Date: 27 August 2024, Tuesday

Time: 6:30 pm – 7:30 pm

Venue: Chan Yat Mei Sophie Room, HKIE Headquarters, 9/F Island Beverley, No. 1 Great George Street, Causeway Bay, Hong Kong

Speaker: Stephen Wu, Associate Professor, The Institute of Statistical Mathematics, Tokyo

Synopsis:

In this talk, Dr. Wu will explore the critical challenges faced when applying machine learning to real-world civil engineering tasks. These challenges include the high uncertainty inherent in the data, and the frequent lack of numerical data. To address these issues, the talk will introduce two frameworks that make use of the concepts of transfer learning and foundation models, such as large language models (LLMs), as potential solutions. Examples from previous research work in civil engineering will be provided to illustrate how these advanced machine learning techniques can be effectively employed to overcome the obstacles that limit the application of machine learning in this domain.

About the Speaker:

Stephen Wu is an Associate Professor at The Institute of Statistical Mathematics in Tokyo, Japan, who has dedicated his research career to solving real-world problems using statistical machine learning methods. After completing his doctoral program at the California Institute of Technology, he worked in various research fields (e.g., materials science, seismology, and civil engineering) and gained extensive experience in international and interdisciplinary collaborative research projects. His achievements in the application of statistical machine learning have been highly recognized in Japan, leading to his receipt of the Young Scientists’ Prize in the field of science and technology, awarded by the Minister of Education, Culture, Sports, Science, and Technology in 2023.

No registration is required.

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CPD certificates will be issued.

Submissions for the Best Reporter Award are invited. Report must be submitted to hkiestructuraldivision@gmail.com within two weeks after the seminar.