I am an Assistant Professor of Computer Science at George Mason University where I run the Robotic Anticipatory Intelligence & Learning (RAIL) Group. Our research, at the intersection of robotics and machine learning, is centered around developing representations that allow robots to better understand the impact of their actions, so that they may plan quickly and intelligently in a dynamic and uncertain world. You can learn more about my research on my research group's website.
I received my Ph.D. from the Robust Robotics Group at MIT's Computer Science and Artificial Intelligence Laboratory. To view my full CV and publications record, you can visit my Curriculum Vitae page.
I also run and maintain a blog, Caches to Caches, in which I discuss my various hobby projects (many of which relate to the Emacs text editor), and my musings on robotics, machine learning, technical communication, and mentorship.
If you are interested in learning more about my work, my talk from the 2018 Conference on Robot Learning nicely motivates my approach to thinking about planning under uncertainty, one of the fundamental challenges my research aims to tackle:
Learn more about my research on my group's website.