楊林

1999年畢業於西安交通大學，獲工學學士學位；

2002年獲西安交通大學信息與通訊工程碩士學位；

2006年、2009年分別獲羅格斯大學電子與計算機工程碩士和博士學位。

2009年至2011年，擔任羅格斯大學病理學系、放射學系和生物醫學工程系的助理教授。

2011年至2014年，擔任計算機科學系的助理教授，並於2014年獲得終身副教授。

2020年加入西湖大學工學院，成立人工智能與生物醫學影像實驗室，從事人工智能、醫學影像、機器學習等醫工交叉方面的研究工作。 ^[1] 

楊林博士聚焦生物醫學圖像分析、圖像信息學和機器學習領域，已有超過15年的研究經驗。在利用大數據進行計算機輔助診斷和預測、生物醫學圖像分析、數字病理和人工智能領域做出了重大貢獻。

課題組長期從事醫學圖像分析、圖像信息學、計算機輔助診斷、數據挖掘、機器學習、計算機視覺、雲計算和大數據等領域的研究。 ^[1] 

1. Jiatong Cai, Chenglu Zhu, Can Cui, Honglin Li, Tong Wu, Shichuan Zhang, Lin Yang, “Generalizing Nucleus Recognition Model in Multi-source Ki67 Immunohistochemistry Stained Images via Domain-specific Pruning”, MICCAI, 2021.

2. X. Shi, F. Xing, Z. Zhang, M. Sapkota, Z. Guo, and L.Yang, “A scalable optimization mechanism for pairwise based discrete hashing”, IEEE Transactions on Image Processing, vol. 30, pp. 1130–1142, 2020.

3. Xiaoshuang Shi,Zhenhua Guo,Fuyong Xing,Yun Liang, Lin Yang, “Anchor-based self-ensembling for semi-supervised deep pairwise hashing”,International Journal of Computer Vision, pp. 1-18, 2020.

4. H. Li, X. Han, Y. Kang, X. Shi, M. Yan, Z. Tong, Q. Bu, L. Cui, J. Feng, and L. Yang, “A novel loss calibration strategy for object detection networks training on sparsely annotated pathological datasets”, in International Conference on Medical Image Computing and Computer-Assisted Intervention（MICCAI）. Springer, pp. 320–329, 2020.

5. X. Shi, F. Xing, Y. Xie, Z. Zhang, L. Cui, and L. Yang, “Loss-based attention for deep multiple instance learning”, AAAI Conference on Artificial Intelligence, Vol.34, No.04, pp. 5742–5749, 2020.

6. P. Chen, J. Cai, and L.Yang,“Chromosome segmentation via data simulation and shape learning”, in 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).IEEE, pp. 1637–1640, 2020.

7. X Shi, H Su, F Xing, Y Liang, G Qu, L Yang,“Graph temporal ensembling based semi-supervised convolutional neural network with noisy labels for histopathology image analysis”, Medical Image Analysis, 2020.

8. Zizhao Zhang, Pingjun Chen, Mason McGough, Fuyong Xing, Chunbao Wang, Marilyn Bui, Yuanpu Xie, Manish Sapkota, Lei Cui, Jasreman Dhillon, Nazeel Ahmad, Farah K. Khalil, Shohreh I. Dickinson, Xiaoshuang Shi, Fujun Liu, Hai Su, Jinzheng Cai, Lin Yang, “Pathology-level interpretable whole-slide cancer diagnosis with deep learning”, Nature Machine Intelligence, Vol.1, pp.236-245, 2019.

9. Jinzheng Cai, Zizhao Zhang, Lei Cui, Yefeng Zheng, Lin Yang, “Towards cross-modal organ translation and segmentation: A cycle- and shape-consistent generative adversarial network”, Medical Image Analysis, Vol.52, pp.174-184, 2019.

10. Hai Su, Lin Yang, “Local and global consistency regularized mean teacher for semi-supervised nuclei classification”, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019.

11. Zizhao Zhang, Pingjun Chen, Xiaoshuang Shi, Lin Yang, “Text-guided neural network training to recognize images in nature scene and medicine”, IEEE Transaction on Pattern Analysis and Machine Intelligence (TPAMI), 2019.

12. Manish Sapkota, Xiaoshuang Shi, Fuyong Xing, Lin Yang, “Deep Convolutional Hashing for Low Dimensional Binary Embedding of Histopathological Images”, IEEE Journal of Biomedical and Health Informatics,Vol.23,No.2, pp. 805-816, 2019

13. Zizhao Zhang, Fuyong Xing, Xiaoshuang Shi, Lin Yang, “Revisiting Graph Construction for Fast Image Segmentation”, Pattern Recognition (PR), 2018.

14. Zizhao Zhang*, Yuanpu Xie*, Lin Yang, “Photographic Text-to-Image Synthesis with a Hierarchically-nested Adversarial Network”, International Conference on Computer Vision and Pattern Recognition (CVPR), pp.6199-6208, 2018.

15. Zizhao Zhang, Yuanpu, Xie, Fuyong Xing, Mason Mcgough, Lin Yang, “MDNet: A Semantically and Visually Interpretable Medical Image Diagnosis Network”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.

16. Yuanpu Xie, Zizhao Zhang, Manish Sapkota, Lin Yang, "Spatial Clockwork Recurrent Neural Network for Muscle Perimysium Segmentation", in the 19th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2016.

17. Fuyong Xing, Lin Yang, “An automatic learning-based framework for robust nucleus segmentation”, IEEE Transaction on Medical Imaging, Vol.35, No.2, pp. 550-566, 2016.

18. Christopher S. Fry, Jonah D. Lee, Jyothi Mula, Tyler J. Kirby, Janna R. Jackson, Fujun Liu, Lin Yang, Esther E. Dupont-Versteegden, John J. McCarthy, Charlotte A. Peterson, "Inducible depletion of satellite cells in adult, sedentary mice impairs muscle regenerative capacity without affecting sarcopenia", Nature Medicine, Vol. 21, pp. 76-80, 2015.

19. Lin Yang, Xin Qi, Fuyong Xing, Tahsin Kurc, Joel Saltz, David J. Foran, “Parallel Content Based Sub-image Retrieval Using Hierarchical Searching”, Bioinformatics, Vol.30, No.7, pp. 996-1002, 2014.

20. Nicolas Wein, Adeline Vulin, Maria Sofia Falzarano, Christina Al-Khalili Szigyarto, Baijayanta Maiti, Andrew Findlay, Kristin H. Heller, Mathias Uhlen, Baskar Bakthavachalu, Sonia Messina, Giuseppe Vita, Chiara Passarelli, Francesca Gualandi, Steve D. Wilton, Louise Rodino-Klapec, Lin Yang, Diane M. Dunn, Daniel Schoenberg, Robert B. Weiss, Michael T. Howard, Alessandra Ferlini, Kevin M. Flanigan, "Translation from a DMD exon 5 IRES results in a functional dystrophin isoform that attenuates dystrophinopathy in humans and mice", Nature Medicine, Vol.20, No.9, pp. 992-1000, 2014. ^[1] 

曾在MICCAI等國際大會中獲得2015年青年科學家最佳論文獎等獎項。 ^[1]