Hello, I’m Steven Chen. I am a Computer Science graduate student at Stanford, focusing on computer vision and artificial intelligence. I completed my undergrad at UT Austin, under the Turing Scholars CS honors program. I will be graduating in mid-2019, and am looking forward to joining Aurora Innovation as a software engineer in the Machine Learning R&D team.
I was fortunate to have Kristen Grauman as my research advisor at UT. Our work on attributes was published in CVPR 2018 (project page here). I am currently working with Kayvon Fatahalian on performant deep neural networks for vision. Our recent work on efficient video inference is here.
I have been fortunate to learn from many internships. This summer, I worked at NVIDIA on autonomous vehicle neural networks and system software. Previously, I worked at Riot Games on machine learning recommendations for League of Legends, at Google on Google Photos MapReduce APIs, and at RetailMeNot on ranking algorithms.
I am currently a teaching assistant for CS102 Big Data taught by Dean Jennifer Widom. I was a teaching assistant for CS230 Deep Learning, taught by Kian Katanforoosh and Andrew Ng, as well as CS161 Algorithms taught by Mary Wootters and Leonidas Guibas.
In my free time, I like to read, dance, travel, and play strategy games. I enjoy touring architecture, and I like to drive and keep up with the auto industry. I’m also an Google Local Guide reviewer, with over 75,000 review and 2.3 million photo views on Google Maps.