Surrogate modeling is a technique used in scientific research and engineering to create simplified, mathematical models that mimic the behavior of more complex, often computationally expensive simulations or experiments. These surrogate models are typically trained on a limited set of data points or output from the original model, and are then used to make predictions or optimize parameters more efficiently. Surrogate modeling can be used to reduce the time and resources needed to perform complex simulations, optimize designs, or perform sensitivity analysis. It is a valuable tool for accelerating the research and development process in many fields, including engineering, computer science, and environmental science.