I’m Kyle Vedder

About Me

I am a Member of Technical Staff at a stealth embodied AGI startup.

I believe strongly in The Bitter Lesson, and I believe our job as researchers is to find the right tricks, data distributions, and algorithms to scale up deep learning.

I believe one such trick is teaching vision systems to understand motion. My PhD research has focused on training self-supervised models to predict motion via scene flow, and building offline preprocessing pipelines to provide these motion descriptions without labels.

Academic Background

I am a CS PhD candidate at Penn under Eric Eaton in the GRASP Lab. I have been fortunate to work closely with Deva Ramanan, James Hays, and Dinesh Jayaraman throughout my PhD. Representative projects include:

For a narrative overview of how my PhD research fits together, see Overview of my PhD Research.

Industry / Engineering Background

I have done many industry internships:

I also have significant experience doing high-precision full stack robotics. In undergrad, I lead the greenfield development of AMRL’s Robocup Small Size League control stack and did research in multi-agent path planning.

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