Volker Tresp

Volker Tresp is a Professor at the Ludwig-Maximilians-Universität München (LMU) and a leading researcher in machine learning for relational structured domains. His work bridges cognitive AI, knowledge graphs, and quantum computing. He is a PI in the Munich Center for Machine Learning (MCML) and co-director of the ELLIS program on Semantic, Symbolic, and Interpretable Machine Learning.

His research interests focus on temporal knowledge graphs, foundation models, multimodal learning, and quantum machine learning. Recent projects include WebPilot (multi-agent web task execution) and FedBiP (federated learning with diffusion models). His work on PyKEEN and RESCAL has advanced knowledge graph embeddings.

Volker Tresp's scientific contributions are recognized through ELLIS Fellowship (2020), Siemens Inventor of the Year (1996), and Best Paper Awards at ISWC 2021 and IEEE ICHI 2020. His students have published extensively at top AI venues like AAAI, CVPR, and ECCV.

Awards and Honors:

• ELLIS Fellow (2020)
• Siemens Inventor of the Year (1996)
• Best Paper Award, ISWC 2021
• Student Best Paper Award, ISWC 2017
• Best Paper Runner-up, PKDD 2005