About me

Welcome! I’m an autonomy and robotics engineer at Icon Technology where we work on automating the future of construction. At Icon, I develop the software and planning architecture for a deployed mobile robot with a 6DOF tool-arm that performs safety-critical tasks in dusty, dynamic environments. Previously, I was postdocorate fellow at the Oden Institute for Computational Sciences, located at the University of Texas at Austin. As a researcher I was a member of Center for Autonomoy. I graduated with my PhD in Aerospace Engineering at the University of Texas at Austin specializing in decision-making for Task-Aware Planning and Learning in Partially Observable Environments. Prior to my graduate studies I received a Bachelors of Engineering/Bachelors of Science in aerospace and mathematics from the University of Sydney.

Research Interests

My research interests include the intersection of control and learning in autonomous systems with a focus on aerospace applications. In particular, my focus is on theory and algorithms for assured autonomy in the presence of partial observability and uncertainty. I have studied how to integrate formal verification and synthesis with data-driven methods such as reinforcement learning and deep learning.

If you are interested in learning more click here for a list of my recent projects.

Skills and Abilities

I have a lot of experience coding in both Python and C++. In particular, I implemented customized deep networks (CNNs, LSTMS, RNNs and GRUs) in both Tensorflow and PyTorch. For deep reinforcement learning, I can parallelize training across multiple instances, safe learning on PPO, discrete SAC, DQN, DRQN and REINFORCE. For deployed agents (UAVs and Turtlebots) I use the robot operating system (ROS).