Adrian Röfer is an ELLIS PhD student at the Robot Learning Lab, University of Freiburg, focused on inferring the intent behind demonstrated tasks from minimal data using deep vision features and statistical methods. He combines a strong experimental mindset with practical software engineering, implementing reusable robotics tools—such as a differentiable kinematics library, a PyBullet wrapper, and workspace visualization utilities—that he relies on daily. With nine years of experience spanning academia and industry, Adrian has applied data-driven approaches to robot motion control and deployed computationally efficient motion generation systems at Amazon. He is comfortable across RL, ROS, and simulation-to-reality tooling, and prefers large-scale quantitative experiments that yield precise insights. Colleagues can expect code-first research that prioritizes reproducibility and tooling to accelerate future work.
9 years of coding experience
3 years of employment as a software developer
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at University of Bremen
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at Universität Bremen
Contributions:3 reviews, 4 PRs, 6 pushes in 1 year 6 months
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Adrian Röfer - PhD Student at University of Freiburg