Intelligent Geosystems Laboratory

Intelligent Geosystems Laboratory at SNIoE is focused to strengthening the state-of-the-art knowledge and cutting-edge technologies for intelligent sensing and data analytics for geotechnical engineering system. It aims to apply this knowledge in solving complex real-life problems of ground engineering and allied domains, and to explore new possibilities and horizons of intelligent geosystems research domain to find robust, sustainable, and resilient solutions to the complex and large-scale problems of geotechnical engineering. The lab is dedicated to transform inventions and scientific outcomes into new technology to benefit society.

The thrust areas of Intelligent Geosystems research group are:

  1. Development of cyber physical system for real time monitoring and decision making for geotechnical engineering systems.
  2. Development of physics based predictive model for geotechnical systems.
  3. Development of unified constitutive modeling for geomaterials.
  4. Development of robust computational methods for large deformation problems and seismic soil structure interaction.
  5. Risk and reliability analysis in geomechanics.
  6. Sensing and data analytics in geotechnical and structural engineering.

Laboratory Resources and Infrastructure

Intelligent Geosystems Laboratory is equipped with the cutting-edge research facilities for Geosystems Sensing, Data Visualization, and advanced computing facilities for physics-based data analytics. Computational facilities of this lab include several high-performance workstations with stand-alone Linux (Fedora and Ubuntu) and Windows Operating Systems. The lab includes the state-of-the-art IoT based sensing devices for real-time monitoring of geotechnical engineering system. Several Finite Element Analysis codes/ packages like Abaqus, Plaxis 3D, Open Sees, GiD; programming platforms such as MATLAB, OCTAVE, SPYDER (PYTHON), etc., in addition to self-developed codes for probabilistic characterization of soil spatial variability and optimization, are available in the lab.

Ongoing Research:

  1. Probabilistic Characterization of Spatial Variability of Ground using Bayesian Learning based Data Analytics Technique
  2. Seismic Analysis and Design of Caisson Foundation Supporting Bridge Piers with Soil-Structure Interaction Effects
  3. Development of cyber physical system for real time monitoring and decision making for geotechnical engineering systems

Images from the lab


  1. Gyan Vikash, Associate Professor
  2. Ashu Singhal, PhD Research Scholar
  3. Abhishek Dixit, PhD Research Scholar
  4. Saksham Dhashmana, PhD Research Scholar