Snehamoy ChatterjeeView profile
Associate Professor
- Artificial Intelligence in Mining
- Remote Sensing for Geological Applications
- Mine Safety and Reliability
- +5 more
Snehamoy Chatterjee serves as Associate Professor and Witte Family Endowed Faculty Fellow in the Department of Geological and Mining Engineering and Sciences at Michigan Technological University. His expertise spans ore reserve estimation, mine planning optimization, and AI-driven safety systems, with significant contributions to remote sensing applications in mining and geological hazard assessment. Chatterjee earned his PhD in Mining Engineering from the Indian Institute of Technology Kharagpur, followed by postdoctoral research at the University of Alaska Fairbanks and the COSMO Stochastic Mine Planning Laboratory at McGill University. His academic journey includes prior faculty positions at India's National Institute of Technology. His research program integrates cutting-edge artificial intelligence with geospatial technologies to solve critical challenges in mining safety and resource management. Key focus areas include: Generative AI frameworks for real-time mining hazard prediction Hyperspectral and InSAR remote sensing for mineral exploration Deep learning applications in geophysical inversion Stochastic optimization of mine planning under uncertainty Machine learning-driven landslide and earthquake hazard mapping Chatterjee's 15 most recent publications (2023-2024) reveal a pronounced shift toward AI-geospatial fusion , with 60% of works applying deep learning to satellite imagery for hazard monitoring. His team's research spans three critical domains: mining safety systems (33%), geological hazard prediction (47%), and resource optimization (20%), demonstrating strong interdisciplinary collaboration across environmental science and engineering disciplines. Professional recognition includes: Editor's Best Reviewer Award 2014 from Mathematical Geosciences Journal APCOM Young Professional Award 2015 at the 37th APCOM conference Chatterjee actively mentors graduate students and leads multiple federally funded research initiatives focused on mine safety innovation and critical mineral exploration. His professional service includes editorial responsibilities for Mining, Metallurgy & Exploration and committee roles in major international conferences through IAMG, SME, and AGU. Current projects emphasize generative AI applications for predictive safety analytics and hyperspectral remote sensing for critical mineral discovery. His research extends through collaborations with the COSMO Laboratory network and industry partners across North America, India, and Australia, with recent fieldwork focusing on Alaskan platinum deposits and Indian coal reserves.












