Daniel M. Torres
Papers
2
Total Citations
5
H-Index
2
About
Daniel M. Torres is a rising researcher at the forefront of human-robot interaction and affective computing, with a focused interest in how emotional intelligence can be embedded into virtual and robotic agents. His work bridges the gap between technology and human psychology, particularly in educational and gaming contexts. In his highly cited 2024 study, "The Emotions and Advice in Virtual Assistants," Torres investigated the critical interplay between user trust and a virtual agent’s emotional expressions, revealing how emotion validation can shape the acceptance of advice in interactive scenarios. Building on this, his work "Roboldo: An Affective Robot for Empathetic Social Interactions in Education" pioneers the integration of social and emotional characteristics into educational robots—a domain where most agents remain purely functional. By designing robots capable of empathetic engagement, Torres is redefining how technology can support learning, moving beyond logic-based instruction to foster deeper, more meaningful student interactions. Though early in his career, his contributions are already shaping the next generation of emotionally aware educational tools, with his 2024 publications accumulating 5 citations and signaling a promising trajectory in this emerging field.
Research Focus
Key Achievements
Top Papers
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- 2