Suzanne Lacasse Lecture

Suzanne Lacasse Lecture Managing Risk in Geotechnical Engineering – from Data to Digitalization
Date / Time 13 December 2019, Friday / 09:00 - 09:40 hrs
Venue Room IB-101
Speaker Kok-Kwang Phoon
National University of Singapore, Singapore


Kok-Kwang Phoon, is Distinguished Professor and Vice Provost (Academic Personnel), National University of Singapore. He obtained his BEng and MEng from the National University of Singapore and his PhD from Cornell University. He is a Professional Engineer in Singapore and past President of the Geotechnical Society of Singapore. Prof. Phoon is particularly interested in developing statistical and other data-driven methods to support decision making in geotechnical engineering. He is the lead editor of 3 books: Reliability of Geotechnical Structures in ISO2394 (CRC Press/Balkema, 2016), Risk and Reliability in Geotechnical Engineering (CRC Press, 2015), and Reliability-based Design in Geotechnical Engineering (Spon Press, 2008). He was bestowed with numerous research awards, including the ASCE Norman Medal in 2005, the John Booker Medal in 2014, and the Humboldt Research Award in 2017. He is the Founding Editor of Geo risk and an advisory board member for the World Economic Forum Global Risks Report. He was elected as a Fellow of the Academy of Engineering Singapore in 2012. He was privileged to spend five months at the Norwegian Geotechnical Institute between May and September 2004, from which he developed a richer understanding of geotechnical risk management in practice from many conversations with Dr. Suzanne Lacasse and his host, Dr. Farrokh Nadim.


If you scan a page from a soil report, this is called digitization. If you deploy digital technologies, both software such as building information modeling and machine learning and hardware such as autonomous drones and additive manufacturing, to support new and more collaborative forms of project delivery, this is called digitalization. Data lies at the heart of this transformation that is targeted at re-valuing infrastructure from a “brick and mortar” asset to a service for the interests of the end-users. There is a need to view the value of data completely differently from how they are routinely used in current practice. In particular, there is a need to treat data as assets in themselves, over and above their conventional roles as inputs to a physical model or as monitoring data to trigger interventions. This paper explores the availability and nature of geotechnical data and presents two recent advances made in this direction for a specific but important task of estimating soil/rock properties (compressive sampling and Bayesian machine learning). Data-driven decision making does not imply taking the engineer out of the entire life cycle management chain. It is intended to support rather than to replace human judgment.

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