I joined the Form Finding Lab in September 2021 to pursue a Ph.D. in Civil Engineering. Previously, I did an integrated BSc degree in Architecture and Engineering at Chalmers University of Technology in Gothenburg, Sweden. Following graduation, I did a computational design internship at Design-to-Production in Zürich, Switzerland and an architectural engineering internship at Jan Knippers Ingenieure in Stuttgart, Germany. For my master’s studies, I did the research master programme in Architecture and Digital Theory at The Bartlett School of Architecture, London, UK. The topic of my thesis was Physics Informed Machine Learning (PIML) for structural engineering. PIML is a novel technique where prior physics knowledge is incorporated into a machine learning model to make more accurate predictions with greater generalizability. A large part of my studies were conducted as a research internship at TNO Delft where I did a realistic study of the applicability of PIML for structural health monitoring.
I’m broadly interested in programming and mathematics and how to create digital tools to design smarter structures. During the course of my PhD I will continue my work on Machine Learning and to conduct research on, and develop methods to predict the behavior of elastic rod networks.