“To deal with this volume of data and the complex inference problem of network discovery we require a language that provides good support for numerical programming and speed, which is why Julia has been such a good option. We find that Julia improves tremendously our productivity with these kind of …

"Julia has the best of both worlds. When we are prototyping, we can rapidly create simple simulations or algorithms to perform general tests, taking advantage of the ease usually available in interpreted languages. After this phase, when algorithms are then used in simulators or multidisciplinary design optimization (MDO) tools, we …