Dr.-Ing. BOROH ANDRÉ WILLIAM,

Courses Taught at the School of Geology and Mining Engineering: Mining and oil deposit modelling, Estimations, Simulationss, Modelling and process simulation  in the assessment of soil, water, and sediment contamination in mining sites, Data analysis and Data Science.

Boroh William is Junior Lecturer at the Department of Mines and Geology at the School of Geology and Mining Engineering of the University of Ngaoundere.

His research focuses on the application of geostatistical and machine learning techniques to address various challenges in mineral exploration and environmental geochemistry. He is the author and co-author of several scientific articles, the main ones being the following:

• Geostatistical modelling: He worked on the impact of geological domain data on modelling and estimating resources at the Nkout iron deposit in southern Cameroon. Geological domains were identified and block modelling was performed to estimate resources, with grade estimation using ordinary kriging and composites within each domain.

• Mineral Exploration and Mapping:

  1. • Gold: He employed geostatistical techniques like ordinary cokriging and machine learning algorithms, such as support vector machines, to map gold mineralization in the Tikondi gold permit.

     • Iron: He developed innovative methods for 3D variogram modeling using analytical geometry, which has been applied to the Nkout iron deposit. I have also compared the performance of geostatistical and machine learning models for predicting iron concentrations in this deposit.

     • Tin, Niobium, and Tantalum: He investigated the structural controls and predictive mapping of these minerals associated with the Mayo Darlé stanniferous granitoids, leveraging geostatistical approaches.

   

• Environmental Geochemistry;

  1. • Trace Metals and Pollution Indices: He combined geostatistical and machine learning methods to assess the spatial distribution of trace metals and pollution indices in sediments from an abandoned gold mining site in Bekao, Adamawa, Cameroon.

• Geochemical Data and Exploration:

  1. • Gold Pathfinder Elements: He contributed to the compilation and analysis of geochemical datasets of laterite soils in the Koubou gold district, aiming to identify potential gold pathfinder elements.                                                                         ff

       Future Research Directions

       He planes to continue exploring the application of advanced geostatistical and machine learning techniques to address complex geological problems. Future research directions include:

       • Integration of Remote Sensing Data: Incorporating remote sensing data to enhance mineral exploration and environmental monitoring.

       • Uncertainty Quantification: Developing robust methods to quantify uncertainty in mineral resource estimates and environmental assessments.

       • Sustainable Mining: Applying data-driven approaches to optimize mining operations and minimize environmental impact.

       By combining innovative methodologies and interdisciplinary collaboration, he aims to contribute to the sustainable development of mineral resources and the protection of the environment.