معرفی
Bernardo Francisco is a researcher specializing in machine learning and human-computer interaction with a focus on applications in music technology and creative industries. He completed his doctoral studies at Goldsmiths, University of London in 2020, conducting a three-year longitudinal action research study within the EU H2020-funded RAPID-MIX project.
His research centers on making machine learning accessible to creative developers through user-centered design of development tools. Francisco has pioneered evaluation frameworks for machine learning APIs, particularly focusing on rapid prototyping needs in music technology. His work bridges complex machine learning algorithms with practical applications for creative practitioners who may lack deep ML expertise.
Francisco's publications reveal consistent focus on usability evaluation, with studies involving cognitive dimensions questionnaires delivered to software developers. His research demonstrates that well-designed ML APIs significantly enhance the developer experience for music technology creation, enabling both personal projects and commercial software development.
He has collaborated extensively with Michael Zbyszynski, Mick Grierson, and Rebecca Fiebrink, contributing to both academic publications and practical tool development. His work spans multiple venues including Frontiers in Artificial Intelligence, Journal of Science and Technology of the Arts, and specialized conferences on machine learning user experience.
Francisco Bernardo در سایتهای دیگر
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- RRebecca FiebrinkGoldsmiths , University of London · استاد
- MMick GriersonGoldsmiths , University of London · پژوهشگر
- RRebecca FiebrinkUniversity of the Arts London · استاد
- TTerence BroadGoldsmiths , University of London · پژوهشگر
Sean McGrathGoldsmiths , University of London · مدرس- MMick GriersonUniversity of the Arts London · استاد