Stanford

Hello, I’m Steven! I am a Stanford Computer Science graduate student, focusing on computer vision and performant systems. I completed my undergrad at UT Austin, under the Turing Scholars CS honors program. I will be graduating in 2019, and am looking forward to joining Aurora Innovation as a software engineer working on Machine Learning R&D.

I was fortunate to have Kristen Grauman as my research advisor at UT. Our work on visual attributes was published in CVPR 2018 (project page here). I am currently advised by Kayvon Fatahalian: our recent work on efficient video inference can be found here.

I have been fortunate to learn from many internships. Last summer, I worked at NVIDIA on autonomous vehicle neural networks and systems. Previously, I worked at Riot Games on machine learning recommendations for League of Legends, at Google on Google Photos MapReduce, and at RetailMeNot on ranking algorithms.

I am currently a teaching assistant for CS230 Deep Learning, taught by Kian Katanforoosh and Andrew Ng. I was a teaching assistant for CS102 Big Data taught by Dean Jennifer Widom, as well as CS161 Algorithms taught by Mary Wootters and Leonidas Guibas.

My resumé is here. If you know me personally, feel free to connect with me on LinkedIn.

In my free time, I like to read, dance, travel, and play strategy and team games. I enjoy thinking about architecture, and I like to keep up with the latest in the auto industry. I’m also an avid Google Local Guide reviewer, with over 2.5 million photo views on Google Maps, as well as the occasional amateur Wikipedia editor.