CV

Education

Ph.D in Version Control Theory, GitHub University, 2018 (expected)
M.S. in Jekyll, GitHub University, 2014
B.S. in GitHub, GitHub University, 2012

Work experience

Spring 2024: Academic Pages Collaborator
- GitHub University
- Duties includes: Updates and improvements to template
- Supervisor: The Users
Fall 2015: Research Assistant
- GitHub University
- Duties included: Merging pull requests
- Supervisor: Professor Hub
Summer 2015: Research Assistant
- GitHub University
- Duties included: Tagging issues
- Supervisor: Professor Git

Skills

Skill 1
Skill 2
- Sub-skill 2.1
- Sub-skill 2.2
- Sub-skill 2.3
Skill 3

Publications

The autoPET3 Challenge: Automated Lesion Segmentation in Whole-Body PET/CT – Multitracer Multicenter Generalization

Dexl, J., Jeblick, K., Mittermeier, A., Schachtner, B., Stüber, A. T., Topalis, J., Rokuss, M., Isensee, F., Maier-Hein, K. H., Kalisch, H., Kleesiek, J., Seibold, C. M., Alasmawi, H., Chan, L. Y. L., Yuan, Y., Jaus, A., Stiefelhagen, R., et al. (2026). The autoPET3 Challenge: Automated Lesion Segmentation in Whole-Body PET/CT – Multitracer Multicenter Generalization. MICCAI 2024 Challenge (autoPET3). arXiv:2605.05775.

IMPACT-Scribe: Interactive Temporal Action Segmentation with Boundary Scribbles and Query Planning

Yin, Q., Wen, D., Peng, K., Schneider, D., Zhong, Z., Jaus, A., Marinov, Z., Wei, J., Liu, R., Zheng, J., Chen, Y., Zhang, C., Qi, L., & Stiefelhagen, R. (2026). IMPACT-Scribe: Interactive Temporal Action Segmentation with Boundary Scribbles and Query Planning. IEEE International Conference on Systems, Man, and Cybernetics (SMC).

IMPACT-HOI: Supervisory Control for Onset-Anchored Partial HOI Event Construction

Zhang, H., Wen, D., Peng, K., Schneider, D., Zhong, Z., Jaus, A., Marinov, Z., Wei, J., Liu, R., Zheng, J., Chen, Y., Zhang, Y., Luo, Y., Qi, L., & Stiefelhagen, R. (2026). IMPACT-HOI: Supervisory Control for Onset-Anchored Partial HOI Event Construction. IEEE International Conference on Systems, Man, and Cybernetics (SMC).

IMPACT-CYCLE: A Contract-Based Multi-Agent System for Claim-Level Supervisory Correction of Long-Video Semantic Memory

Kong, W., Wen, D., Peng, K., Schneider, D., Zhong, Z., Jaus, A., Marinov, Z., Wei, J., Liu, R., Zheng, J., Chen, Y., Qi, L., & Stiefelhagen, R. (2026). IMPACT-CYCLE: A Contract-Based Multi-Agent System for Claim-Level Supervisory Correction of Long-Video Semantic Memory. IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Learning to Look Closer: A New Instance-Wise Loss for Small Cerebral Lesion Segmentation (Oral)

Bouteille, L., Jaus, A., Kleesiek, J., Stiefelhagen, R., & Heine, L. (2026). Learning to Look Closer: A New Instance-Wise Loss for Small Cerebral Lesion Segmentation. In 2026 IEEE 23rd International Symposium on Biomedical Imaging (ISBI). IEEE. https://doi.org/10.1109/ISBI61048.2026.11515682

Good Enough? An Investigation on the Impact of Label Quality in Large-Scale Medical Datasets

Jaus, A., Marinov, Z., Reiß, S., Seibold, C., Wei, J., Kleesiek, J., & Stiefelhagen, R. (2026). Good Enough? An Investigation on the Impact of Label Quality in Large-Scale Medical Datasets. Medical Image Computing and Computer Assisted Intervention (MICCAI).

Is Visual in-Context Learning for Compositional Medical Tasks within Reach?

Reiß, S., Marinov, Z., Jaus, A., Seibold, C., Sarfraz, M. S., Rodner, E., & Stiefelhagen, R. (2025). Is Visual in-Context Learning for Compositional Medical Tasks within Reach? In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV 2025).

GRASPing Anatomy to Improve Pathology Segmentation

Li, K., Jaus, A., Kleesiek, J., & Stiefelhagen, R. (2025). GRASPing Anatomy to Improve Pathology Segmentation. In Z. Cui et al. (Eds.), MLMI 2025 Workshops, LNCS 16241, pp. 487–497. Springer Nature Switzerland.

Semantic Segmentation for Preoperative Planning in Transcatheter Aortic Valve Replacement

Zöllner, C., Reiß, S., Jaus, A., Sholi, A., Sodian, R., & Stiefelhagen, R. (2025). Semantic Segmentation for Preoperative Planning in Transcatheter Aortic Valve Replacement. Statistical Atlases and Computational Models of the Heart (STACOM), held with MICCAI 2025.

Medshapenet–a large-scale dataset of 3d medical shapes for computer vision

Li, Jianning; Zhou, Zongwei; Yang, Jiancheng; Pepe, Antonio; Gsaxner, Christina; Luijten, Gijs; Qu, Chongyu; Zhang, Tiezheng; Chen, Xiaoxi; Li, Wenxuan; . (2025). "Medshapenet–a large-scale dataset of 3d medical shapes for computer vision." Biomedical Engineering/Biomedizinische Technik. 70(1): 71-90.

LIMIS: Towards Language-based Interactive Medical Image Segmentation (Oral)

Heinemann, L., Jaus, A., Marinov, Z., Kim, M., Spadea, M. F., Kleesiek, J., & Stiefelhagen, R. (2025, April). LIMIS: Towards Language-Based Interactive Medical Image Segmentation. In 2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI) (pp. 1-5). IEEE.

Every Component Counts: Rethinking the Measure of Success for Medical Semantic Segmentation in Multi-Instance Segmentation Tasks

Jaus, Alexander; Seibold, Constantin; Reiß, Simon; Marinov, Zdravko; Li, Keyi; Ye, Zeling; Krieg, Stefan; Kleesiek, Jens; Stiefelhagen, Rainer; . (2024). "Every Component Counts: Rethinking the Measure of Success for Medical Semantic Segmentation in Multi-Instance Segmentation Tasks." Proceedings of the AAAI Conference on Artificial Intelligence 2025.

Towards Unifying Anatomy Segmentation: Automated Generation of a Full-Body CT Dataset

Jaus, Alexander; Seibold, Constantin; Hermann, Kelsey; Shahamiri, Negar; Walter, Alexandra; Giske, Kristina; Haubold, Johannes; Kleesiek, Jens; Stiefelhagen, Rainer; . (2024). "Towards Unifying Anatomy Segmentation: Automated Generation of a Full-Body CT Dataset." 2024 IEEE International Conference on Image Processing (ICIP): 41-47.

Taking a Step Back: Revisiting Classical Approaches for Efficient Interactive Segmentation of Medical Images

Marinov, Zdravko; Jaus, Alexander; Kleesiek, Jens; Stiefelhagen, Rainer; . (2024). "Taking a Step Back: Revisiting Classical Approaches for Efficient Interactive Segmentation of Medical Images." Medical Image Segmentation Challenge: 101-125.

Muscles in time: Learning to understand human motion in-depth by simulating muscle activations

Schneider, David; Reiß, Simon; Kugler, Marco; Jaus, Alexander; Peng, Kunyu; Sutschet, Susanne; Sarfraz, M Saquib; Matthiesen, Sven; Stiefelhagen, Rainer; . (2024). "Muscles in time: Learning to understand human motion in-depth by simulating muscle activations." Advances in Neural Information Processing Systems. 37: 67251-67281.

FootCapture: Towards an AR-based System for 3D Foot Object Acquisition through Photogrammetry

Khan-Blouki, Valentin; Seiz, Franziska; Walter, Nicolas; Jaus, Alexander; Marinov, Zdravko; Luijten, Gijs; Egger, Jan; Seibold, Constantin Marc; Solte, Dirk; Kleesiek, Jens; Stiefelhagen, Rainer. (2024). "FootCapture: Towards an AR-based System for 3D Foot Object Acquisition through Photogrammetry." Medical Imaging with Deep Learning

Filters, thresholds, and geodesic distances for scribble-based interactive segmentation of medical images

Marinov, Zdravko; Jaus, Alexander; Kleesiek, Jens; Stiefelhagen, Rainer; . (2024). "Filters, thresholds, and geodesic distances for scribble-based interactive segmentation of medical images." Medical Image Segmentation Challenge: 39-56.

Data Diet: Can Trimming PET/CT Datasets Enhance Lesion Segmentation?

Jaus, Alexander; Reiß, Simon; Kleesiek, Jens; Stiefelhagen, Rainer; . (2024). "Data Diet: Can Trimming PET/CT Datasets Enhance Lesion Segmentation?." MICCAI 2024 autoPET III Challenge — Data-Centric Track.

Anatomy-guided Pathology Segmentation

Jaus, Alexander; Seibold, Constantin; Reiß, Simon; Heine, Lukas; Schily, Anton; Kim, Moon; Bahnsen, Fin Hendrik; Herrmann, Ken; Stiefelhagen, Rainer; Kleesiek, Jens; . (2024). "Anatomy-guided Pathology Segmentation." International Conference on Medical Image Computing and Computer-Assisted Intervention: 3-13.

Towards unifying anatomy segmentation: automated generation of a full-body ct dataset via knowledge aggregation and anatomical guidelines

Jaus, Alexander; Seibold, Constantin; Hermann, Kelsey; Walter, Alexandra; Giske, Kristina; Haubold, Johannes; Kleesiek, Jens; Stiefelhagen, Rainer; . (2023). "Towards unifying anatomy segmentation: automated generation of a full-body ct dataset via knowledge aggregation and anatomical guidelines." arXiv preprint arXiv:2307.13375..

Panoramic panoptic segmentation: Insights into surrounding parsing for mobile agents via unsupervised contrastive learning

Jaus, Alexander; Yang, Kailun; Stiefelhagen, Rainer; . (2023). "Panoramic panoptic segmentation: Insights into surrounding parsing for mobile agents via unsupervised contrastive learning." IEEE Transactions on Intelligent Transportation Systems. 24(4): 4438-4453.

Accurate fine-grained segmentation of human anatomy in radiographs via volumetric pseudo-labeling

Seibold, Constantin; Jaus, Alexander; Fink, Matthias A; Kim, Moon; Reiß, Simon; Herrmann, Ken; Kleesiek, Jens; Stiefelhagen, Rainer; . (2023). "Accurate fine-grained segmentation of human anatomy in radiographs via volumetric pseudo-labeling." arXiv preprint arXiv:2306.03934

Panoramic panoptic segmentation: Towards complete surrounding understanding via unsupervised contrastive learning

Jaus, Alexander; Yang, Kailun; Stiefelhagen, Rainer; . (2021). "Panoramic panoptic segmentation: Towards complete surrounding understanding via unsupervised contrastive learning." 2021 IEEE Intelligent Vehicles Symposium (IV): 1421-1427.

Alexander Jaus

CV