Rafael Pastrana

︎  arpastrana@princeton.edu

︎ @arpastrana
︎ @arpastrana

︎ Publications

Rafael is a Ph.D. candidate in the Form Finding Lab at Princeton. He develops auto-differentiable tools for structural design, like JAX FDM and COMPAS CEM.

Rafael holds a Master of Advanced Studies in Architecture and Digital Fabrication from the Swiss Federal Institute of Technology (ETH) Zurich and a Master of Arts from Princeton.

He worked as a software engineering intern in computational geometry at Robert McNeel & Associates over the summer of 2023.

Between 2014 and 2017, Rafael worked at Bollinger + Grohmann, where he was responsible for the structural analysis and geometric rationalization of art installations in Europe and in Australia.

In 2019, Rafael worked at the Block Research Group. There, he contributed to the development of a COMPAS package to streamline the generatation of the fabrication data for one of the full-scale prototypes of the functionally-integrated, funicular floors at the NEST HiLo.

At Gramazio Kohler Research, and in collaboration with Autodesk in 2018, Rafael trained a reinforcement learning model that overcame geometrical and material inaccuracies arising during the robotic assembly of timber structures.