Abstract

In this talk, I will provide a brief geological background to GIS-based mineral potential modeling and review some of the GIS-based spatial analyses techniques used for generating input data for modeling. I will then summarize various knowledge-driven and data-driven aproaches to mineral potential modeling, focussing on aritifical intelligence techniques including expert systems and machine learning algorithms. Finally I will discuss some real-world case studies on applications of machine learnign and expert systems to modeling the potential of various types mineral deposits.

Presenter Profile

Alok is a full professor at the Centre for Studies in Resources Engineering at IIT Bombay in India. He is a PhD in mathematical geology from the Utrecht University, the Netherlands, and was working at the University of Western Australia prior to joining IIT Bombay, where he continues to hold the adjunct professor positon. His core research interests include remote sensing and spectroscopy of terrestrial and planetary surfaces, predictive geospatial modelling, and genesis of uranium and gold mineral systems. He also works in machine learning and soft computation, particularly for geological applications. Basically an academic, he works very closely with the industry and has been involved in a large number of projects for mining industry in Australia, Africa and India, and is an expert advisor to International Atomic Energy Agency on uranium exploration. An internationally recognized and acclaimed researcher, he has published over 60 highly cited papers in international journals, in addition to being in the editorial boards of several high-impact international journals. But foremost, Alok is a dedicated and popular teacher. He has been recently conferred IIT Bombay’s Professor SM Sukhatme Award for Excellence in Teaching.