Lena Maier-Hein

Lena Maier-Hein serves as one of Helmholtz Imaging's center coordinators at the German Cancer Research Center (DKFZ), head of the Intelligent Medical Systems division, managing director of the Data Science and Digital Oncology cross-topic program, and is a full professor at Heidelberg University. She also holds the position of managing director at the National Center for Tumor Diseases (NCT) Heidelberg.

Her research focuses on machine learning-based biomedical image analysis with specific emphasis on surgical data science, computational biophotonics, and validation of machine learning algorithms. As a fellow of both the Medical Image Computing and Computer Assisted Intervention (MICCAI) society and the European Laboratory for Learning and Intelligent Systems (ELLIS), she leads significant initiatives including presidency of the MICCAI special interest group on challenges and chairing the international surgical data science initiative.

Her publication portfolio demonstrates strong focus on algorithm validation, surgical data science, and medical imaging AI, with recent work addressing critical issues in reproducibility, bias in medical AI, and practical clinical implementation. The articles reveal consistent themes around establishing rigorous validation frameworks, developing practical surgical AI tools, and addressing real-world deployment challenges in medical imaging.

Her notable scientific recognition includes:

• 2013 Heinz Maier Leibnitz Award of the German Research Foundation (DFG)
• 2017/18 Berlin-Brandenburg Academy Prize
• European Research Council (ERC) starting grant (2015-2020)
• ERC consolidator grant (2021-2026)

She serves on the editorial boards of prestigious journals including Nature Scientific Data, IEEE Transactions on Pattern Analysis and Machine Intelligence, and Medical Image Analysis, demonstrating her leadership in establishing standards for medical imaging research. Her work bridges fundamental AI research with practical clinical applications, particularly in surgical settings where real-time decision support is critical.