Dr Rika Antonova

A Brief Bio

I am an Associate Professor at the University of Cambridge, leading the Cambridge Resilient Autonomous Learning (CamRAL) Lab.

Previously, I was at Stanford University upon receiving the NSF/CRA Computing Innovation Fellowship, and worked with the Interactive Perception and Robot Learning Lab at Stanford led by Jeannette Bohg. I completed my PhD work on data-efficient simulation-to-reality transfer at KTH (Sweden) in the group headed by Danica Kragic. I also had the opportunity to intern at NVIDIA Robotics (Seattle, USA) and Microsoft Research (Cambridge, UK).

Before that, I obtained my Master's degree from the Robotics Institute at Carnegie Mellon University, where I developed data-efficient methods for learning controllers for bipedal locomotion (with Akshara Rai and Chris Atkeson). During my time at CMU, my advisor was Emma Brunskill, and in her group I also worked on data-efficient reinforcement learning.

A few years earlier, I was a software engineer at Google, first in the Search Personalization group and then in the Character Recognition team (developing an open-source OCR engine Tesseract).

Updates

I am currently looking for talented mechanical engineers and postdocs for a project on novel robot hardware design. If you are interested - please reach out to me.

While my recent work focused on robotics, I am also returning to my long-term interest in reinforcement learning algorithms, so I am enthusiastic about collaborations in data-efficient RL, active learning & exploration​, ​and ​decision​-making for scientific & environmental domains as well.