Evaluation of Dynamic Properties of Liquefaction-Susceptible Sand Using Shaking Table Tests (2023-2025)

Conducted a series of shaking table tests to evaluate the cyclic properties of dry and saturated liquefaction-susceptible Kasai River sand. 

Seismic Performance of Pile Foundations Partially Embedded Within Hill Slope (2021-2025) 

Conducted a series of shaking table tests on scaled model piles to study their seismic performance when installed within the slopes. These tests provided valuable insights into the behavior of piles installed within the slopes under dynamic loading conditions. In addition to the experimental work, extensive numerical modeling using PLAXIS was also carried out to study the effects of various parameters on pile performance.

Modeling of Geotechnical Problems Using Machine Learning Techniques (2018-2019)

Implemented advanced Machine Learning techniques, including Artificial Neural Networks (ANN), Multivariate Adaptive Regression Splines (MARS), and Gene Expression Programming (GEP), on collected datasets to develop predictive equations for key geotechnical parameters. These equations accurately predict geotechnical parameters such as liquefaction indexes, settlement, and the bearing capacity of shallow foundations.