Yasaman Etesam
Papers
1
Total Citations
6
H-Index
1
About
Dr. Yasaman Etesam is pioneering the frontier of affective computing by bridging the gap between raw visual data and human-like emotional understanding. Her research centers on contextual emotion recognition, where she tackles the longstanding challenge of teaching machines to interpret feelings not just from facial expressions, but from the full scene—including body language, environmental cues, and commonsense reasoning. Her most influential work, "Contextual Emotion Recognition using Large Vision Language Models" (2024, 6 citations), demonstrates a breakthrough: achieving human-level recognition of apparent emotions in real-world settings by leveraging large vision-language models. This approach moves beyond traditional methods, showing that context is as critical as the person themselves. Dr. Etesam’s contributions are reshaping how we think about social AI, with implications for human-robot interaction, mental health monitoring, and assistive technologies. Her work stands out for its ambition to replicate the nuanced, holistic perception humans use daily, marking her as a rising leader in making AI not just smarter, but more empathetically aware.
Research Focus
Key Achievements
Top Papers
- 1Contextual Emotion Recognition using Large Vision Language Models6 citations · 2024