Joshua Dimasaka is a doctoral researcher at the UKRI EPSRC Centre for Doctoral Training in the Application of Artificial Intelligence to the study of Environmental Risks (AI4ER) of the University of Cambridge. He both develops benchmark datasets and investigates artificial intelligence methods to quantify exposure and risk of the built environment at large scales, enabling the beginnings of a global risk audit. His work measures the changes in disaster risk profiles over time to assess whether countries are making progress in reducing disaster risk, ultimately to inform our collective efforts on the Sendai Framework for Disaster Risk Reduction 2015-2030.

Reducing disaster risk is interdisciplinary. Joshua received his BS in Civil Engineering (2018) from the University of the Philippines, his MS in Civil & Environmental Engineering (2022) and MA in Public Policy (2022) from Stanford University, and his MRes in Environmental Data Science (2023) from the University of Cambridge. He also took up an Executive Education Certificate in Entrepreneurship and Innovation (2021) at Stanford Graduate School of Business. He is a recipient of the Stanford Knight-Hennessy Graduate Fellowship, 2018 BPI-DOST Science Award, 2017 3rd MOCES PICE National Award, and DOST & RSFI Undergraduate Scholarships.

Joshua is a registered Filipino civil engineer, having reviewed and designed the structural integrity of high-rise buildings in the Philippines. He then worked for Stanford LBRE as a risk consultant to Dr. Eng. Fouad Bendimerad and the local government of Quezon City (Philippines) as an EMI Urban Resilience Fellow to support data-driven policies to manage earthquake risks of over 400,000 buildings. At Stanford, he worked with US Geological Survey to use machine learning on NASA satellite imagery products to improve PAGER, a global real-time earthquake hazard and loss estimation system.