Rudolf Schneider is a research assistant at DATEXIS at Beuth University of Applied Sciences.
He studied computer science at Fachhochschule Brandenburg - University of Applied Sciences (B.Sc.) and Beuth University of Applied Sciences (M.Sc.). His current research is focused on extracting information of large amount of diverse text like clinical notes and recommending medical publications based on medical health records.
In his spare time he involves himself in the organization of a heavy metal festival and enjoys attending Chaos Computer Club events.
Rudolf is currently working in the BMWi funded MACSS project.
- Deep Learning
- Information Extraction
- Information Retrieval
- MACSS - Medical Allround-Care Service Solutions
- BeuthVR – Oculus Rift Multiplayer tech-demo for the long night of sciences at Beuth university
- October 2019 PHD Colloquium at Einstein Center Digital Future (ECDF)
- March 2019 MACSS project closing at the Lecture Hall Ruin of Charité Berlin
- November 2018 Presentation of our projects results in MACSS at the S³ - Smart Service Summit at Federal Ministry of Economics and Technology (Germany)
- November 2018 Leibniz Startup & Industry Event "Künstliche Intellegenz" in the atrium of Leibniz Universität Hannover organized by Forschungszentrum L3S. Presentation of solutions developed in MACSS
- April 2018 "Neural Text Mining for Clinical Environments" at German Finnish DigiSummit 2018 - Smart Data Forum, Berlin
- June 2018 “Masochismus für Fortgeschrittene – Promovieren an der Fachhochschule” at Beuth University of Applied Sciences
- June 2018 “Neural Passage Retrieval in Joint Embedding Spaces” at Institute for Web Science and Technologies - University Koblenz-Landau
- June 2017 "RelVis: Exploring and Benchmarking OpenIE Systems" at Hasso Plattner Institute - Potsdam
- March 2017 "Open Information Extraction in Idiosyncratic Domains - an Evaluation" at Institute for Web Science and Technologies - University Koblenz-Landau
- Rudolf Schneider, Tom Oberhauser, Paul Grundmann, Felix Alexander Gers, Alexander Loeser and Steffen Staab. Is Lanugage Modeling enough? Evaluating Effective Embedding Combinations. LREC 2020 [Dataset / Code]
- Sebastian Arnold, Rudolf Schneider, Philippe Cudré-Mauroux, Felix A. Gers and Alexander Löser. SECTOR: A Neural Model for Coherent Topic Segmentation and Classification. Transactions of the Association for Computational Linguistics (2019). [PDF] [code] [dataset]
- Rudolf Schneider, Sebastian Arnold, Tom Oberhauser, Tobias Klatt, Thomas Steffek and Alexander Löser: Smart-MD: Neural Paragraph Retrieval of Medical Topics. World Wide Web Conference (Companion). IW3C2, 2018: 203–206 [PDF]
- R. Schneider, S. Arnold, T. Oberhauser, T. Klatt, T. Steffek, A. Löser, "Smart-MD: Neural Paragraph Retrieval of Medical Topics", WWW ’18 Companion: The 2018 Web Conference Companion, April 23–27, 2018, Lyon, France. ACM, New York, NY, USA, 4 pages. [video]
- R. Schneider, T. Oberhauser, T. Klatt, F. A. Gers, and A. Löser, “RelVis: Benchmarking OpenIE Systems,” ISWC 2017 The 16th International Semantic Web Conference - Posters and Demos, p. to appear. [video]
- R. Schneider, T. Oberhauser, T. Klatt, F. A. Gers, and A. Löser, “Analysing Errors of Open Information Extraction Systems,” BLGNLP 2017 Building Linguistically Generalizable NLP Systems at EMNLP 2017. [arXiv] [slides]
- R. Schneider, C. Guder, T. Kilias, A. Löser, J. Graupmann, and O. Kozachuk, “Interactive Relation Extraction in Main Memory Database Systems,” Proceedings of the 26th International Conference on Computational Linguistics.
- TheWebConf 2020 Research Track – External Reviewer
- AAAI 2020 – External Reviewer
- EMNLP 2019 – External Reviewer
- NAACL HTL 2018 Industry Track - External Reviewer
- ISWC 2018 Research Track - External Reviewer
- T. Steffek, “Neural Facet Detection on Medical Resources,” Bachelor Thesis, Beuth University of Applied Sciences, Berlin, Germany, 2019.
- T. Oberhauser, “Neural Information Retrieval with Vector Space Queries,” Master Thesis, Beuth University of Applied Sciences, Berlin, Germany, 2019
- T. Schilling, “Information Retrieval mit Satz- und Wortembeddings,” Master Thesis, Beuth University of Applied Sciences, Berlin, Germany, 2018.
- T. Klatt, “A Graphical Training Interface for Named Entity Recognition,” Bachelor Thesis, Beuth University of Applied Sciences, Berlin, Germany, 2018.