Tom Oberhauser

Tom Oberhauser is a Researcher and research assistant at DATEXIS since December 2018. He holds a Bachelor of Science and a Master of Science in Media Informatics, both completed with distinction. His research focuses on Active Learning, Human-in-the-Loop methodologies, Training Data Augmentation, and Few-Shot/Zero-Shot Learning. He is currently involved in the Smart-MD project, which explores neural paragraph retrieval in medical contexts. Tom has contributed to multiple interdisciplinary projects, including RelVis (benchmarking OpenIE systems) and TrainX (NLP with bi-encoders). His work bridges theoretical advancements in machine learning with practical applications in healthcare and information retrieval.

Tom participates in the Berlin-based Master Data Science program and is part of the Graduate School cohort. His academic contributions span NLP, medical informatics, and semantic web technologies, reflecting a commitment to both foundational research and real-world problem-solving.