Research and Publications

My research focuses on leveraging advanced computational techniques, particularly machine learning, to address complex challenges in geotechnical engineering. My work spans several key areas:

  • Application of machine learning to solve intricate geotechnical problems

  • Reliability-based design in geotechnical engineering

  • Design optimization and robust geotechnical solutions

  • Uncertainty quantification and risk assessment

  • Enhancement of subsurface exploration using machine learning techniques

  • Development of explainable AI for geotechnical applications

  • Integration of physics-based machine learning for geotechnical structures

Research Highlights

Soil stratification using machine learning

Robust geotechnical design of rigid pavement

Optimizing XGBoost algorithm for soil liquefaction prediction

Hierarchical Bayesian Modeling for geotechnical correlation

Selected Peer-Reviewed Journal Papers

  • Sadik L., Al-Jeznawi D., Al-Janabi MAQ, Alzabeebee S. (2024). “Prediction of seismic-induced bending moment and lateral displacement in closed and open-ended pipe piles: A genetic programming approach.” Artificial Intelligence in Geosciences.

  • Sadik L., Al-Jeznawi D., Al-Janabi MAQ, Alzabeebee S. (2024). “An Explicit Model for Soil Resilient Modulus Incorporating Freezing-Thawing Cycles Through Offspring Selection Genetic Algorithm (OSGA).” Transportation Infrastructure Geotechnology Journal.

  • Sadik, L., & Samui, P. (2024). "Uncertainty-Aware Prediction of Bearing Capacity of Shallow Foundations Resting on Cohesionless Soils Using Bayesian Regression." Geotechnical and Geological Engineering, 1-19.

  • Al-Jeznawi, D., Sadik, L., et al. (2023). "Developing Vs-NSPT Prediction Models Using Bayesian Framework." Transportation Infrastructure Geotechnology Journal.

  • Sadik, L. (2023). "Developing Prediction Equations for Soil Resilient Modulus Using Evolutionary Machine Learning." Transportation Infrastructure Geotechnology Journal.

  • Albusoda, B. S., & Al-Anbary, L. (2016). "Performance Assessment of Pile Embedded in Expansive Soil." Al-Khwarizmi Engineering Journal, 12(2), 1-9.

  • Al-Busoda, B. S., & Al-Anbarry, L. (2014). "Wetting-Drying Cycles Effect on Piles Embedded in a Very High Expansive Soil." WASET Journal of Civil and Environmental Engineering.

Selected Peer-Reviewed Conference Papers

  • Sadik, L., Khoshnevisan, S. (2024), “Improved Estimation of California Bearing Ratio value from Dynamic Cone Penetrometer Test Data Using Hierarchical Bayesian Modeling.” GeoCongress 2024.

  • Sadik, L., Khoshnevisan, S. (2024), “Simplicity vs Complexity in Machine Learning Models – Focusing on Soil Resilient Modulus Prediction.” GeoCongress 2024.

  • Sadik, L., Khoshnevisan, S. (2024), “Predicting Soil Liquefaction Potential Using XGBoost Algorithm with Bayesian Hyperparameters Optimization.” GeoCongress 2024.

  • Khoshnevisan, S., Sadik, L. (2023), “Developing SPT-CPT Correlation Models using Hierarchical Bayesian Approach.” Rocscience International Conference (RIC) 2023.

  • Sadik, L., Khoshnevisan, S., Athar, M. (2023), “Reliability-Based Robust Design Framework for Rigid Pavements.” GeoCongress 2023: Geotechnical Systems from Pore-Scale to City-Scale.

  • Athar, M., Khoshnevisan, S., Sadik, L. (2023), “CPT-Based Soil Classification through Machine Learning Techniques.” GeoCongress 2023: Geotechnical Systems from Pore-Scale to City-Scale.

Patents

  • Wetting-Drying Cycles Device for Soil Samples. Central Organization for Standardization and Quality Control, Iraq – Baghdad International Classification – E21B49/02 – 201.

Presentations

  • Sadik, L., Khoshnevisan, S. (2024), “Improved Estimation of California Bearing Ratio value from Dynamic Cone Penetrometer Test Data Using Hierarchical Bayesian Modeling.” GeoCongress 2024.

  • Sadik, L., Khoshnevisan, S. (2024), “Simplicity vs Complexity in Machine Learning Models – Focusing on Soil Resilient Modulus Prediction.” GeoCongress 2024.

  • Sadik, L., Khoshnevisan, S. (2024), “Predicting Soil Liquefaction Potential Using XGBoost Algorithm with Bayesian Hyperparameters Optimization.” GeoCongress 2024.

  • Khoshnevisan, S., Sadik, L. (2023), “Developing SPT-CPT Correlation Models using Hierarchical Bayesian Approach.” Rocscience International Conference (RIC) 2023.

  • Sadik, L., Khoshnevisan, S., Athar, M. (2023), “Reliability-Based Robust Design Framework for Rigid Pavements.” GeoCongress 2023: Geotechnical Systems from Pore-Scale to City-Scale.

Research profiles