The article provides an overview of the advancements in computational inverse design and its applications in nanophotonics. It highlights the historical reliance on intuition-based approaches in nanophotonics device design, which have been effective for creating a rich library of templates. However, as the scope of nanophotonics broadens to include large bandwidth, multi-frequency applications, nonlinear phenomena, and dense integration, traditional methods become increasingly challenging. The introduction of computational inverse design techniques offers a systematic approach to optimize complex structures and devices, addressing the limitations of intuition-based methods. The article outlines key developments in inverse design, including the use of genetic algorithms and gradient-based methods, and the introduction of level-set and topology optimization techniques. These methods allow for the systematic exploration of a vast design space, enabling the creation of structures with enhanced performance in areas such as nonlinear optics, topological photonics, and near-field optics. Recent applications of inverse design in nanophotonics are discussed, including the design of devices for solar energy conversion, thermal energy manipulation, and on-chip integration. The article also highlights the potential of inverse design in realizing wavelength-scale nonlinear devices, which are crucial for developing on-chip technologies such as low-threshold lasers, frequency combs, and quantum information processing. Experimental challenges in fabricating inverse-designed structures are addressed, particularly the need for compatibility with photolithography to reduce fabrication costs. The article concludes by emphasizing the positive outlook for inverse design in nanophotonics, with ongoing research focusing on expanding the applicability of these techniques to active devices and further exploring their potential in understanding fluctuation physics and near-field optics.The article provides an overview of the advancements in computational inverse design and its applications in nanophotonics. It highlights the historical reliance on intuition-based approaches in nanophotonics device design, which have been effective for creating a rich library of templates. However, as the scope of nanophotonics broadens to include large bandwidth, multi-frequency applications, nonlinear phenomena, and dense integration, traditional methods become increasingly challenging. The introduction of computational inverse design techniques offers a systematic approach to optimize complex structures and devices, addressing the limitations of intuition-based methods. The article outlines key developments in inverse design, including the use of genetic algorithms and gradient-based methods, and the introduction of level-set and topology optimization techniques. These methods allow for the systematic exploration of a vast design space, enabling the creation of structures with enhanced performance in areas such as nonlinear optics, topological photonics, and near-field optics. Recent applications of inverse design in nanophotonics are discussed, including the design of devices for solar energy conversion, thermal energy manipulation, and on-chip integration. The article also highlights the potential of inverse design in realizing wavelength-scale nonlinear devices, which are crucial for developing on-chip technologies such as low-threshold lasers, frequency combs, and quantum information processing. Experimental challenges in fabricating inverse-designed structures are addressed, particularly the need for compatibility with photolithography to reduce fabrication costs. The article concludes by emphasizing the positive outlook for inverse design in nanophotonics, with ongoing research focusing on expanding the applicability of these techniques to active devices and further exploring their potential in understanding fluctuation physics and near-field optics.