My research focuses on simplifying content creation, in particular to produce highly detailed patterns, structures and shapes. Applications range from Computer Graphics to additive manufacturing (3D printing), for rendering of highly detailed scenes, for the design of complex objects, or for the modelling of technical parts that have to follow precise specifications.
The main approach I follow is to develop fast, highly controllable by-example and synthesis approaches. The resulting techniques generate new content -- images, 3D models, microstructures -- while enforcing user specified constraints. Synthesizing content automatically enables users to focus on their main design task while the algorithm produces the intricate details and enforces constraints.
Detailed content can quickly lead to large, heavy models, with files of several gigabytes in size. This hinders fast processing and visualization. Instead, I focus on methods that can quickly generate content on-demand, at the resolution it is needed and only where it is needed (e.g. for the current viewpoint). To support this line of research I investigate novel data-structures and algorithms running on parallel graphics processors (GPUs). I am also increasingly focusing on FPGA architectures, for which I develop a programming language called Silice.
Between 2012 and 2017 I lead the ERC funded project ShapeForge which was targeted at bringing complex, by-example shape generation to additive manufacturing, as well as optimizing shapes to consider fabrication and structural constraints. As we explored the generation of complex objects, we needed tools able to process these shapes and drive the 3D printers during fabrication. To achieve this goal I created the IceSL software, which simplifies the digital modeling and 3D printing of complex objects using techniques from modern Computer Graphics. IceSL is now being developed within the MFX team, which I started in 2018.