Thomas Oommen

Thomas Oommen


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  • Associate Professor, Geological and Mining Engineering and Sciences
  • Affiliated Associate Professor, Civil and Environmental Engineering
  • PhD, Geotechnical and Geoenvironmental Engineering, Tufts University
  • MS, System Engineering, University of Alaska-Fairbanks
  • BS, Civil Engineering, M. S. Ramaiah Institute of Technology


Dr. Oommen’s research efforts focus on developing improved susceptibility characterization and documentation of geo-hazards (e.g. earthquakes, landslides) and spatial modeling of georesource (e.g. mineral deposits) over a range of spatial scales and data types. To achieve his research interests, he has adopted an inter-disciplinary research approach from two main areas, specifically: aerial/satellite based remote sensing for obtaining data, and artificial intelligence/machine learning based methods for data processing and modeling.

Dr. Oommen is expanding his research to investigate future applications of satellite remote sensing and machine learning for geological engineering in the fields of geohazards and georesource characterization. His immediate goal is to verify the applicability of remote sensing techniques such as Differential Interferometric Synthetic Aperture Radar (DinSAR) and Light Detection and Ranging (LiDAR) as sustainable operational strategies for monitoring land subsidence. Land subsidence is often the surface expression of a variety of subsurface mechanisms such as lowering of water table, drainage, lateral flow, loading, vibration, and tectonic activity. Quantifying subsidence is critical for land use and infrastructure planning, health monitoring of engineered structures as well as for understanding the subsurface conditions.

Links of Interest

Teaching Interests

  • Computer Methods in Geomechanics
  • Computational Geoscience
  • Remote Sensing for Geotechniques
  • Geostatistics and Data Analysis
  • Engineering Geology and Geoinformatics

Research Interests

  • Liquefaction susceptibility evaluation at local and regional scales using in-situ measurements and remote sensing observations
  • Estimating liquefaction induced damage such as lateral spread displacement
  • Transportation Geotechniques
  • Documenting earthquake induced damages, especially liquefaction using aerial/satellite images that are sensitive to surficial moisture
  • Geotechnical asset monitoring

Recent Publications

  • L N Schaefer, Z Lu, T Oommen (2015) Dramatic volcanic instability revealed by InSAR Geology. doi:10.1130/G36678.1 Read More
  • L N Schaefer, J E Kendrick, T Oommen, Y Lavallée, G Chigna (2015) Geomechanical rock properties of a basaltic volcano Frontiers in Earth Science 3: 29. Read More
  • D M Smith, T Oommen, L J Bowman, J S Gierke, S Vitton (2015) Hazard assessment of rainfall-induced landslides: A case study of San Vicente Volcano in Central El Salvador. Natural Hazards 75: 3. 2291-2310. Read More
  • Zwissler B., Oommen T., and Vitton S. (2014) A study of the impacts of freeze-thaw on cliff recession at the Calvert Cliffs in Calvert County, Maryland. Geotechnical and Geological Engineering. 10.1007/s10706-014-9792-1 Read More
  • Schaefer L.N., Oommen T., Corazzato C., Tibaldi A. Escobar-Wolf R., and Rose W.I. (2013). An integrated field-numerical approach to assess slope stability hazards at volcanoes: the example of Pacaya, Guatemala. Bulletin of Volcanology. Read More
  • Oommen T., Baise L.G., Gens R., Prakash A., and Gupta R.P. (2013). Documenting earthquake-induced liquefaction using satellite remote sensing image transformations. Environmental & Engineering Geoscience 19:(3). Read More
  • Samui P., Gowda P.H., Oommen T., Howell T.A., and Marek T.H. (2012). Statistical learning algorithms for identifying contrasting tillage practices with Landsat thematic mapper data. International Journal of Remote Sensing 33:(18) 5732-5745. Read More
  • T. Oommen, L. G. Baise, R. M. Vogel, "Sampling bias and class imbalance in maximum likelihood logistic regression." Mathematical Geosciences 43: 1. 99-120. 2011 Read More