Vanellus - Radically efficient CFD

Expensive simulations bottleneck product development

To reduce reliance on expensive physical testing, engineers lean heavily on CFD to optimise their designs. However, many problems across aerospace and automotive are extremely computationally expensive to simulate, taking from hours to days to run; critically slowing product development.

By developing an order of magnitude more efficient CFD solver, we will dramatically increase the productivity of engineers. This will allow engineers to efficiently search for optimal designs and therefore develop better products.

Laurence Cullen
CEO

Previously: Fetch.ai, Sensity, ARM

Laurence is a machine learning engineer of 6 years skilled at rapid prototyping and has driven two startups to seed as a first and second employee.

Whilst at Sensity, he led the development of one of the world’s first deepfake detection products from scratch, defining and implementing features in consultation with customers from Reuters and The Guardian. He leads on software design, machine learning and commercialisation.

Dr Aditi Roy
Mathematical Engineer

Previously: KCL, University of Oxford

Dr Roy joins us from her postdoc at the Oxford Department of Computer Science where she ported cardiac simulation code to run on GPUs.

She did her PhD at King's College London developing a pipeline to identify fibrosis in cardiac walls from MRI images and simulate the electrical activity behind atrial fibrillation.

She brings her knowledge of GPU computing and machine learning to improve our solver capabilities.