Phoenix Perry is an interdisciplinary researcher, educator, and practitioner specializing in the intersections of human-computer interaction (HCI), creative computing, and machine learning (ML) for embodied and artistic interaction design. Their work spans creative technology, games, immersive media, interactive machine learning, and generative AI, with a strong focus on empowering creative practitioners through accessible tools and methodologies.
This UKRI EPSRC 12-month project tackles bias in AI music generation caused by over-reliance on Western classical and pop music datasets. By developing AI tools and datasets that promote access to marginalized genres, it empowers and fosters inclusivity in music consumption.
As a disabled arts practitioner, I create bespoke input systems and interfaces, drawing on over 20 years of experience to design games like Bot Party that explore accessibility through playful, embodied interactions. My PhD research proposes a criptastic design framework, embedding the values and practices of disabled designers to redefine accessibility as a creative process rather than a checklist.
Perry explores creative applications of generative AI, emphasizing small-data methodologies that align with artistic processes. Their work advocates for human-centric and resource-efficient models for AI integration into creative workflows.
A Small-Data Mindset for Generative AI Creative Work
Vigliensoni, G., Perry, P., & Fiebrink, R. (2022). In Generative AI and HCI - CHI 2022 Workshop.
Perry highlights the role of art in HCI, providing insights from a practitioner’s perspective to enrich interdisciplinary dialogues on the creative potential of technology.
Art in HCI: A View from the UAL Creative Computing Institute
Perry, P., Fiebrink, R., Grierson, M., Brueggemann, M. J., Doukianou, S., Plummer-Fernandez, M., & Troisi, A. (2022). In The State of the (CHI)Art - ACM CHI '22 Workshop.
Devotion Gallery: A Case Study in HCI and Digital Arts Practice
Perry, Phoenix & Schedel, Margaret & Jackson, Brian. (2013). In Chi Curatorial Practices in CHI Workshop.
Perry has significantly contributed to the development of tools and methodologies (e.g., InteractML) to make interactive machine learning accessible for artists, dancers, and movement practitioners. Their work focuses on gestural interaction, embodied play, and immersive media.
InteractML: Making Machine Learning Accessible for Creative Practitioners
Hilton, C., Plant, N., Gonzalez Diaz, C., Perry, P., et al. (2021). In VRST 2021: ACM Symposium on Virtual Reality Software and Technology.
Interactive Machine Learning for Embodied Interaction Design
Plant, N., Hilton, C., Perry, P., et al. (2021). In TEI '21: International Conference on Tangible, Embedded, and Embodied Interaction.
Programming by Moving: Interactive Machine Learning for Embodied Interaction Design
Plant, N., et al. (2020). In NordiCHI '20 Workshop on Programming for Working Bodies.
Node-Based Tool for Artists Using Interactive Machine Learning
Hilton, C., Gonzalez Diaz, C., Perry, P., et al. (2020). In NordiCHI '20: The UX of Interactive Machine Learning.
Movement Interaction Design for Immersive Media
Plant, N., Gibson, R., Perry, P., et al. (2020). In 7th International Conference on Movement and Computing (MOCO '20).
Perry’s work investigates interactive systems and their potential for expressive game design, integrating machine learning to create innovative gameplay experiences rooted in embodied interaction.
Interactive Machine Learning for More Expressive Game Interactions
Gonzalez Diaz, C., Perry, P., & Fiebrink, R. (2019). In IEEE Conference on Games (GOG) 2019.
Experimental Game Design
Perry, P., & Freidhoff, J. (2015). Open Frameworks.
Perry has authored resources to promote accessibility in creative technology development, focusing on natural user interfaces and experimental game design.
Meet the Kinect: An Introduction to Programming Natural User Interfaces
Kean, S., Hall, J.C., Perry, P., & Webb, J. (2011). Apress.
Perry explores how technology mediates human emotion and embodiment, particularly through embodied play design and ML-driven artistic systems.
User-Defined Gestural Interactions Through Multi-Modal Feedback
Perry, P., & Katan, S. (2016) In Tangible Embedded and Embodied Interactions (TEI) 2016.
Feeling the Fear: Creating Emotion through Embodied Play Design
Perry, P. (2013). Master’s Thesis, NYU Polytechnic Institute.
Wekinating Swan: Using Machine Learning in Complex Artistic Systems
Schedel, M., Perry, P., & Fiebrink, R. (2011). In NIME (New Interfaces for Musical Expression).
Embodied Games at NYU ITP
Perry, P. (2013). Interactions Magazine Blog.