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Hi! I'm Daniel

How can we turn AI into applications that create value in the real world? As a postdoctoral researcher in medical imaging I focus on building machine learning and computer vision models designed to hold up outside the lab. My work spans self-supervised learning, generative modeling, anomaly detection, and domain adaptation, with a focus on making models robust enough for deployment on messy, real-world data.

Publications

For a comprehensive list have a look at Google Scholar.
Hierarchical Adaptive networks with Task vectors for Test-Time Adaptation

Hierarchical Adaptive networks with Task vectors for Test-Time Adaptation

Sameer Ambekar, Marta Hasny, Laura Alexandra Daza, Daniel M. Lang* and Julia A. Schnabel*

WACV 2026

Journal
Temporal Neural Cellular Automata: Application to modeling of contrast enhancement in breast MRI

Temporal Neural Cellular Automata: Application to modeling of contrast enhancement in breast MRI

Daniel M. Lang, Richard Osuala, Veronika Spieker, Karim Lekadir, Rickmer Braren and Julia A. Schnabel

MICCAI 2025

arXiv Journal Project Code
Towards learning contrast kinetics with multi-condition latent diffusion models

Towards learning contrast kinetics with multi-condition latent diffusion models

Richard Osuala, Daniel M. Lang, Preeti Verma, Smriti Joshi, ..., Julia A. Schnabel and Karim Lekadir

MICCAI 2024

arXiv Journal Code
Multispectral 3D masked autoencoders for anomaly detection in non-contrast enhanced breast MRI

Multispectral 3D masked autoencoders for anomaly detection in non-contrast enhanced breast MRI

Daniel M. Lang, Eli Schwartz, Cosmin I. Bercea, Raja Giryes and Julia A. Schnabel

MICCAI Workshop on Cancer Prevention through Early Detection 2023

arXiv Journal
Deep Learning Based HPV Status Prediction for Oropharyngeal Cancer Patients

Deep Learning Based HPV Status Prediction for Oropharyngeal Cancer Patients

Daniel M. Lang, Jan C. Peeken, Stephanie E. Combs, Jan J. Wilkens and Stefan Bartzsch

Cancers 2021

arXiv Journal Code

Resume

Experience

11/2022 - Present

Postdoctoral Researcher, Helmholtz Munich

Institute of Machine Learning in Biomedical Imaging

11/2022 - Present

Visiting Researcher, TUM Klinikum rechts der Isar

Institute for Diagnostic and Interventional Radiology

11/2018 - 10/2022

Doctoral Researcher, Helmholtz Munich

Institute of Radiation Medicine

02/2019 - 10/2022

Visiting Researcher, TUM Klinikum rechts der Isar

Department of Radiation Oncology

Education

11/2018 - 10/2022

PhD in Physics, Technical University of Munich

Grade: Magna cum laude

10/2016 - 06/2018

MSc. in Physics, University of Regensburg and DESY Hamburg

10/2012 - 09/2016

BSc. in Physics, University of Regensburg

09/2010 - 09/2012

University Entrance Qualification, Maximilian-Kolbe Schule, Neumarkt i.d. OPf.

09/2006 - 04/2010

Apprenticeship as Industrial Electronics Technician, MAN Nutzfahrzeuge AG, Nuremberg

Fellowships

02/2026 - 04/2026

Science Meets Politics Fellow in the Office of Ayşe Asar, MP

Funded by the Wilhelm and Else Heraeus Foundation

03/2024 - 03/2026

Helmholtz High Potentials Fellow

Helmholtz Munich Postdoc Program

05/2022 - 07/2022

Research Stay at University of Tel Aviv, School of Electrical Engineering

Funded by the Helmholtz Israel Exchange Program