Jiecheng Ren

University of Science and Technology of China

Papers

Total Citations

H-Index

About

Jiecheng Ren is a rising researcher at the intersection of brain-computer interfaces (BCIs) and human-robot interaction (HRI), with a focus on how humans perceive and control robots. Ren’s work spans two critical frontiers: decoding neural signals for robotic control and understanding the psychological dynamics of human-robot encounters. In a standout achievement, Ren led the winning solution for the supervised motor imagery task at the prestigious BCI Controlled Robot Contest in the 2021 World Robot Contest, a paper that has garnered 5 citations and demonstrates practical expertise in data augmentation and feature extraction for real-world BCI systems. Complementing this technical work, Ren’s research delves into the neural and evolutionary underpinnings of robot perception. A 2024 study (3 citations) reveals separable amygdala activation patterns during robot evaluations, offering a neurobiological basis for social judgments of machines. Meanwhile, a 2021 paper (2 citations) provocatively shows that humanoid robots are perceived as an evolutionary threat, drawing on science fiction narratives to inform HRI design. By bridging engineering and cognitive neuroscience, Ren is shaping how we build and understand robots that coexist with humans.