Cedric De Boom

Ghent University, Ghent University Hospital

Papers

Total Citations

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About

Cedric De Boom is a robotics and machine learning researcher whose work sits at the intersection of autonomous systems, active perception, and probabilistic inference. He is best known for his pioneering contributions to applying the **active inference framework** — a neuroscientifically grounded theory of how biological agents perceive and act — to artificial robotic systems. His most cited work, "Learning Generative State Space Models for Active Inference" (2020, 39 citations), demonstrated how autonomous agents could learn to minimize free energy to drive intelligent behavior, laying important groundwork for biologically inspired AI. Building on this, his research on active vision for robot manipulators (2021, 23 citations) addressed real-world sensing challenges such as occlusions and limited field of view, enabling robots to strategically gather information before completing tasks. De Boom has also contributed to practical robotics applications, including a data-efficient approach to robotic grasping from a single demonstration (2018). Across his body of work, he consistently bridges theoretical neuroscience-inspired frameworks with tangible engineering solutions, making him a notable voice in the growing community exploring free energy principles for next-generation autonomous robots.