At ISAS, Dr Jianxu Chen heads the AMBIOM - Analysis of Microscopic BIOMedical Images junior research group, funded by the German Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung, BMBF). His research revolves around biomedical image analyses and deep learning. Chen is an expert in the development of scalable biomedical image analysis algorithms based on artificial intelligence (AI), for example for the coordination and evaluation of three-dimensional microscopy images. After having completed his doctorate in computer science at the University of Notre Dame in Indiana, USA, Chen worked at the Allen Institute for Cell Science in Seattle. There, he led the microscopy image analysis work on research and development as well as preparing large-scale microscopy image analysis algorithms for production. To become a group leader at ISAS, Chen moved his family of four to the Ruhr area.
Dr. Jianxu Chen
Select publications
Journal of leukocyte biology, Vol. 117, No. 2, 2025
Cibir Z, Beer A, Kraus A, Pillibeit A, Bludau D, Abdulla H, Neuendorff NR, Sonneck J, Kowitz L, Riese S, Tuz A, Chen J, Cherneha M, Beelen DW,…
Risk beyond neutropenia: insights into neutrophil migration from newly diagnosed AML until late after allogeneic stem cell transplantation
https://doi.org/10.1093/jleuko/qiae250
Journal of Neuroinflammation, Vol. 22, No. 1, 2025
Christ R, Siemes D, Zhao S, Widera L, Spangenberg P, Lill J, Thiebes S, Bottek J, Borgards L, Pinho AG, Silva NA, Monteiro S, Jorch SK, Gunzer M,…
Inhibition of tumour necrosis factor alpha by Etanercept attenuates Shiga toxin-induced brain pathology
https://doi.org/10.1186/s12974-025-03356-z
Computational Mechanics, Vol. 2025, 2025
Shi R, Yang H, Chen J, Hackl K, Avril S, He Y.
Deep learning without stress data on the discovery of multi-regional hyperelastic properties
https://doi.org/10.1007/s00466-024-02591-0
Biomedizinische Technik / Biomedical engineering, Vol. 70, No. 1, 2024, P. 71-90
Li J, Zhou Z, Yang J, Pepe A, Gsaxner C, Luijten G, Qu C, Zhang T, Chen X, Li W, Wodzinski M, Friedrich P, Xie K, Jin Y, Ambigapathy N, Nasca E,…
MedShapeNet - a large-scale dataset of 3D medical shapes for computer vision.
https://doi.org/10.1515/bmt-2024-0396
Biological Imaging, Vol. 4, 2024, P. e16
Zhou Y, Sollmann J, Chen J.
Deep-learning-based image compression for microscopy images: An empirical study
https://doi.org/10.1017/S2633903X24000151