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 exploring using convolutional neural networks (CNNs) and recurrent neural networks (RNNs) for real-time object detection and 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 am currently organizing a seminar on using deep learning in practice. In it, we discuss how to apply modern techniques to solve real research problems. We explore the effectiveness of methods. More information, as well as slides and videos are posted on the seminar website.