Stanford

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.

You can find my resumé here. If you know me personally, connect with me on LinkedIn.

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.