TC309 Machine Learning

Machine Learning and Big Data

Disseminate knowledge and practice within the TC’s subject area to the membership of the ISSMGE:

TC309 aims to provide a forum for all interested members of ISSMGE to explore the use of machine learning (ML) techniques to solve problems relevant to soil mechanics and geotechnical engineering. To disseminate and develop knowledge and practice within the area of ML in geotechnical engineering, TC309 will deal with the following important technical issues:

  1. The development of accurate, robust and efficient predictive tools based on ML methods, such as Support Vector Machine (SVM), Deep Learning (DL), Reinforcement Learning (RL) and Case-based Reasoning (CBR).
  2. The development of webinars for global training use;
  3. Producing a widely distributed newsletter for general dissemination and communication on ML;
  4. The organization of symposia and workshops with the aim to promote cooperation and exchange of information concerning research and developments in using ML in geotechnical practice;
  5. Advancing the collaboration between ML techniques and complicated geotechnical problems by showing the advantages of popular and more advanced ML methods, and by demonstrating the efficiency of these techniques applied to geotechnical engineering via organizing prediction events.

To establish guidelines and technical recommendations within the TC’s subject area:

TC309 will focus on the following actions:

  1. To set up a reference list for ML research work and books recommended by members of TC309;
  2. To prepare a State-of-the-Art paper on the use of ML in geotechnical engineering;
  3. To cooperate with other TCs to compile useful databases for determining relationships within the data, and computing parameters for analytical models that apply those relationships to the use case at hand;
  4. To establish or maintain contact with TCs having close interests such as TC304, TC103 and TC205.

Assist with technical programs of international and regional conferences organized by the ISSMGE:

  1. Organize a session on ML in the International Conference on Soil Mechanics and Geotechnical Engineering (ICSMGE) in Sydney, Australia, in 2021.
  2. Organize a joint TC309/TC304 ML workshop in 6th International Symposium on Reliability Engineering and Risk Management (ISRERM), 31 May-1 June 2018, Singapore and in 7th International Symposium on Geotechnical Safety and Risk (ISGSR), 12-13 December 2019, Taipei, Taiwan.
  3. Encourage the active participation (papers, lectures, workshops) of TC309 members at regional conferences, For example, 9th European Conference on Numerical Methods in Geotechnical Engineering 25-27 June 2018, Porto, Portugal, 17th European Conference on Soil Mechanics and Geotechnical Engineering 1-6 September 2019, Reykjavik, Iceland, and 16th Asian Regional Conference on Soil Mechanics and Geotechnical Engineering (16ARC) 14-18 October 2019, Taipei, Taiwan.  

Develop various schemes to draw the active participation of ISSMGE members. Typical examples of these include online survey of typical software packages used for their research/work, challenging problems/difficulties they have encountered or meet in their work when using ML techniques.

Interact with industry and overlapping organizations working in areas related to the TC’s specialist area:

TC309 will make efforts to reduce the gap existing between the State-of-the-Art and the State-of-the-Practice in the field of using ML techniques. TC309 will invite experienced practicing engineers to join the technical committee. They will be encouraged to organize sessions with practice-oriented topics and discussion workshops involving also academics.

TC309 will also actively seek collaborative opportunities with other ISSMGE TC's as well as other professional societies to promote the advance of applying ML techniques in geotechnical engineering. This also will involve close liaison with other ISSMGE Technical Committees.

# Type Full Name Country
1 Chair Zhongqiang Liu Norway
2 Vice Chair Mohammad Rezania United Kingdom
3 Secretary Zenon Medina-Cetina United States
4 Nominated by TC Chair Dongming Zhang China
5 Nominated by TC Chair Byron Quan Luna Norway
6 Nominated Member Lin Zhang Ireland
7 Corresponding Member Sogol Fallah Ireland
8 Nominated Member Simon BUNIESKI France
9 Nominated Member Faraz Sadeghi Tehrani Netherlands
10 Corresponding Member Michel RISPAL France
11 Corresponding Member Adel ABDALLAH France
12 Corresponding Member Jean-François MOSSER France
13 Corresponding Member Philippe REIFFSTECK France
14 Nominated Member MÁRCIO SANTOS Brazil
15 Nominated Member Michael Mygind Denmark
16 Corresponding Member Jinsong Huang Australia
17 Nominated Member Ali Karrech Australia
18 Corresponding Member Rafael Jiménez Rodríguez Spain
19 Nominated Member Germán López Pineda Spain
20 Nominated Member María Megía Spain
21 Nominated Member Vic Kumaran New Zealand
22 Nominated Member Huong Thi Thanh NGO Vietnam
23 Nominated Member Kirill Alexander Schmoor Germany
24 Corresponding Member Vikas Thakur Norway
25 Nominated Member Sigurdur Már Valsson Norway
26 Corresponding Member Santiago Peña Spain
27 Nominated Member Gilles Chapron France
28 Corresponding Member Ivan Ho Hong Kong
29 Corresponding Member Andy Leung Hong Kong
30 Nominated Member Y.H. Wang Hong Kong
31 Nominated Member Yu Wang Hong Kong
32 Nominated Member Christopher Rothschedl Austria
33 Nominated Member Michele Calvello Italy
34 Nominated Member Zijun Cao China
35 Corresponding Member Wengang Zhang China
36 Nominated Member Marco Uzielli Italy
37 Nominated Member jinhui Li China
38 Nominated Member Erdi Myftaraga Albania
39 Nominated Member Dimitrios Zekkos United States
40 Nominated Member Xiong (Bill) Yu United States
41 Nominated Member Olsi Koreta Albania
42 Nominated Member Gustav Grimstad Norway
43 Nominated Member Sukumar Pathmanandavel Australia

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Contact Technical Committee : Machine Learning and Big Data