Pei-Yuan Hsu is a Research Associate at the Transport Systems and Logistics Laboratory and the Alan Turing Institute. His research focuses on the data-driven design of civil infrastructure under uncertainty to support emerging modes of urban mobility.

He holds a PhD from the Dyson School of Design Engineering at Imperial College London, which he carried out in affiliation with the Centre for Systems Engineering and Innovation. His research focused on the optimal design of modular construction supply chains under conditions of uncertainty, making use of stochastic programming and robust optimisation. Previously, he obtained an MSc and BSc at the Department of Civil Engineering at National Chiao-Tung University (Taiwan). He also has industrial experience as a Site Engineer and BIM Practitioner with Taiwan Photon Source.

Pei-Yuan is currently focusing on the development of stochastic programming techniques for the design of flexible Demand Responsive Transport Systems (DRTs) for electric and autonomous vehicles. His models make extensive use of Machine Learning technologies to identify patterns in customer activity and facilitate the optimal use of shared vehicles and the underlying transport infrastructure.