Bright Sparks Lecture - The Hong Kong Institution of Engineers (HKIE) Geotechnical Division 43rd Annual Seminar, 2023

Bright Sparks Lecture - The Hong Kong Institution of Engineers (HKIE) Geotechnical Division 43rd Annual Seminar, 2023

The YMPG in collaboration with the Organising Committee for the The Hong Kong Institution of Engineers (HKIE) Geotechnical Division 43rd Annual Seminar, 2023, would like to announce the winner of the Bright Spark Lecture Award to threr distinguished young geotechnical engineers/academics: Te Xiao. He is invited to give keynote lectures on 19 May 2023.

  1. Te Xiao, Research Assistant Professor, Geotechnical Engineering, Hong Kong University of Science and Technology (HKUST), Hong Kong
    Bright Spark Lecture Title: "Machine learning-powered landslide forecasting: from initiation to mobility"

The Bright Spark Lecture Award was established to promote young members of the ISSMGE to play a major role in various international and regional conferences. Recipients of this award are invited to give a keynote lecture at ISSMGE conferences. All Technical Committee conference organisers and Member Society conference organisers are encouraged to select Bright Spark Lecturers at their conferences. Details regarding the award can be found on the ISSMGE website: https://www.issmge.org/the-society/awards/bright-spark-lecture-award.

We invite everyone, especially young geotechnical engineers, to come and enjoy the lectures. We hope these lectures can inspire and motivate us further to excel in our beloved field, geotechnical engineering.

 

Winners Bio

 

Te Xiao

Dr. Te Xiao is currently the Research Assistant Professor, Geotechnical Engineering, Hong Kong University of Science and Technology (HKUST), Hong Kong. Previously, he completed his doctorate study in Hydraulic Structure Engineering from Wuhan University, China. His research interests include geotechnical risk and reliability, probabilistic site characterization and modeling, multi-hazard risk management, sustainable land reclamation, and machine learning and digital modeling.