School of Engineering

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  • Rika Antonova

    Rika Antonova

    Postdoctoral Research Fellow, Computer Science

    BioI am a postdoctoral scholar at Stanford IPRL lab and a recipient of a CI Fellowship from NSF/CRA for research on active learning of transferable priors, kernels, and latent representations for robotics. My research interests include reinforcement learning and Bayesian optimization. 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).