  Two transformative waves of computing have redefined the way we approach
science. The first wave came with the birth of the digital computer, which
enabled scientists to numerically simulate their models and analyze massive
datasets. This technological breakthrough led to the emergence of many
sub-disciplines bearing the prefix "computational" in their names. Currently,
we are in the midst of the second wave, marked by the remarkable advancements
in artificial intelligence. From predicting protein structures to classifying
galaxies, the scope of its applications is vast, and there can only be more
awaiting us on the horizon.
  While these two waves influence scientific methodology at the instrumental
level, in this dissertation, I will present the computational lens in science,
aiming at the conceptual level. Specifically, the central thesis posits that
computation serves as a convenient and mechanistic language for understanding
and analyzing information processing systems, offering the advantages of
composability and modularity.
  This dissertation begins with an illustration of the blueprint of the
computational lens, supported by a review of relevant previous work.
Subsequently, I will present my own works in quantum physics and neuroscience
as concrete examples. In the concluding chapter, I will contemplate the
potential of applying the computational lens across various scientific fields,
in a way that can provide significant domain insights, and discuss potential
future directions.
