Welcome to the International Symposium 

« Machine Learning & Big Data in Geosciences »

 Wroclaw, March 15 – 17, 2021

 

Change in the Symposium venue

The Symposium initially planned in the city of Lille (France) will be organized in the city of Wroclaw (Poland). This change results from the desire of the technical committees TC 309 (Machine Learning and BigData) and TC 304  (Engineering Practice of Risk Assessment & Management) to reinforce the synergies between their members through the organization of their events (3rd International Symposium on Machine Learning and Big Data in Geosciences & Workshop on Risk Assessment in Geoengineering) under the same umbrella (MRLA – Wroclaw, March 15 – 17, 2021). 

For the general information about the conference venue and registration, kindly visit the MRLA website: MRLA – Wroclaw 2021

 

Machine Learning & Big Data in Geosciences (ISMLG – 2021)

After the great success of the first two editions of the International Symposium on Machine Learning and BigData in Geoscience ( NGI  – Oslo October 21 – 22, 2018;  and Tongji University – Shanghai July 28 – 30, 2019), the Technical Committee « Machine Learning and BigData TC309″ of the International Society for Soil Mechanics and Geotechnical Engineering (ISSMGE) is pleased to invite you to the 3rd  International Symposium on Machine Learning and BigData in Geosciences (ISMLG –2021).

This symposium aims to bring together researchers and engineers working in the field of Geosciences and Information Technology to discuss how progress in the field of BigData and Machine learning could impact engineering and research practices in geosciences. It aims also at presenting feed-backs about the use of data science in solving conventional and emerging problems in geosciences.

The symposium will focus on the following:

  • Role of data science in solving traditional and emergent problems in geosciences.
  • Progresses in data collection in geoscience (remote sensing, smart sensors, open data, social media, and mobile applications).
  • Specificities and patterns of data in geosciences, data cleaning
  • Combination of geoscience scientific-based design methods with Artificial Intelligence methods (Machine Learning and Deep Learning).
  • Role of visualization and visual analytics in geosciences
  • Needs and perspectives for the use of data in geosciences.