Max Upravitelev

Max Upravitelev is a Researcher and doctoral student at the Quality and Usability Lab (Q&U Lab) at Technische Universität Berlin, affiliated with the XplaiNLP group. Previously, he served as a research associate at Fraunhofer FOKUS, contributing to projects in learning technologies and image processing. His academic journey includes a BA in Philosophy/Social Sciences, an MA in European History and Literature, and a second master's in Practical Computer Science from Fernuniversität Hagen.

• Education:
• BA Philosophy & Social Sciences
• MA European History & Literature
• M.Sc. Practical Computer Science (Fernuniversität Hagen)

His research focuses on multimodal semantic search, knowledge graph construction, and interpretability of transformer/GNN-based architectures. He explores numerical-symbolic reasoning across textual, visual, and graphical data, and designs software systems integrating ML components. Current work emphasizes narrative modeling from interdisciplinary angles and automated evaluation of LLM-based systems.

No scientific awards explicitly mentioned in the text. His doctoral research examines knowledge graph applications in visual question answering. He has collaborated with Fraunhofer FOKUS on future applications and media projects. No grants or advising roles listed in the provided data.

Affiliated with the Q&U Lab and XplaiNLP team at TU Berlin, focusing on advancing explainable AI and interdisciplinary computational methods.