Daniel Gordon

About Me

I am a 4th year graduate student at the University of Washington, advised by Dieter Fox and Ali Farhadi. Previously, I graduated from Washington University in St. Louis, where I worked as an undergraduate researcher with Robert Pless.


I am researching using convolutional neural networks (CNNs) and recurrent neural networks (RNNs) for real-time object tracking in video data. In my research, I am developing fast and robust algorithms with the eventual goal of fully tracking laboratory procedures to reduce errors in experiments and increase reproducibility. I am also working on visual planning for robots using simulation environments and a combination of reinforcement learning and supervised learning.


Curriculum Vitae



I previously organized a seminar on using deep learning in practice. In it, we discussed how to apply modern techniques to solve real research problems. We also explored the effectiveness of various methods. More information, as well as slides, videos, and code are posted on the seminar website.