AUST'S Charles Komadja Defends Ph.D Thesis

Abuja, August 13, 2025 — Charles Komadja, of the Department of Materials Science and Engineering at the African University of Science and Technology (AUST) has successfully defended his Ph.D thesis.

The thesis defense which took place at the Computer lab Video conferencing room was conducted via hybrid was attended by a panel of supervisors including the President of AUST, Professor Azikiwe Peter Onwualu, FAS, Director, Academic Planning; Dr. Abdulhakeem Bello; Dr. Vitalis Anye, Acting Dean, School of Engineering, Prof. Erik Westman, Dr. Rana Aditya, Prof. Gerrald d' Almeida, Prof Nicoise Yalo.

Komadja’s research focuses on the application of machine learning techniques to improve mining engineering practices.

His work was sub-divided into two main projects namely the evaluation of the influence of blast design parameters on ground vibration, specifically Peak Particle Velocity (PPV), aiming to select sensitive parameters through a machine learning approach and the application of machine learning to lithology classification in mining, utilizing measurement while drilling (MWD) and exploration data.

The work examined early exploration data, integrating spatial coordinates (X, Y, Z), and employing classifiers such as Support Vector Machines (SVM), Random Forest (RF), and Extra Gradient Boosting (XGBoost) for improved prediction accuracy.

During the course of the defense, Komadja acknowledged the mentorship and support of Prof. Erik Westman, Dr. Vitalis Anye, and Dr. Rana Aditya throughout his research journey. He also thanked committee members Prof. Gerard d’Almeida, Prof. Nicaise Yalo, and Dr. Bello Abdulhakeem, along with financial supports from the Regional Scholarship and Innovation Fund (RSIF) and TWAS-CSIR Postgraduate Fellowship Program.

Upon completing his presentation, Charles Komadja faced rigorous questions from the panel, including a detailed inquiry from Professor Azikiwe Peter Onwaulu, President of the African University of Science and Technology, who sought to identify the properties of his predictive model.

The research holds promise for advancing sustainable mining practices and geological modeling through the integration of AI and data-driven approaches, potentially transforming mineral processing and mining safety standards.

In conclusion, the panel unanimously approved his thesis and then afterwards declared him a Doctor of Philosophy in his field of work.