team
Core group members, including postdocs and PhD students.
Tim Schopf
Tim Schopf is a postdoctoral researcher since January 2025. He earned his PhD in 2024 from Technical University of Munich. His current interests includes LLMs for scientific reasoning, AI agents for scientific discovery, attributed scientific text generation, and scientific claim verification of AI-generated content.
📧 tim.schopf@tu-dresden.de 📚 Google Scholar 🔗 Personal Website
Shuzhou Yuan
Shuzhou Yuan’s research interests includes Natural Language Processing, Large Language Models, and Graph Neural Networks. He has contributed to publications such as “Hallucinations Can Improve Large Language Models in Drug Discovery” and “GraSAME: Injecting Token-Level Structural Information to Pretrained Language Models via Graph-guided Self-Attention Mechanism.”
📧 shuzhou.yuan@tu-dresden.de 📚 Google Scholar 🔗 Personal Website
Zhan Qu
Zhan Qu’s research interests lie in the areas of explainable AI, machine learning, natural language processing, and graph neural networks. He has contributed to KDD’25 publications such as “Explainable LiDAR 3D Point Cloud Segmentation and Clustering for Detecting Airplane-Generated Wind Turbulence”.
Parisa Aghdam
Parisa Aghdam’s research interests lie in the areas of machine learning, natural language processing and data science. Currently, she is working on scientific text summarization and simplification. She has contributed to publication such as “SimplifyMyText: An LLM-Based System for Inclusive Plain Language Text Simplification”.
Tobias Schreieder
Tobias Schreieder’s research interests lie in the areas of information retrieval, natural language processing and privacy. Currently, he is working on citation-aware large language models - the idea of giving LLMs the ability to cite the references used to create responses.
Nicholas Popovic
Nicholas Popovic’s research interests lie in natural language processing and machine learning, with a particular focus on representation learning for information extraction. He has contributed to EMNLP’25 publications such as “Embedded Named Entity Recognition using Probing Classifiers.”
📧 nicholas.popovic@tu-dresden.de 📚 Google Scholar 🔗 Personal Website
Chen Shao
Chen Shao’s research interests includes Machine Learning and Graph Neural Networks. She has contributed to publications such as “A Novel Machine Learning-based Equalizer for a Downstream 100G PAM-4 PON”.