Thomas Steffek

Thomas Steffek is a researcher at Beuth University for Applied Sciences, affiliated with the Data Science and Text-based Information Systems (DATEXIS) group. He holds a Bachelor of Science (2019) and Master's degree (2023) from the same institution. His research focuses on applying Natural Language Processing (NLP) to healthcare challenges, including clinical outcome prediction, assertion detection in medical notes, and contextualized document retrieval for clinical decision-making. He has contributed to projects like Smart-MD and explored data drift in clinical data analytics.

His work spans healthcare informatics, machine learning applications in medicine, and neural network-based retrieval systems. Collaborations include projects with Alexander Löser and Paul Grundmann, addressing topics like media bias detection and in-database text mining (e.g., INDREX). While no formal teaching roles are explicitly stated, he has tutored peers during his studies.