Nathan Hatch

Computer science PhD student at the University of Washington


Research Interests

I’m interested in machine learning for robotic perception and control, with a focus on potential applications in autonomous vehicles. My recent work focuses on high-speed obstacle avoidance using information theoretic model-predictive control. Before that, I did some work in learning a real-time, dynamic bipedal locomotion controller for rough terrain. My advisor is Dr. Byron Boots, who directs the University of Washington Robot Learning Lab.

Curriculum Vitae (CV) or shorter resume (both updated 2019-12-20)


A. Shaban, C. Cheng, N. Hatch, and B. Boots. “Truncated Back-Propagation for Bilevel Optimization.” Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019). (PMLR) (arXiv)

N. Hatch. “Group Theory: An Introduction and an Application.” University of Chicago VIGRE REU; August 2011. (paper)

Personal Projects

You may be interested in this Mancala AI, this factor graph SLAM implementation, this RRT demo, or other projects on my GitHub.

Class Projects

S. Foley, N. Hatch, and A. Beedu. A Global Optimal Solution to Non-Minimal Relative Pose Estimation. ECE 8823 Convex Optimization; Spring 2019. (pdf)

N. Hatch and E. Wijmans. Probabilistic Graphical Modeling of Data-Dependent Annotator Accuracy for Active Learning. CS 8803 Probabilistic Graphical Models; Spring 2018. (paper) (slides)

N. Hatch, A. Sundaresan, M. Dutreix, R. Kuppan, and P. Pattanashetty. Google Landmark Recognition and Retrieval Challenges. ECE 6254 Statistical ML; Spring 2018. (paper) (poster)

N. Hatch. Unsupervised Curriculum Learning for Image Clustering. CS 7643 Deep Learning; Fall 2017. (poster)


I joined the University of Washington CS PhD program in Winter 2020, after two and a half years in the Georgia Tech ML PhD program. Prior to that, I worked for three years as a software engineer at eSpark Learning, an education technology company that adaptively curates educational resources for grade school students based on their test scores. I completed my Bachelor of Science degree at the University of Chicago in 2014 with a double major in mathematics and computer science.