MIT IAP Fellow
Jasmin Rubinovitz is a cross-disciplinary researcher, designer, and engineer. She holds a Masters in Media Arts and Science from the MIT Media Lab, where she worked in the Viral Communications group. While at the Media Lab, she designed and built interactive data visualizations to explore the content and perspectives in mass media, enabling better collaboration between humans and machine learning models.
At Stochastic Labs, Jasmin worked on GooeyBrain—an open source GUI app for generating data, such as images, using a neural network built on top of Google's Tensorflow library, with the goal to facilitate the creation of artistic and creative artifacts using artificial intelligence. She also developed FiftyNifty.org, a game that simplifies the process of calling congress, while encouraging a social network to do the same. Jasmin earned her bachelors in Computer Science and Ceramic Design at the Hebrew University of Jerusalem and Bezalel Academy for Art and Design; has worked as a software engineer at Google; and is currently a lead creative technologist at Fake Love—an innovative experiential design agency that is part of The New York Times.