Evan Cesanek
Papers
1
Total Citations
9
H-Index
1
About
Evan Cesanek is a cognitive scientist whose research explores how the human brain predicts and interacts with the physical properties of objects, particularly their weight. His key contributions lie at the intersection of perception, action, and learning, with a focus on how we use spatial cues to anticipate object dynamics. In his most-cited work (2022), Cesanek demonstrated that people can rapidly predict an object’s weight by leveraging learned associations between its location and weight, rather than relying solely on visual appearance. Using a novel three-dimensional robotic interface and virtual reality system, he showed that location-based weight prediction is both fast and cognitively efficient, offering new insights into the mechanisms underlying sensorimotor control and object manipulation. This work has garnered 9 citations and has implications for fields ranging from robotics to rehabilitation. Cesanek’s research continues to illuminate how prior experience shapes our ability to interact seamlessly with the physical world, making his contributions valuable for understanding the cognitive foundations of everyday actions.
Research Focus
Key Achievements
Top Papers
- 1