Stanford

Hello, I’m Steven! I am currently a software engineer on the Perception team at Aurora, working on autonomous vehicles. I graduated from Stanford in 2019 with a Masters in Computer Science, where I focused on computer vision, machine learning, and performant systems. I completed my undergrad at UT Austin, under the Turing Scholars CS honors program.

I was advised by Kayvon Fatahalian at Stanford: our work on efficient video inference was published in ICCV 2019 and can be found here. I was fortunate to have Kristen Grauman as my research advisor at UT. Our research on visual attributes was published in CVPR 2018 (project page here).

I had four internships during undergraduate and graduate school. In 2018, 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.

At Stanford, I was a teaching assistant for CS230 Deep Learning, taught by Kian Katanforoosh and Andrew Ng, 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 an avid Google Local Guide reviewer, with over 3 million photo views and 100 thousand review reads on Google Maps, as well as the occasional amateur Wikipedia editor.