Tanya Keshari
Papers
1
Total Citations
61
H-Index
1
About
Dr. Tanya Keshari is a leading researcher in affective computing and computer vision, whose work focuses on the automatic recognition of human emotion through multimodal analysis. Her most-cited paper, "Emotion Recognition Using Feature-level Fusion of Facial Expressions and Body Gestures" (2019, 61 citations), makes a pivotal contribution by demonstrating that combining facial cues with body language—rather than relying on a single modality—significantly improves emotion detection accuracy. This research is grounded in psychological findings that humans process emotional information from multiple visual channels, and it has direct applications in photojournalism, virtual reality, sign language recognition, and Human-Robot Interaction (HRI). By advancing feature-level fusion techniques, Dr. Keshari has helped bridge the gap between computational models and real-world emotional intelligence. Her work is widely cited by scholars developing more robust, context-aware systems for human-computer interaction. Through her innovative approach to integrating diverse visual signals, Dr. Keshari continues to shape the future of empathetic technology, making machines better equipped to understand and respond to human emotional states.
Research Focus
Key Achievements
Top Papers
- 1