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Fueled by breakthroughs in both hardware and algorithm development, the past few decades have witnessed an explosive growth in computational power, which has led to remarkable advances in various fields of science and technology, such as the mapping of the human genome. It also set the stage for addressing even more ambitious goals, many of which can't be achieved through hardware developments alone. Because conventional modeling strategies are typically based on single physical descriptions, they're simply unable to capture the relevant phenomena occurring over many space and time scales. This special issue brings together five articles that address the coming challenges.