Dr Pei-Yuan Hsu

Contact

Email: p.hsu@kingston.ac.uk
Location: Penrhyn Road
Faculty: Faculty of Engineering, Computing and the Environment
School: School of Engineering and the Environment
Department: Department of Civil Engineering, Surveying and Construction Management

About

Pei-Yuan Hsu was a research associate at Imperial College London 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.

Academic responsibilities

Lecturer in Built Environment

Qualifications

Imperial College London, Dyson School of Design Engineering (Doctor of Philosophy, 2015-2019), London, United Kingdom
National Chiao Tung University, Department of Civil Engineering (Master of Science, 2012-2013), Hsinchu Taiwan
National Chiao Tung University, Department of Civil Engineering (Bachelor of Science, 2007-2011), Hsinchu, Taiwan

Research

Current Research Interests

Construction and Logistics

Applying two-stage stochastic programming model in determining the optimal supply chain configuration in modular construction.

Employing robust optimisation to reveal the optimal strategy for establishing consolidation centres in modular construction projects.

Applying mixed-integer linear programming model to find out the best emergency supply chain plan in response to abrupt demand disruptions.

Applying mathematical modelling techniques to determine the optimal outsourcing strategy under uncertain productivity for prefabricated infrastructure projects.

Optimising the deployment of wireless charging lane for electric buses under uncertain energy consumption by using stochastic programming techniques.

Investigating schedule deviation factors in construction projects through root cause analysis.

BIM

Using BIM to assist the "as-built" engineering and the construction process of modularised buildings.

Integrating BIM and quantity take-off tools for accurate estimation of the quantities and prices of construction material.

Using 3D BIM in visualising and checking the problems that may occur during the assembly process of the prefabricated building components.

Using BIM to optimise the modularisation scheme of a building project.