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Arindam Fadikar

Assistant Compuational Statistician

Arindam is interested in developing statistical techniques for computer model calibration, inverse problem and uncertainty quantificaiton with applications in cosmology, epidemiology.


Arindam’s research is largely motivated by finding ways of doing predictions and uncertainty quantifications for physical system by combining simulations and noisy observation from the system. In particular, he is interested in stochastic simulations and modeling the inadequacy of the computational model.

Arindam received his Master’s degree from Indian Statistical Institute in 2011. He graduated from Virginia Tech with a Ph.D. degree in Statistics in 2019, where he worked with epidemiologists and used agent-based models to forecast Ebola outbreaks in West Africa and seasonal flu in the United States.

In addition to being a PostDoc with Argonne, he is part of a team at the Biocomplexity Institute at the University of Virginia that supports the Virginia Department of Health (VDH) and other federal agencies with COVID-19 models and predictions.