Mirjana Spasojevic
Papers
1
Total Citations
5
H-Index
1
About
Mirjana Spasojevic is a researcher at the intersection of human-robot interaction (HRI) and affective computing, with a focus on enabling robots to detect and recover from errors in real-world social contexts. Her most notable contribution is the creation of the Bystander Affect Detection (BAD) Dataset, a pioneering resource that leverages implicit bystander reactions—such as confusion, smirks, or giggles—to help robots recognize their own mistakes. This work, published in 2023 and already garnering 5 citations, addresses a critical gap in HRI: the need for robots to autonomously identify failures without explicit human feedback. By shifting the error-detection burden from the robot's internal sensors to the natural social cues of nearby humans, Spasojevic’s research opens new pathways for more intuitive and resilient robotic systems. Her approach is particularly innovative for its focus on bystanders rather than direct interaction partners, reflecting a nuanced understanding of social dynamics. With a growing citation impact and a clear trajectory toward practical applications in assistive robotics, Spasojevic is establishing herself as a key voice in making robots more perceptive and socially aware.
Research Focus
Key Achievements
Top Papers
- 1