教师简介

梁小丹，教授，博士生导师，中山大学“百人计划”人才引进，主要从事机器学习、计算机视觉、智慧医疗等方面的研究。 

电子邮箱：xdliang328@gmail.com

个人主页：https://lemondan.github.io

研究领域

机器学习，计算机视觉，自然语言理解，智慧医疗，智能驾驶

获奖及荣誉

1. 2019 阿里巴巴达摩院青橙奖
2. 2019 吴文俊人工智能优秀青年奖
3. 2018 国际计算机人工智能学会ACM China 优秀博士论文奖(中国地区每年共2名)
4.2018中国计算机学会优秀博士论文奖(每年10名)
5.国家级2011高性能计算协同创新中心优秀博士论文奖（每年10名）

教育背景

2007-2011：中山大学，硕士学位

2011-2016：中山大学，博士学位
       

工作经历

2014-2016：新加坡国立大学，访问学者

2016-2018：美国卡内基梅隆大学，研究员

2018-至今：中山大学，副教授

主要学术兼职

1.国际知名期刊Pattern Recognition Letters 和journal of Multimedia Tools and Applications的客座编辑

2.Programm Committee member of CVPR 2017, IJCAI 2017-2018, AAAI 2017-2019. Reviewer for TPAMI, IJCV, TKDE, TMM, TIP, TNNLS, TCSVT, and so on。

3.Reviewer for CVPR, ECCV, ACM MM, AAAI, NIPS, IJCAI, and so on

科研项目

1.国家自然科学基金面上项目（主持, 2020.01~2023.12）  
2.国家自然科学区域联合基金重点项目（合作单位负责人, 2020.01~2023.12） 
3.广东省基础与应用基础研究基金-重点项目（主持, 2020.01~2022.12） 

代表性论著

1.Xiaodan Liang, Si Liu, Xiaohui Shen, Jianchao Yang, Luoqi Liu, Jian Dong, Liang Lin, Shuicheng Yan. Deep Human Parsing with Active Template Regression. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 37(12): 2402-2414, 2015. (SCI, 中科院一分区, 影响因子: 9.455)

2.Xiaodan Liang, Liang Lin, Yunchao Wei, Xiaohui Shen, Jianchao Yang, Shuicheng Yan. Proposal-free Network for Instance-level Semantic Object Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), DOI: 10.1109/TPAMI.2017.2775623, 2017. (SCI,中科院一分区, 影响因子: 9.455)

3.Xiaodan Liang, Yunchao Wei, YunPeng Chen, Jianchao Yang, Liang Lin, Shuicheng Yan. Learning to Segment Human by Watching YouTube. IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 39(7): 1462-1468, 2017. (SCI, 中科院一分区, 影响因子: 9.455)

4.Xiaodan Liang, Chunyan Xu, Xiaohui Shen, Jianchao Yang, Jinhui Tang, Liang Lin, Shuicheng Yan. Human Parsing with Contextualized Convolutional Neural Network. IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 39(1): 115-127, 2017. (SCI, 中科院一分区, 影响因子: 9.455)

5.Xiaodan Liang, Ke Gong, Xiaohui Shen, Liang Lin. Look into Person: Joint Human Parsing and Pose Estimation Network and a New Benchmark. IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2018. (SCI,中科院JCR一区, 影响因子: 9.455)

6.Xiaodan Liang, Liang Lin, Qingxing Cao, Rui Huang, and Yongtian Wang. Recognizing Focal Liver Lesions in CEUS with Dynamically Trained Latent Structured Models. IEEE Transactions on Medical Imaging (T-MI), 35(3): 713-727, 2016. (SCI,中科院JCR一区, 影响因子: 6.131)

7.Xiaodan Liang, Liang Lin, Wei Yang, Ping Luo, Junshi Huang, and Shuicheng Yan. Clothes Co-Parsing via Joint Image Segmentation and Labeling with Application to Clothing Retrieval. IEEE Transactions on Multimedia (T-MM), 18(6): 1175-1186, 2016. (SCI,中科院JCR二区, 影响因子: 3.977)

8.Xiaodan Liang, Zhiting Hu, Hao Zhang, Liang Lin, Eric P. Xing. Symbolic Graph Reasoning Meets Convolutions. Conference on Neural Information Processing Systems (NIPS), 2018. (机器学习领域旗舰会议)

9.Chenhan Jiang, Hang Xu, Xiaodan Liang*, Liang Lin. Hybrid Knowledge Routed Modules for Large-scale Object Detection. Conference on Neural Information Processing Systems (NIPS), 2018. (机器学习领域旗舰会议, 通讯作者)

10.Xiaodan Liang, Lisa Lee, Eric P. Xing. Deep Variation-structured Reinforcement Learning for Visual Relationship and Attribute Detection. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. (计算机视觉领域旗舰会议)

11.Haoye Dong, Xiaodan Liang, Ke Gong, Hanjiang Lai, Jia Zhu, Jian Yin. Soft-Gated Warping-GAN for Pose-Guided Person Image Synthesis. NIPS 2018 

12.Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Xiaodan Liang, Lianhui Qin, Haoye Dong, Eric Xing. Deep Generative Models with Learnable Knowledge Constraints. NIPS 2018

13.Generative Semantic Manipulation with Mask-Contrasting GAN

14.Xiaodan Liang, Hao Zhang, Eric P. Xing. ECCV 2018.

15.CIRL: Controllable Imitative Reinforcement Learning for Vision-based Self-driving

16.Xiaodan Liang, Tairui Wang, Luona Yang, Eric P. Xing. ECCV 2018.

17.Instance-level Human Parsing via Part Grouping Network (Oral)

18.Ke Gong, Xiaodan Liang, Yicheng Li, Yimin Chen, Liang Lin. ECCV 2018.

19.Adversarial Geometry-Aware Human Motion Prediction (Oral)

20.Liangyan Gui, Xiaodan Liang, Yuxiong Wang, Jose M.F. Moura. ECCV 2018.

21.Real-to-Virtual Domain Unification for End-to-End Autonomous Driving

22.Luona Yang, Xiaodan Liang, Eric P. Xing. ECCV 2018.

23.Toward Characteristic-Preserving Image-based Virtual Try-On Network

24.Bochao Wang, Huabin Zheng, Xiaodan Liang,Yimin Chen, Liang Lin. ECCV 2018.

25.RCAA: Relational Context-Aware Agents for Person Search

26.Xiaojun Chang, Po-Yao Huang, Xiaodan Liang, Yi Yang, Alexander Hauptmann. ECCV 2018.

27.A Modulation Module for Multi-task Learning with Applications in Image Retrieval

28.Xiangyun Zhao, Haoxiang Li, Xiaohui Shen, Xiaodan Liang, Ying Wu. ECCV 2018.

29.Adaptive Temporal Encoding Network for Video Instance-level Human Parsing

30.Qixian Zhou,Xiaodan Liang, Ke Gong, Liang Lin. ACM MM 2018.

31.Teaching Robots to Predict Human Motion. Liangyan Gui, Kevin Zhang, Yuxiong Wang, Xiaodan Liang, Jose M.F. Moura, Manuela Veloso. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018. (Oral)

32.Unsupervised Domain Adaptation for Automatic Estimation of Cardiothoracic Ratio

33.Nanqing Dong, Michael C. Kampffmeyer, Xiaodan Liang, Zeya Wang, Wei Dai, Eric P. Xing. MICCAI 2018

34.StepDeep: A Novel Spatial-temporal Mobility Event Prediction Framework based on Deep Neural Network. Bilong Shen, Xiaodan Liang, Yufeng Ouyang, Miaofeng Liu, Weimin Zheng, Kathleen M. Carley. KDD 2018

35.Dynamic-structured Semantic Propagation Network

36.Xiaodan Liang, Hongfei Zhou, Eric P. Xing. CVPR 2018

37.Visual Question Reasoning on General Dependency Tree

38.Qingxing Cao, Xiaodan Liang, Bailing Li, Guanbin Li, Liang Lin. CVPR 2018. (Spotlight)

39.Reinforcement Cutting-Agent Learning for Video Object Segmentation

40.Junwei Han, Le Yang, Dingwen Zhang, Xiaojun Chang, Xiaodan Liang. CVPR 2018. (Spotlight)