Rate My Professor Arunasalam Arunasalam Rahunanthan

Rahunanthan's academic interests center on mathematical modeling of multiphase flows through porous media, Bayesian methods for uncertainty quantification, discontinuous Galerkin approximations, and high-performance computing on GPUs. His peer-reviewed publications include "Contaminant Transport Forecasting in the Subsurface Using a Bayesian Framework" with A. Mamun et al. (Applied Mathematics and Computation, 2020), "Multi-Physics Markov Chain Monte Carlo Methods for Subsurface Flows" with V. Ginting and F. Pereira (Mathematics and Computers in Simulation, 2015), "Rapid Quantification of Uncertainty in Permeability and Porosity of Oil Reservoirs for Enabling Predictive Simulation" (Mathematics and Computers in Simulation, 2014), "Hysteretic Enhancement of Carbon Dioxide Trapping in Deep Aquifers" (Computational Geosciences, 2014), and "High-order W-methods" (Journal of Computational and Applied Mathematics, 2010). As principal investigator or co-principal investigator, he has obtained grants totaling millions, such as the $500,000 NSF Excellence in Research Award (2023) for groundwater contamination forecasting, $299,208 NSF Research Initiation Award (2016-2021), Ohio RAPIDS grants exceeding $200,000, and $2.25 million USDA NIFA scholarship program. Recognitions include the Southwestern Ohio Council for Higher Education Faculty Excellence Award (2017), CASL Fellowship (2019-2020), and Scientific Teaching Fellow (2018-2019). His contributions enhance predictive capabilities in environmental and energy sectors.