Dissertation
Rico Jonschkowski. Learning Robotic Perception Through Prior
Knowledge. Dissertation, Technische Universität Berlin, 2018.
PDF
This dissertation summarizes my pre-2018 work listed above. My committee
consisting of Manfred Opper, George Konidaris, Marc Toussaint, and Oliver Brock
graded
it with summa cum laude and the Department for Electrical
Engineering and Computer Science at TU Berlin awarded it the
Best Dissertation Prize of the Dr. Wilhelmy-Stiftung.
Curriculum Vitae
- 05/2018 - present
-
Research scientist at Robotics at Google, Mountain View,
California.
- 10/2012 - 05/2018
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Research associate and PhD student at RBO, TU Berlin (Advisor: Oliver Brock).
Taught courses: Fundamentals of Robotics, Robotics,
Advanced Robotics, Robotics Seminar, Robotics Project, Algorithms and
Datastructures.
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05/2018 Dr. rer. nat. (German PhD equivalent, summa cum
laude)
Thesis: Learning
Robotic Perception Through Prior Knowledge.
-
01/2017 - 04/2017 PhD Intern at DeepMind,
London.
- 10/2007 - 09/2012
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Study of computer science at FU Berlin.
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09/2012 Master of Science (grade: 1.0, major: robotics/AI,
minor: psychology).
Thesis: New Approaches to Temporal Abstraction in Hierarchical
Reinforcement Learning.
-
01/2012 - 09/2012 Research assistant at MLR,
FU Berlin (Advisor: Marc Toussaint).
-
2011 Study abroad at UNSW, Sydney.
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10/2009 - 09/2011 Teaching assistant at FU Berlin.
Taught courses: Functional Programming, Object-Oriented Programming,
Computer Science and Society, Software Engineering
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01/2011 Bachelor of Science (grade: 1.4, major: computer
science, minor: philosophy).
Thesis: Control of autonomous humanoid soccer robots with XABSL.
-
2008 - 2011 Member of RoboCup team FUmanoids (Advisor: Raul Rojas).
Awards, Prizes, Scholarships
2018 Prize from the Dr. Wilhelmy-Stiftung for the best dissertation in electrical
engineering and computer science at TU Berlin.
2017 Paper Award winner at New Frontiers for Deep Learning in Robotics Workshop
at RSS
Rico Jonschkowski, Roland Hafner, Jonathan Scholz, and Martin Riedmiller. PVEs:
Position-Velocity Encoders for Unsupervised Learning of Structured State
Representations. New Frontiers for Deep Learning in Robotics Workshop at RSS,
2017.
2016 Best Paper Award finalist at IROS
Rico Jonschkowski, Clemens Eppner, Sebastian Höfer, Roberto Martín-Martín, and
Oliver Brock. Probabilistic Multi-Class Segmentation for the Amazon Picking
Challenge. IEEE/RSJ International Conference on Intelligent Robots and Systems
(IROS), 2016.
2016 Best Systems Paper Award winner at RSS
Clemens Eppner, Sebastian Höfer, Rico Jonschkowski, Roberto Martín-Martín, Arne
Sieverling, Vincent Wall, and Oliver Brock. Lessons from the Amazon Picking
Challenge: Four Aspects of Building Robotic Systems. Robotics: Science and Systems
(RSS), 2016.
2015 Winner of the Amazon Picking Challenge at ICRA15.
2015 AAAI-15 Robotics Fellowship
2011 PROMOS scholarship from FU Berlin
2011 4th
place RoboCup Worldcup, 2nd place RoboCup German Open,
1st place Technical Challenge @ RoboCup German Open, 1st place RoboCup Iran Open
2010 2nd place RoboCup Worldcup, 1st place Technical Challenge @ RoboCup
Worldcup, 1st place RoboCup Iran Open
2008 2nd place RoboCup German Open
2007 1st place RoboCup Junior German Open
Organized Events
Nature vs. Nurture in Robotics (ICRA16 Workshop)
Slides, Transcript of a radio interview