Luis de Miranda

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About

Luis de Miranda explores the intersection of artificial intelligence and live artistic performance, focusing on how AI systems can collaborate with humans in real-time creative contexts. His major contributions center on developing models for human-AI collaboration in domains like music, dance, and acting, where he analyzes the mechanisms that enable effective co-creation. In his most-cited work, "On human-AI collaboration in artistic performance" (2020, 7 citations), he proposes a framework for collaborative artistic performance where AI systems act as partners rather than tools. His case study on musical improvisation (2019, 2 citations) demonstrates an AI system capable of both reactive and anticipatory behavior, accompanying a human pianist with a virtual drummer. This work is notable for applying fuzzy systems to model anticipation in collaborative music performance, a novel approach that bridges computational intelligence and artistic expression. De Miranda's research is particularly significant for advancing our understanding of how AI can engage in nuanced, temporally-sensitive interactions with human performers, opening new possibilities for creative partnerships in the arts.