IRIS.TV turns video distribution into a science. We are transforming the video viewing experience online into one that is personalized, highly engaging and turns static web pages into deeply engaging media experiences across the open web. Six years ago I was lucky enough to work with some brilliant engineers and data scientists where we built the first in-stream video recommendation engine. We called it Jukebox TV—think "Pandora for Video." By focusing on building better data sets and adaptive machine learning—we built an early iteration of the tech that is now IRIS.TV. I've been designing machine learning systems and programming products to power the future of video and TV since graduating at Pomona College. Throughout my professional career I've worked with artists, creators, media companies and studios with a focus on distribution and product. Ensuring that content distribution is profitable for artists and content owners is my DNA and we built IRIS.TV to ensure that content owners and brands can own their distribution and make online video a profitable distribution. I write and maintain a studio art practice focused on multi-media and Montage in Los Angeles.