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I grew up in sunny Southern California where my obsession with computers and technology started. Like others, I was completely self-taught and took it upon myself to learn as much as I could. My interest progressed steadily from building PC's to creating virtual networks and running various Linux distribution servers at home. This experience paid off when I started looking for a job after I had graduated from New York Univeristy with a Bachelor's degree in Economics and Spanish. Companies I interviewed for were willing to take a chance and hire me as a member of their Information Technology (IT) department. I was a natural fit and easily assimilated.

I did that for a number of years, first for a Search Engine Optimization (SEO) company and, more recently, a private airline company called JetSuite. It was at the latter when I was asked one day if I could help another department expedite a task they were doing. I did my research and in a couple hours came up with a Windows batch script that ended up saving them hours daily. While they were thrilled with the results, I was left in a cathartic state, realizing that software development was what I wanted to do.

To accomplish this career change, I knew I had to start with a strong foundation, so I looked at the classes that CS undergraduates would typically take, and enrolled in them through the Extensions program at the University of California, Irvine (UCI) which allowed post-graduates to take college undergraduate courses. Eventually I had taken enough of these courses to meet the pre-requisites for the Master of Computer Science (MCS) program at UCI, where I spent 5 quarters honing my programming skills. The culimination of the program was an entire quarter spent on a final Capstone project of our choice, which myself and 2 other graduate students had to present in an auditorium with representatives from over a hundred tech companies, including Google. We ended up developing a web application for FitBit users that enabled them to sync their fitness data, which we fed into a k-means clustering machine learning algorithm, in order to generate a weekly workout schedule. Our app also featured a one-of-a-kind injury tracking system, which our algorithm also took into consideration. This allowed users to make sure their custom workout schedule didn't include workouts for any injured areas of their body. We received a lot of positive feedback from all the tech representatives who attended.