Publications & Presentations
A comprehensive list of my academic publications in peer-reviewed journals and presentations at international conferences, categorized for clarity.
Explainable Artificial Intelligence Estimation of Maximum Dry Density in Soil Compaction Based on Basic Soil Properties and Compaction Energy
Authors: Rodney Ewusi-Wilson, Jerome Anabannye Yendaw, Sylvanus Sebbeh-Newton, Emmanuel Ike & Felix Jojo Fianko Ayeh | Transportation Infrastructure Geotechnology | 2025
Published the parametric study of the various input rock parameters revealed that the most sensitive parameter to the total displacement and yield zone depth. This study has thus concentrated on creating explainable AI-based models for forecasting MDD.
Real-time classification of ground conditions ahead of a TBM using supervised machine learning algorithms
Authors: Sylvanus Sebbeh-Newton, Jamel Seidu, Mawuko Luke Yaw Ankah, Rodney Ewusi-Wilson, Hareyani Zabidi & Louis Amakye | Modeling Earth Systems and Environment | 2025
Accurately predicting the ground conditions ahead of a tunnel boring machine (TBM) in real-time is crucial for preventing geological hazards as well as for the adaptive adjustment of TBMs. The results suggest that ERT has the potential to correctly predict rock masses conditions ahead of a TBM in real-time by utilizing TBM operation parameters.
The Use of Interpretable Artificial Intelligence Inferences in the Estimation of Optimal Moisture Content Utilizing Basic Soil Parameters
Authors: Rodney Ewusi-Wilson, Jerome Anabannye Yendaw, Sylvanus Sebbeh-Newton, Emmanuel Ike & Felix Jojo Fianko Ayeh | Indian Geotechnical Journal | 2024
Published SVR OMC model was determined to be the best utilizing interpretable AI (IAI) since it has a high degree of generalizability and is compatible with engineering and physical concepts. This study has thus concentrated on creating interpretable AI-based models for forecasting OMC utilizing liquid limit, plastic limit (PL), gravel fraction, sand fraction (SF), clay fraction (CF), and compaction energy from a broader range of soil data as input data.
Artificial intelligence-optimized design for dynamic compaction in granular soils
Authors: Rodney Ewusi-Wilson, Changho Lee & Junghee Park | Acta Geotechnica | 2023
Published four AI algorithms used in this study involve artificial neural network ANN, support vector regression SVR, gradient boosting machine GBM, and random forest RF. This study presents a novel procedure and mathematical model employing four artificial intelligence AI algorithms to predict the cumulative degree of soil compaction CDSC during dynamic compaction DC.
Geostatistics and Artificial Intelligence Applications for Spatial Evaluation of Bearing Capacity after Dynamic Compaction
Authors: R. Ewusi-Wilson, Junghee Park, Boyoung Yoon, Changho Lee | Advances in Civil Engineering | 2022
This study employs geostatistical and artificial intelligence (AI) methods to estimate the degree of ground improvement after dynamic compaction. This unique approach for evaluating the efficiency of dynamic compaction will be useful to geotechnical engineers when designing site improvement projects, especially dynamic compaction by employing easily obtainable field data for coarse-grained soils.
Effect of Specific Surface, Mineralogy, and Pore-Fluid Chemistry on Fine-Grained Soil Classification Based on Plasticity and Electrical Sensitivity
Authors: E Ike, J Park, R Ewusi-Wilson, C Lee | Geotechnical and Geological Engineering | 2025
Published research on applying physics and chemistry modeling for engineering studies of clay behaviour in Geotechnical and Geological Engineering. Focused on the physics and chemistry behaviour of clay soils.
Probabilistic analysis of underground rock excavation stability using point estimate method
Authors: Sylvanus Sebbeh-Newton, Jamel Seidu, Rodney Ewusi-Wilson & Hareyani Zabidi | Modeling Earth Systems and Environment | 2025
Published the parametric study of the various input rock parameters revealed that the most sensitive parameter to the total displacement and yield zone depth. This study analyzed the effect of uncertainties in the peak and post-peak rock mass mechanical parameters on the displacement and the plastic zone depth.
Artificial intelligence and Geostatistics Applications in Consolidation Layer Thickness Prediction
Authors: R. Ewusi-Wilson Junghee Park, Changho Lee | KSCE Convention 2023 | 2023
This is a conference proceeding and presentation for Artificial intelligence and Geostatistics Applications in Consolidation Layer Thickness Prediction.
Dynamic Compaction Design Applying Artificial Neural Network to Estimate the Degree of Ground Improvement
Authors: R. Ewusi-Wilson Junghee Park, Changho Lee | KSCE Convention 2022 | 2023
This is a conference proceeding and presentation for Dynamic Compaction Design Applying Artificial Neural Network to Estimate the Degree of Ground Improvement.
Prediction of Dynamic Compaction Crater Depths by Artificial Intelligence Method
Authors: R. Ewusi-Wilson Junghee Park, Boyeong Yoon, Changho Lee | KSCE Convention 2023 | 2023
This is a conference presentation and proceeding for Prediction of Dynamic Compaction Crater Depths by Artificial Intelligence Method .
Investigation of the Structure-Soil-Structure Interaction Between Two Structures in Centrifuge Test
Authors: Van-Linh Ngo, Rodney Ewusi-Wilson & Emmanuel Ike | Geotechnics for Sustainable Infrastructure Development | 2019
This is a conference presentation and proceeding for dynamic soil-structure interaction and structure-soil-structure interaction (SSSI) between two structures were investigated using the dynamic geo-centrifuge machine at KAIST, South Korea.