Snehamoy Chatterjee

Contact

schatte1@mtu.edu
906-487-2516
Dow 625

Associate Professor, Geological and Mining Engineering and Sciences
Witte Family Endowed Faculty Fellow in Mining Engineering

PhD, Mining Engineering, Indian Institute of Technology Kharagpur, India

Biography

Snehamoy Chatterjee is an Associate Professor of Department of Geological and Mining Engineering and Sciences, Michigan Tech. Before joining Michigan Tech, Chatterjee was working as an Assistant Professor at National Institute of Technology, India. Chatterjee specializes in ore reserve estimation, short- and long-range mine planning, mining hazards, reliability, and safety analysis, and the application of remote sensing and artificial intelligence in mining problems. He received his PhD in Mining Engineering from Indian Institute of Technology Kharagpur, India.

During his PhD research, Chatterjee solved quality control-related problems using remote sensing and geostatistical methods. Chatterjee then worked as a Post-Doctoral Fellow at the University of Alaska Fairbanks where he worked primarily on ore reserve estimation of gold and platinum resources off the coast of Alaska. Thereafter, he joined the COSMO Stochastic Mine Planning Laboratory at McGill University, Canada, where he focused on mine planning optimization and ore-body modeling under uncertainty. He completed ore body and rock-type modeling projects of several other mining operations in India, Australia and Canada.

Presently, Chatterjee is actively involved in research work in the field of hyperspectral and InSAR remote sensing for mining and geological applications, generative AI for mine safety, and inverse modeling using deep learning. He is teaching courses on topics related to mine planning, mineral resource modeling, mining optimization and reliability, and geostatistics and data analysis. He has completed a number of sponsored research and industry projects in these fields for different federal agencies.

Chatterjee is an active member of the International Associate of Mathematical Geosciences (IAMG), the Society for Mining, Metallurgy and Exploration, Inc. (SME), the American Geophysical Union (AGU). He has served as a co-convener and a technical committee member for several international mining conferences. He has received The Editor's Best Reviewer Awards 2014 from Mathematical Geosciences Journal. He is the recipient of the 2015 APCOM Young Professional Award at the 37th APCOM in Fairbanks, Alaska. He is an Associate Editor of Mining, Metallurgy & Exploration Journal. He was a member of Michigan Mining Future Committee.

Links of Interest

Research Interests

Generative AI for mine safety
Remote sensing for critical mineral exploration
InSAR for mining hazards
Geophysical inversion using deep learning
Stochastic resource modeling and stochastic optimization in mining

Teaching Interests

Mine Planning and Design
Mineral Resource Estimation
Mining System Reliability and Optimization
Geostatistics and Data Analysis

Recent Publications (2023-2024)

Eshwar, D., Chatterjee, S., Kaunda, R., Miller, H., & Majdara, A. (2024). An Information Entropy–based Risk (IER) Index of Mining Safety Using Clustering and Statistical Methods. Mining, Metallurgy & Exploration, 41(4), 1693-1708.
Vishnu, C. L., Oommen, T., Chatterjee, S., & Sajinkumar, K. S. (2024). Addressing the Effect of Intra-Seasonal Variations in Developing Rainfall Thresholds for Landslides: An Antecedent Rainfall-Based Approach. GeoHazards, 5(3), 634-651.
Asadi, A., & Chatterjee, S. (2024). Pixel-MPS: Stochastic Embedding and Density-Based Clustering of Image Patterns for Pixel-Based Multiple-Point Geostatistical Simulation. Geosciences, 14(6), 162.
Nelson, K. M., Jiménez, C., Deering, C. D., de Moor, M. J., Blackstock, J. M., Broccardo, S. P., ... & Hernandez, C. (2024). Total CO2 budget estimate and degassing dynamics for an active stratovolcano: Turrialba Volcano, Costa Rica. Journal of Volcanology and Geothermal Research, 450, 108075.
Thakur, M., Mandal, S., Manohar, P., & Chatterjee, S. (2024). Spatio-temporal characteristics of particulate matter in Delhi, India due to the combined effects of fireworks and crop burning during pre-COVID festival seasons. Natural Hazards, 1-28.
Asadi, A., Baise, L. G., Koch, M., Moaveni, B., Chatterjee, S., & Aimaiti, Y. (2024). Pixel-based classification method for earthquake-induced landslide mapping using remotely sensed imagery, geospatial data and temporal change information. Natural Hazards, 120(6), 5163-5200.
Chatterjee, S., Karacan, C. Ö., & Mastalerz, M. (2024). Exploring the uncertainty of machine learning models and geostatistical mapping of rare earth element potential in Indiana coals, USA. International Journal of Coal Geology, 282, 104419.
Asadi, A., Baise, L. G., Chatterjee, S., Koch, M., & Moaveni, B. (2024). Regional landslide mapping model developed by a deep transfer learning framework using post-event optical imagery. Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards, 18(1), 186-210.
Abuzaied, M. M., Chatterjee, S., & Askari, R. (2023). Stochastic inversion combining seismic data, facies properties, and advanced multiple-point geostatistics. Journal of Applied Geophysics, 213, 105026.
Vishnu, C. L., Oommen, T., Chatterjee, S., Rajaneesh, A., & Sajin Kumar, K. S. (2023). Assessing the Improvement of a Sparse Rain Gauge Network in a Landslide Hotspot in Kerala, India—A Multi-Criteria Approach. Environmental & Engineering Geoscience, 29(4), 245-256.
Asadi, A., Baise, L. G., Sanon, C., Koch, M., Chatterjee, S., & Moaveni, B. (2023). Semi-supervised learning method for the augmentation of an incomplete image-based inventory of earthquake-induced soil liquefaction surface effects. Remote Sensing, 15(19), 4883.
Madziwa, L., Pillalamarry, M., & Chatterjee, S. (2023). Integrating stochastic mine planning model with ARDL commodity price forecasting. Resources Policy, 85, 104014.
Anil, J., Kumar, K., Ram, S., Chatterjee, S., & Gorai, A. K. (2023). Monitoring of Subsidence Over a Continuous Miner-Based Coal Mine Caving Panels Using PS-InSAR Technique. Mining, Metallurgy & Exploration, 1-18.
Madziwa, L., Pillalamarry, M., & Chatterjee, S. (2023). Integrating flexibility in open pit mine planning to survive commodity price decline. Resources Policy, 81, 103428.

Teaching Statement

Dr. Chatterjee teaches mine planning and design, geostatistics and data analysis, advanced geomechanics, resource and reserve estimation, and mine system reliability and optimization.