The focus area of the group is computational studies of materials for energy storage devices and electrocatalysis. From the methodological viewpoint, the group efforts are divided between theoretical approaches involving the application of density functional theory (DFT) methods and large-scale classical molecular dynamics (MD) simulations to understand and predict the atomistic properties of electrolytes and electrode/electrolyte interfaces. In both the aforementioned thrusts, the methods of high-throughput computational screening using DFT theory based-methods and/or automated classical MD simulations are employed. Over the recent few years, a significant progress has been made in complimenting the existing high-throughput infrastructure with computational models and modules involving machine learning. The materials informatics elements allow for a significant facilitation of materials screening by expanding the parameter space and inclusion of systems and processes spanning different time- and length-scales. Our approach is composed of three main components First, (I) Physical Models describing processes taking place in energy storage devices and electrocatalyst systems are derived from sequential multi-scale simulations to explore properties at wide length and time scales. The data generated from high-throughput physical models is then used to train (II) Machine Learning (ML) surrogate models (SMs) to explore a vast parameter space at unprecedented speed and lower cost. Lastly, (III) Experimental verification (from collaborators) of theoretical predictions and analysis to have a close-knit feedback loop of synthesis-structure-property-performance relationships. The ongoing work includes – but is not limited to – development of computational modules for inverse molecular design and surrogate machine learning-based models for expanding the parameter hyperspaces. In our lab, these approaches are implemented to studies of electrolytes, electrodes, and electrode-electrolyte interfaces in model systems relevant for batteries, supercapacitors, and electrocatalysis.