SQUISHBOI is a continuous touch controller for interacting with complex musical systems. An elastic rubber membrane forms the playing surface of the instrument, while machine learning is used for dimensionality reduction and gesture recognition. The membrane is stretched over a hollow shell which permits considerable depth excursion, with an array of distance sensors tracking the surface displacement from underneath. The inherent dynamics of the membrane lead to cross-coupling between nearby sensors, however this is not a flaw or limitation. Instead this coupling gives structure to the playing techniques and mapping schemes chosen by the user. The instrument is best utilized as a tool for actively designing abstraction and forming a relative control structure within a given system, one which allows for intuitive gestural control beyond what can be accomplished with conventional musical controllers. SQUISHBOI was developed as a project for the Interface Design course at CalArts and was awarded the Ableton Award at the 2019 CalArts Expo. A peer review of SQUISHBOI and the unique technology behind it will be published in July in the proceedings of the International Conference on New Interfaces for Musical Expression (NIME 2020).