Lisa Cerda
Papers
1
Total Citations
3
H-Index
1
About
Lisa Cerda’s research lies at the compelling intersection of affective computing, human-robot interaction, and social cognition. Her most-cited work, “Emotional Valence Recognition on Virtual, Robotic, and Human Faces: a Comparative Study” (2020), offers a foundational contribution by systematically comparing how individuals perceive emotional expressions across human, robotic, and virtual agents. This study provides critical insights into the design of socially intelligent machines, revealing nuanced differences in how valence is decoded from synthetic versus natural faces. Though early in her career, Cerda’s work has already garnered attention for its methodological rigor and its implications for improving human-robot communication. By bridging psychology and robotics, she helps pave the way for more empathetic and effective artificial social agents. Her research is particularly relevant for developers of assistive technologies and social robots, where accurate emotional recognition is key to user trust and engagement. As she continues to explore the boundaries of emotional AI, Cerda is establishing herself as a thoughtful voice in understanding how humans relate to increasingly lifelike machines.
Research Focus
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Top Papers
- 1