About Me

I am a Lead Research Scientist at Bosch Corporate Research, specializing in robot learning—the intersection of robotics and machine learning. My research focuses on robot skill learning for dexterous manipulation, with broader interests in sequential decision making (reinforcement learning, imitation learning, optimal control), geometric learning and control, and computer vision for object understanding.

I spend my free time with my family and astronomy. Check out my AstroBin page to see my astrophotography work.

Publications

For my complete publication list, visit my Google Scholar profile.

Notable Publications

  • Rozo L., Kupcsik A., et al. The e-Bike motor assembly: Towards advanced robotic manipulation for flexible manufacturing, Robotics and Computer-Integrated Manufacturing, 2024

  • Kupcsik A., et al. Supervised training of dense object nets using optimal descriptors for industrial robotic applications, AAAI, 2021

  • Kupcsik A., Lee W.S., Hsu D. Learning dynamic robot-to-human object handover from human feedback, Robotics Research, 2018

  • Kupcsik A., Deisenroth M., Neumann G., Peters J. Data-efficient generalization of robot skills with contextual policy search, AAAI, 2013

Professional Journey

2022 - Present: Lead Research Scientist at Bosch Corporate Research, focusing on robot learning and industrial applications.
2018 - Present: Research Scientist at Bosch Corporate Research, focusing on robot learning and industrial applications.
2016 - 2018: Joined Sylvain Calinon's lab at Idiap Research Institute in Switzerland to work on the DexRov project.
2014 - 2016: Joined the lab of David Hsu at NUS, focusing on human-robot interaction research.
2010 - 2014: Completed my PhD in robot skill learning at the National University of Singapore. During my studies, I spent 8 months as a PhD sabbatical at TU Darmstadt with Jan Peters' lab.