Maximilian Thiessen

Maximilian Thiessen is a PhD student in machine learning at Technische Universität Wien, supervised by Thomas Gärtner. He is affiliated with the machine learning research unit and collaborates with the Laila lab in Milan.

Research Interests:

• Learning with graphs
• Active learning frameworks
• Convexity theory in ML
• Computational learning theory

Recent Research Trends include: (1) Expressive GNN architectures for outerplanar graphs (2025), (2) Generalized boosting theory through game frameworks (2024), (3) Efficient monophonic halfspace learning (2024), (4) Abstention mechanisms in contextual bandits (2024), (5) Global feature extensions in GNNs (2023), and (6) Expectation-complete graph representations (2023).

Scientific Awards:

• 2024: DOC Fellowship from Austrian Academy of Sciences
• 2023: Best Poster Award at G-Research's ICML Poster Party

Community Contributions: Organizer of Mining and Learning with Graphs (MLG) workshops at ECMLPKDD 2022-2024, co-organizer of Graph Learning on Wednesdays (GLOW) reading group, and session chair at ECMLPKDD'23.