I am a postdoctoral scholar at Stanford IPRL lab and a recipient of NSF Computing Innovation Fellowship for research on active learning of transferable priors, kernels, and latent representations for robotics. My research interests include Bayesian optimization, reinforcement learning, and manipulation with deformables. I completed my PhD work on data-efficient simulation-to-reality transfer at the Robotics, Perception and Learning lab in KTH, Stockholm. Previously, I was a Masters student at the Robotics Institute at Carnegie Mellon University, developing Bayesian optimization approaches for learning control parameters for bipedal locomotion (with Akshara Rai and Chris Atkeson). During my time at CMU my MS advisor was Emma Brunskill and in her group I worked on developing reinforcement learning algorithms for education. Prior to that, I was a software engineer at Google, first in the Search Personalization group and then in the Character Recognition team (developing open-source OCR engine Tesseract).