Personal information

Data-efficient robot learning, Bayesian optimization, Active learning
United States

Biography

I am a postdoctoral scholar at Stanford University and a recipient of NSF/CRA Computing Innovation Fellowship for research on active learning of transferable priors, kernels, and latent representations for robotics. Currently, I work at the IPRL lab headed by Jeannette Bohg.

I completed my PhD work on data-efficient simulation-to-reality transfer at the Robotics, Perception and Learning lab at KTH (Stockholm, Sweden), working in the group headed by Danica Kragic. During my PhD time, I also had an opportunity to intern at NVIDIA Robotics (Seattle, USA) and Microsoft Research (Cambridge, UK).

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).

Activities

Employment (2)

KTH Royal Institute of Technology: Stockholm, Stockholm, SE

Employment
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KTH Royal Institute of Technology

Stanford University: Stanford, CA, US

2021-01-27 to present | Postdoctoral Research Fellow (Computer Science)
Employment
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Rika Antonova

Education and qualifications (2)

KTH Royal Institute of Technology: Stockholm, SE

2016-08-22 to 2020-12-20 | PhD (EECS Electrical Engineering and Computer Science)
Education
Source: Self-asserted source
Rika Antonova

Carnegie Mellon University: Pittsburgh, PA, US

2013-09-01 to 2016-08-01 | Master of Science in Robotics (Robotics Institute)
Education
Source: Self-asserted source
Rika Antonova

Peer review (1 review for 1 publication/grant)

Review activity for Nature machine intelligence. (1)