Memo Akten

Memo Akten is a researcher at Goldsmiths, University of London specializing in the application of deep learning to creative expression. He completed his doctoral thesis in 2021 titled Deep Visual Instruments: Realtime Continuous, Meaningful Human Control over Deep Neural Networks for Creative Expression, establishing his research focus on creating interactive generative systems that prioritize meaningful human control over neural networks. His work bridges computer science and artistic practice, exploring how deep learning can serve as a tool for creative expression rather than autonomous creation.

Akten's research interests center on deep learning for creative applications, with specific focus on latent space navigation, real-time interactive systems, and meaningful human control over generative models. His work consistently addresses the challenge of maintaining human agency when working with increasingly autonomous AI systems, framing neural networks as instruments to be 'played' rather than tools to be 'used.'

His publication record reveals a strong emphasis on practical implementations that enable artists to work with deep learning models in performative contexts. Notable works include Deep Meditations for controlled navigation of latent space and Learning to See which explores bias in neural networks through an artistic lens. These publications demonstrate his consistent approach to making complex AI techniques accessible for creative practitioners.

Akten has collaborated extensively with Mick Grierson (likely his doctoral supervisor) and Rebecca Fiebrink, indicating strong connections within Goldsmiths' creative computing research ecosystem. His work has been presented at prestigious venues including SIGGRAPH, NeurIPS workshops, and specialized conferences on movement computing.