I create robots that achieve complex active perception tasks by reasoning from perceptual models to sample views of the environment. To this end, I develop theory and algorithms to enable inference with respect to consistent, high-resolution spatial representations. This research enables robots to execute safe maneuvers to acquire information under uncertainty and real-time constraints.

I am a postdoctoral fellow with Professor Nathan Michael in the Resilient Intelligent Systems Lab. I completed my PhD in Computer Science at Carnegie Mellon University in 2019 with Professors Nathan Michael and Red Whittaker. I also hold an MS in Robotics as well as a BS in Computer Science from Carnegie Mellon University.