On June 24, 2022, the International symposium, Machine Learning and Innovative Techniques in Geohazard Prevention & Control, hosted by Chongqing University (CQU), Norwegian Geotechnical Institute (NGI), Committee on Machine Learning and Big Data (TC309) of International Society for Soil Mechanics and Geotechnical Engineering (ISSMGE), was successfully held on Zoom with more than 130 people participation. This symposium was presided over by Zhang Wengang, the associate chair of SCE, and Liu Zhongqiang, the researcher of NGI.
At the opening ceremony, Prof. Yang Qingshan, chair of SCE, delivered a welcome speech to the experts and scholars attended this symposium on behalf of SCE, CQU, and also introduced SCE, and then pointed out that machine learning method and algorithm is the basic support technology in natural science and engineering technology. Then Prof. Dominik Lang, director of NGI, on behalf of NGI warmly welcomed all the participants and also brief introduced NGI. Soon afterwards, NGI researcher Liu Zhongqiang, the chair of TC309 of ISSMGE, on behalf of TC309 of ISSMGE gave a background introduction of this symposium.
Later, researchers Sylfest Glimsdal, Kjersti Gisnås, Rosa Maria Palau Berastegui, Hervé Vicari, Mats Kahlström from NGI, Prof. Lu Xinzheng from Tsinghua University, Prof. Mei Gang from China University of Geosciences (Beijing), Prof. Dou Jie from China University of Geosciences (Wuhan), Researcher Fu Jie from Hydrogeological Environmental Geological Survey Center of China Geological Survey, Prof. Wen Haijia, Prof. Yang Haiqing, Dr. Wang Luqi from Chongqing University, who are renowned experts and scholars in the field of machine learning for geotechnical disaster prevention and control, conducted keynote speeches respectively to introduce the latest research progress and application in related fields.
The closing ceremony was presided over by Prof. Wang Rui from Tsinghua University, he is also the director of Young Engineer Work Committee of Chinese Institution of Soil Mechanics and Geotechnical Engineering. He sincerely thanked all the reporters and participants, and expressed that he regarded the successfully holding of this symposium has aroused researchers’ strong interest in machine learning methods and strengthened the communication between professors, experts, scholars and students.