Dr. Rebecca Fiebrink

Dr. Rebecca Fiebrink

Dr Rebecca Fiebrink is currently a Senior Lecturer in Computing at Goldsmiths, University of London. She is the original creator of Wekinator, an open source software project that allows users to build new interactive systems by demonstrating human actions and matching them to computer responses, instead of writing code.

Accompanied by her students and research assistants, Fiebrink works on projects that develop technologies that enable new forms of human expression, creativity, and embodied interaction.

Dr Fiebrink’s work draws on, and contributes to, fields such as human-computer interaction, machine learning, and signal processing with an aim to allow people to apply machine learning more effectively to new problems, such as the design of new digital musical instruments and gestural interfaces for gaming and accessibility.

She is affiliated with the Embodied AudioVisual Interaction (EAVI) group.

Keynote: Using Data and Machine Learning to Support Human Creative Practices

Machine learning algorithms are now capable of creating new images, sound, and other media content, which we can reasonably call novel, sophisticated, and even compelling. What do these algorithms mean for the future of human creative practice? Will all of us soon sit at home watching algorithmically-generated music videos after robots take our jobs? In this talk, I will show how machine learning is instead opening doors to new forms of human creative expression. For instance, by modeling data that captures how we move, play, and make art and music, machine learning algorithms can help computers better understand our most expressive human activities. Furthermore, these algorithms can augment human capabilities by allowing people to more easily discover and explore new ideas. By enabling more natural ways for humans to express their ideas to machines, machine learning can even make it easier for more people to engage in creative work and technical innovation. This talk will include live demonstrations of machine learning used to make new musical instruments and interactive art.

Dr Sarah Morris

Dr. Teresa Dillon

Originally trained as a social and educational psychologist. Teresa Dillon is a self-taught artist and curator. Drawing on methodologies from psychology, social science and the performing arts, her work reflects on our cybernetic attachments and the influence of techno-civic systems on our everyday lives and personal relationships. Recent work includes the exhibition YOU MIGHT BE A DOG (2014), the installation ADIP (2014), the web authoring tool and personal server, Superglue (2014) and the programme of talks and workshops Urban Knights (2013+). From 2012-2013 she was curator and course coordinator at the Science Gallery, Dublin, where she curatedHACK-THE-CITY, developed various urban labs and taught the science-art curriculum. Her works has been shown internationally at various festivals and exhibitions (Transmediale, Ars Electronica, ISEA, Pixelache, Enter_)and she has published widely on technology, creativity and learning. Teresa holds a PhD in psychology from The Open University, UK and is currently a Humboldt Fellow at UdK and TU, Berlin.