GEMS lab focuses on Geo-energy and Geo-materials including carbon dioxide sequestration, geothermal energy, hydraulic stimulation, and their engineering implications. We try to explore the challenging and unanswered topics to expand our knowledge and to produce the distinguished and creative young scholars in Geotechnical engineering.
Current research area investigated by GEMS includes;
Deep-learning based analysis of geotechnical visions and images
Optimization of tunnelling by artificial neural network
Prediction of stress-strain evolution by neutral network
Optimization and characterization of multi-phase fluid flow (e.g., contaminants, hydrocarbon recovery and storage)
Sustainable and tunable engineered soils
We are currently moving to the new scope - "Digital Geotechnics" based on big-data, deep learning, geotechnical images, and high-performance computing.