Introducing Katie Bouman, the MIT graduate who led the development of the algorithm that helped make the photo of a black hole possible. Bouman, 29, who has a Ph.D. in Electrical Engineering, worked with more than 200 scientists, over a three-year span, directing the verification of images and the selection of image parameters as they took the "sparse and noisy data" from a series of telescopes to construct an image of a black hole-which has never been done before.

"We developed ways to generate synthetic data and used different algorithms and tested blindly to see if we can recover an image. We didn't want to just develop one algorithm. We wanted to develop many different algorithms that all have different assumptions built into them. If all of them recover the same general structure, then that builds your confidence," Bouman said. "No matter what we did, you would have to bend over backwards crazy to get something that wasn't this ring."

"No one of us could've done it alone. It came together because of lots of different people from many backgrounds," Bouman added. "I'd like to encourage all of you to go out and help push the boundaries of science, even if it may at first seem as mysterious to you as a black hole,"

Since the release of the black hole picture, social media have fallen in love with Bouman's story along with her picture. That comes with thanks to her alma mater for being super supportive and also giving credit, where credit is due. MIT posted a picture of Bouman alongside a picture of Margaret Hamilton-the MIT grad that essentially put man on the moon-as an homage to groundbreaking science by way of female scientists. Bouman, herself, also had a hand in this viral frenzy, she posted a picture to her own Facebook page showing her utter excitement as the picture she created of the black hole was being restored. The caption read: Watching in disbelief as the first image I ever made of a black hole was in the process of being reconstructed.

(Photo : Katie Bouman Facebook)

Bouman gives a brief description of exactly how the picture came to life. She says, "If all [pictures captured by the telescopes] produce a very similar-looking image, then we can start to become more confident that the image assumptions we're making are not biasing this picture that much," Bouman added, "This is a little bit like giving the same description to three different sketch artists from all around the world. If they all produce a very similar-looking face, then we can start to become confident that they're not imposing their own cultural biases on the drawings. One way we can try to impose different image features is by using pieces of existing images. So we take a large collection of images, and we break them down into their little image patches. We then can treat each image patch a little bit like pieces of a puzzle. And we use commonly seen puzzle pieces to piece together an image that also fits our telescope measurements."

Bouman is now teaching; she accepted a Visiting Associate position in the Computing and Mathematical Sciences department at the California Institute of Technology in Pasadena.