Current methods of searching for video tutorials rely on basic information of videos such as view counts, titles, descriptions, and tags to return search results. By gathering more data about video tutorials relevant to the software involved such as tools and plugins being used at certain frames of the video, we can create a better searching interface that is catered towards finding video tutorials. My work will create an effective procedure that uses computer vision and crowdsourcing to gather metadata of videos. I will be evaluating every method by testing the accuracy, quality, and quantity of the metadata it provides.

I assisted graduate student Kevin Chiu with his web project by submitting potential web designs and finding software glitches. I worked with Professor Nitin Sawhney to develop an iOS application that served as a digital diary. I was part of the team that tested the user interface of a mobile digital diary for children.