Postdoctoral Researcher at University of Düsseldorf
Dusseldorf, North Rhine-Westphalia, Germany
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Summary
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Benjamin Ruppik is a postdoctoral researcher combining a decade of mathematical training with hands-on deep learning expertise to advance representation learning for NLP and dialogue systems. Holding a PhD in low-dimensional topology from the Max Planck–University of Bonn collaboration, he applies Topological Data Analysis to probe and improve how large language models encode meaning. Based at Heinrich-Heine-University Düsseldorf’s Dialog Systems and Machine Learning lab, Ben bridges theory and practice—evidenced by full‑stack contributions like extending a point-cloud labeling tool with OpenGL shader and UI work. His background in semantic segmentation and LiDAR processing gives him an uncommon perspective on spatial and linguistic representations, enabling cross-domain insights into model robustness and structure.
10 years of coding experience
PhD Mathematics, Low-dimensional topology, PhD Mathematics, Low-dimensional topology at Max Planck Society
Master of Science - MS, Mathematics, Master of Science - MS, Mathematics at The University of Bonn
Contributions summary:Benjamin implemented features related to point cloud data manipulation and visualization within the point labeling tool. They added functionality for cutting point clouds using a plane, enabling the specification of plane parameters through sliders. The changes included modifications to both the front-end (UI) and back-end (OpenGL shaders), demonstrating a full-stack approach to the project.
Contributions:8 PRs, 100 pushes, 10 branches in 8 years 2 months
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Benjamin Ruppik - Postdoctoral Researcher at University of Düsseldorf