Research Group Carsten Marr
Carsten Marr
Prof. Dr.
Principal Investigator
Carsten Marr
is Professor of Artificial Intelligence in Cell Therapy and Hematology at LMU Munich and Director of the Institute of AI for Health at Helmholtz Munich.
His lab focuses on improving the diagnosis, treatment, and understanding of severe blood disorders. The team develops machine learning algorithms to classify individual cells and patients and uses single-cell data to identify potential drug targets. Combining AI with mechanistic models of haematopoiesis – the production of blood cells – is a key focus of their research.
Team members @MCML
PostDocs
Ario Sadafi
→ Group Carsten Marr
Artificial Intelligence in Cell Therapy and Hematology
→ Co-Group Nassir Navab
Recent News @MCML
Publications @MCML
2025
[3]
S. S. Boushehri • S. Kazeminia • A. Gruber • C. Matek • K. Spiekermann • C. Pohlkamp • T. Haferlach • C. Marr
A large expert-annotated single-cell peripheral blood dataset for hematological disease diagnostics.
Scientific Data 12.1773. Nov. 2025. DOI
A large expert-annotated single-cell peripheral blood dataset for hematological disease diagnostics.
Scientific Data 12.1773. Nov. 2025. DOI
[2]
R. M. Umer • D. Sens • J. Noll • C. Matek • L. Wolfseher • R. Spang • R. Huss • J. Raffler • S. Reinke • W. Klapper • K. Steiger • K. Schwamborn • C. Marr
A Multicenter Benchmark of Multiple Instance Learning Models for Lymphoma Subtyping from HE-stained Whole Slide Images.
Preprint (Nov. 2025). URL
A Multicenter Benchmark of Multiple Instance Learning Models for Lymphoma Subtyping from HE-stained Whole Slide Images.
Preprint (Nov. 2025). URL
[1]
S. Kazeminia • C. Marr • B. Rieck
Topological Inductive Bias fosters Multiple Instance Learning in Data-Scarce Scenarios.
Transactions on Machine Learning Research. Feb. 2025. URL GitHub
Topological Inductive Bias fosters Multiple Instance Learning in Data-Scarce Scenarios.
Transactions on Machine Learning Research. Feb. 2025. URL GitHub
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