Zhenlin Xu

Ph.D. in Computer Science

UNC Chapel Hill

Zhenlin Xu finished his Ph.D. in computer science in 2022. He worked on deep learning approaches for image registration, image segmentation, and learning robust and generalizable visual representation. See more about him here. He currently works at Amazon.

Interests

Medical Image Analysis
Computer Vision
Machine Learning

Education

PhD in Computer Science, 2022

UNC Chapel Hill
MSc in Imaging Science, 2016

Rochester Institute of Technology
BSc in Optical Information Science and Technology, 2014

Xi'an Jiaotong University

Latest

Zhenlin Xu, Marc Niethammer, Colin Raffel (2022). Compositional Generalization in Unsupervised Compositional Representation Learning: A Study on Disentanglement and Emergent Language. NeurIPS.
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Chao Huang, Zhenlin Xu, Zhengyang Shen, Tianyou Luo, Tengfei Li, Daniel Nissman, Amanda Nelson, Yvonne Golightly, Marc Niethammer, Hongtu Zhu (2022). DADP: Dynamic abnormality detection and progression for longitudinal knee magnetic resonance images from the Osteoarthritis Initiative. Medical Image Anal..
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Qin Liu, Zhenlin Xu, Yining Jiao, Marc Niethammer (2022). iSegFormer: Interactive Segmentation via Transformers with Application to 3D Knee MR Images. Medical Image Computing and Computer Assisted Intervention - MICCAI 2022 - 25th International Conference, Singapore, September 18-22, 2022, Proceedings, Part V.
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Qin Liu, Zhenlin Xu, Gedas Bertasius, Marc Niethammer (2022). SimpleClick: Interactive Image Segmentation with Simple Vision Transformers. CoRR.
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Zhenlin Xu (2022). Towards Deep Visual Learning in the Wild: Data-efficiency, Robustness and Generalization.
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Zhenlin Xu, Deyi Liu, Junlin Yang, Colin Raffel, Marc Niethammer (2021). Robust and Generalizable Visual Representation Learning via Random Convolutions. 9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3-7, 2021.
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Xu Han, Zhengyang Shen, Zhenlin Xu, Spyridon Bakas, Hamed Akbari, Michel Bilello, Christos Davatzikos, Marc Niethammer (2020). A Deep Network for Joint Registration and Reconstruction of Images with Pathologies. Machine Learning in Medical Imaging - 11th International Workshop, MLMI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings.
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Sahin Olut, Zhengyang Shen, Zhenlin Xu, Samuel Gerber, Marc Niethammer (2020). Adversarial Data Augmentation via Deformation Statistics. Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XXIX.
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Zhengyang Shen, Zhenlin Xu, Sahin Olut, Marc Niethammer (2020). Anatomical Data Augmentation via Fluid-Based Image Registration. Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 - 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part III.
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Zhenlin Xu, Marc Niethammer (2019). DeepAtlas: Joint Semi-supervised Learning of Image Registration and Segmentation. Medical Image Computing and Computer Assisted Intervention - MICCAI 2019 - 22nd International Conference, Shenzhen, China, October 13-17, 2019, Proceedings, Part II.
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Zhengyang Shen, Xu Han, Zhenlin Xu, Marc Niethammer (2019). Networks for Joint Affine and Non-Parametric Image Registration. IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2019, Long Beach, CA, USA, June 16-20, 2019.
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Zhenlin Xu, Zhengyang Shen, Marc Niethammer (2018). Contextual Additive Networks to Efficiently Boost 3D Image Segmentations. Deep Learning in Medical Image Analysis - and - Multimodal Learning for Clinical Decision Support - 4th International Workshop, DLMIA 2018, and 8th International Workshop, ML-CDS 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings.
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