shibaura Institute of Technology

Papers

Total Citations

H-Index

About

Keita Mori is a computational ethologist and roboticist whose research bridges the gap between animal behavior analysis and autonomous machine control. His work centers on two key areas: probabilistic generative modeling of behavior and bipedal locomotion stability. In his most cited paper (2021, 6 citations), Mori introduces a novel framework that combines generative modeling with reinforcement learning to extract the intrinsic, underlying features of animal behavior. This approach addresses a fundamental challenge in ethology—understanding the stochastic, complex dynamics of natural movement—by enabling researchers to not only analyze but also reproduce and control behavior in artificial systems. Earlier, Mori contributed to robotics with his 2014 study on a stability criterion for biped robots navigating rough terrain, where he extended conventional support polygon methods to account for non-perpendicular ground surfaces. Though his citation counts are still growing, Mori’s interdisciplinary work is notable for its ambition to unify biological insight with machine learning and robotics, offering a powerful toolkit for decoding behavior in both animals and machines. His research holds promise for advancing autonomous systems and deepening our understanding of natural intelligence.