Michael Suguitan
Papers
9
Total Citations
169
H-Index
6
About
Michael Suguitan is a robotics researcher specializing in social robotics, human-robot interaction (HRI), and affective computing. He is perhaps best known as the creator of **Blossom**, an open-source social robotics platform designed to democratize robot development by lowering the technical barriers to designing, manufacturing, and programming social robots. Blossom's flexible, compliant tensile structure enables organic, lifelike movements, and its multiple publications have collectively garnered over 80 citations, reflecting its significant influence on accessible HRI research. Suguitan has made notable contributions to affective robot movement generation, developing neural network-based approaches — including MoveAE and CycleGAN-based synthesis — that allow robots to automatically produce expressive, varied gestures beyond repetitive preprogrammed behaviors. His Face2Gesture work extends this further by translating human facial expressions into robot movements through shared latent space networks, enabling more personalized interactions. Beyond hardware and motion generation, Suguitan has explored the conceptual framing of robotics, with his "Collection of Metaphors for Human-Robot Interaction" (49 citations) encouraging researchers to rethink assumptions about robotic perfection. His telepresence work addresses real-world constraints on HRI research access. Across his career, Suguitan consistently champions inclusive, expressive, and human-centered approaches to social robotics.
Research Focus
Key Achievements
Top Papers
- 1Blossom68 citations · 2019
- 2Collection of Metaphors for Human-Robot Interaction49 citations · 2021
- 3MoveAE15 citations · 2020
- 4Affective Robot Movement Generation Using CycleGANs11 citations · 2019
- 5
- 6Blossom7 citations · 2018
- 7Blossom6 citations · 2018
- 8
- 9