Brad Knox is a Research Associate Professor of Computer Science at the University of Texas at Austin. His research primarily explores the human side of reinforcement learning, with a current focus on how humans can specify reward functions that align with their interests. His dissertation, "Learning from Human-Generated Reward," was early pioneering work in human-in-the-loop reinforcement learning and received the 2012 best dissertation award from the UT Austin Department of Computer Science.