Shaohua Li's Academic Site
CONTACT:
Email: shaohua at gmail.com
EDUCATION & RESEARCH:
6.2017 - Now: Scientist in Institute of High Performance Computing, A*STAR, Singapore.
2.2016 - 5.2017: Postdoctoral Research Fellow at NExT center, National University of Singapore (NUS).
8.2009 - 1.2016: PhD student at School of Computer Engineering, Nanyang Technological University (NTU).
Supervisor: Chunyan Miao. Cosupervisor: Gao Cong.
9.2012 - 12.2012: Research Intern at Data Mining and Business Analysis Technology Group, NEC Japan.
Mentor: Ryohei Fujimaki.
2002 - 2005: M.Sc. in CS, Institute of Software, Chinese Academy of Sciences (CAS).
Supervisor: Jian Zhang.
1997 - 2002: B.S. in Math (Special Class for the Gifted Youth, SCGY), University of Science and Technology of China (USTC).
RESEARCH INTERESTS:
Deep Learning, Computer Vision and Natural Language Processing.
PUBLICATIONS:
"Localizing Anatomical Landmarks in Ocular Images Using Zoom-In Attentive Networks". Xiaofeng Lei, Shaohua Li, Xinxing Xu, Huazhu Fu, Yong Liu, Yih-Chung Tham, Yangqin Feng, Mingrui Tan, Yanyu Xu, Jocelyn Hui Lin Goh, Rick Siow Mong Goh, Ching-Yu Cheng. International Workshop on Ophthalmic Medical Image Analysis (OMIA) 2022 (Best paper award), MICCAI 2022.
"CRAFT: Cross-Attentional Flow Transformers for Robust Optical Flow". Xiuchao Sui*, Shaohua Li*, Xue Geng, Yan Wu, Xinxing Xu, Yong Liu, Rick Goh, Hongyuan Zhu. CVPR 2022. (*: Equal contributions) [PDF] [Code] [5Min Video]
"Text-Graph Enhanced Knowledge Graph Representation Learning". Linmei Hu, Mengmei Zhang, Shaohua Li, Jinghan Shi, Chuan Shi, Cheng Yang, Zhiyuan Liu. Frontiers in Artificial Intelligence, Volume 4, 2021. [PDF]
"Few-Shot Domain Adaptation with Polymorphic Transformers". Shaohua Li, Xiuchao Sui, Jie Fu, Huazhu Fu, Xiangde Luo, Yangqin Feng, Xinxing Xu, Yong Liu, Daniel Ting, Rick Siow Mong Goh. Accepted to 24nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2021). [PDF] [Code]
"Medical Image Segmentation using Squeeze-and-Expansion Transformers". Shaohua Li, Xiuchao Sui, Xiangde Luo, Xinxing Xu, Yong Liu, Rick Siow Mong Goh. IJCAI 2021 (acceptance rate: 13.9%). [PDF] [Code] [15Min Video] [2Min Video]
"Retinal photograph-based deep learning algorithms for myopia and a blockchain platform to facilitate artificial intelligence medical research: a retrospective multicohort study". Tien-En Tan, Ayesha Anees, Cheng Chen, Shaohua Li, Xinxing Xu, Zengxiang Li, Zhe Xiao, Yechao Yang, Xiaofeng Lei, Marcus Ang, Audrey Chia, Shu Yen Lee, Edmund Yick Mun Wong, Ian Yew San Yeo, Yee Ling Wong, Quan V. Hoang, Ya Xing Wang, Mukharram M. Bikbov, Vinay Nangia, Jost B. Jonas, Yen-Po Chen, Wei-Chi Wu, Kyoko Ohno-Matsui, Tyler Hyungtaek Rim, Yih-Chung Tham, Rick Siow Mong Goh, Haotian Lin, Hanruo Liu MD, Ningli Wang MD, Weihong Yu, Donald Tiang Hwee Tan, Leopold Schmetterer, Ching-Yu Cheng, You-Xin Chen, Chee Wai Wong, Gemmy Chui Ming Cheung, Seang-Mei Saw, Tien Yin Wong, Yong Liu, Daniel Shu Wei Ting. Lancet Digital Health, Volume 3, Issue 5, E317-E329, 2021. [Link]
"Referral for Pathology-Related Visual Loss using Retinal Photograph-Based Deep Learning". Yih-Chung Tham, Ayesha Anees, Liang Zhang, Jocelyn Goh, Tyler Hyungtaek Rim, Simon Nusinovici, Haslina Hamzah, Miao-Li Chee, Gabriel Tjio, Shaohua Li, Xinxing Xu, Rick Goh, Fangyao Tang, Carol Yim-Lui Cheung, Ya Xing Wang, Vinay Nangia, Jost B. Jonas, Bamini Gopinath, Paul Mitchell, Rahat Husain, Ecosse Lamoureux, Charumathi Sabanayagam, Jie Jin Wang, Tin Aung, Yong Liu, Tien Yin Wong, Ching-Yu Cheng. Lancet Digital Health, Volume 3, Issue 1, E29-E40, Jan 01, 2021. (Editor's Pick) [PDF]
"Cascaded Mixed-Precision Networks". Xue Geng, Jie Lin, Shaohua Li. In the Proceedings of the 27th IEEE International Conference on Image Processing (ICIP 2020).
"Graph Neural Entity Disambiguation". Linmei Hu, Jiayu Ding, Chuan Shi, Chao Shao, Shaohua Li. Knowledge-Based Systems, 2020. [PDF]
"RoboCoDraw: Robotic Avatar Drawing with GAN-based Style Transfer and Time-efficient Path Optimization". Tianying Wang, Wei Qi Toh, Hao Zhang, Xiuchao Sui, Shaohua Li, Yong Liu, Wei Jing. In the Proceedings of AAAI'2020. [PDF]
"Learning to Reconstruct Crack Profiles for Eddy Current Nondestructive Testing". Shaohua Li, Ayesha Anees, Yu Zhong, Zaifeng Yang, Yong Liu, Rick Siow Mong Goh, En-xiao Liu. Accepted by Machine Learning and the Physical Sciences Workshop (ML4PS) at NeurIPS 2019. [PDF] [Poster] [Code]
"Multi-discriminator Generative Adversarial Networks for Improved Thin Retinal Vessel Segmentation". Gabriel Tjio, Shaohua Li, Xinxing Xu, Daniel Shu Wei Ting, Yong Liu, Rick Siow Mong Goh. In Ophthalmic Medical Image Analysis. OMIA 2019. Lecture Notes in Computer Science, vol 11855. Springer. [PDF]
"Multi-Instance Multi-Scale CNN for Medical Image Classification". Shaohua Li, Yong Liu, Xiuchao Sui, Cheng Chen, Gabriel Tjio, Daniel Shu Wei Ting and Rick Siow Mong Goh. In the Proceedings of the 22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2019). [PDF] [Poster] [Code]
"Method and system for classification and visualisation of 3D images". Shaohua Li, et al., Patent No. WO 2020162834 (published on 13 Aug 2020). [URL]
"Laplacian-Steered Neural Style Transfer". Shaohua Li, Xinxing Xu, Liqiang Nie and Tat-Seng Chua. In the Proceedings of ACM Multimedia Conference (MM) 2017. [PDF] [Code] [Slides]
"Dirichlet-vMF Mixture Model". arXiv:1702.07495 [cs.CL], 2017.
"Document Visualization using Topic Clouds". arXiv:1702.01520 [cs.IR], 2017.
"Detecting Functional Modules of the Brain using Eigenvalue Decomposition of Laplacian", Xiuchao Sui, Shaohua Li, and Jagath C Rajapakse. In the Proceedings of the International Symposium on Biomedical Imaging (ISBI) 2017. [PDF]
"Generative Topic Embedding: a Continuous Representation of Documents", Shaohua Li, Tat-Seng Chua, Jun Zhu and Chunyan Miao. In the Proceedings of the Annual Meeting of the Association for Computational Linguistics (ACL) 2016 (oral), pp. 666-675. [PDF] (extended with proofs) [Code] [Slides]
"PSDVec: a Toolbox for Incremental and Scalable Word Embedding", Shaohua Li, Jun Zhu and Chunyan Miao. Neurocomputing, volume 237, 2017, Pages 405-409. [PDF] [Code&Data]
"Locality Regularized Sparse Subspace Clustering with Application to Cortex Parcellation on Resting fMRI", Xiuchao Sui, Shaohua Li and Jagath C Rajapakse. In the Proceedings of the International Symposium on Biomedical Imaging (ISBI) 2016. [PDF]
"Mobile App Tagging", Ning Chen, Steven C.H. Hoi, Shaohua Li and Xiaokui Xiao. In the Proceedings of the ACM Conference of Web Search and Data Mining (WSDM) 2016. [PDF]
"A Generative Word Embedding Model and its Low Rank Positive Semidefinite Solution", Shaohua Li, Jun Zhu, Chunyan Miao. In the Proceedings of the Conference on Empirical Methods on Natural Language Processing (EMNLP) 2015, pp. 1599–1609. [PDF] [Code&Data] [Poster]
"On the Equivalence of Factorized Information Criterion Regularization and the Chinese Restaurant Process Prior", Shaohua Li. arXiv:1506.09068 [stat.ML], 2015.
"Factorized Asymptotic Bayesian Inference for Factorial Hidden Markov Models", Shaohua Li, Ryohei Fujimaki, Chunyan Miao. arXiv:1506.07959 [stat.ML], 2015.
"Sparse Canonical Correlation Analysis Reveals Correlated Patterns of Gray Matter Loss and White Matter Impairment in Alzheimer's Disease", Xiuchao Sui, Shaohua Li, Chunshui Yu, Tianzi Jiang. In the Proceedings of the International Symposium on Biomedical Imaging (ISBI) 2015. [PDF]
"SimApp: A Framework for Detecting Similar Mobile Applications by Online Kernel Learning", Ning Chen, Steven C.H. Hoi, Shaohua Li and Xiaokui Xiao. In the Proceedings of the ACM Conference of Web Search and Data Mining (WSDM) 2015. [PDF]
"Factorial hidden markov models estimation device, method, and program", Ryohei Fujimaki, Shaohua Li. US Patent US20140343903 A1, 2014. [Details]
"Author Name Disambiguation using a New Categorical Distribution Similarity", Shaohua Li, Gao Cong, Chunyan Miao. In the Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) 2012, Bristol, UK. [PDF] [Slides] [Code&Data]
"A k-NN Method for Large Scale Hierarchical Text Classification at LSHTC3", Xiaogang Han, Shaohua Li, Zhiqi Shen. ECML-PKDD 2012 PASCAL Workshop on Large-Scale Hierarchical Classification, Bristol, UK. [PDF]
GRANTS
Megatran: Fine-Grained Medical Image Analysis using Transformers. 2020 A*STAR Career Development Award. PI, SG$300,000.
MARIO : Multimodal AI-Driven Decision Making for Ophthalmology. Co-I, SG$10M.
SLIDES:
统计建模基础 Statistical Modeling - Basics (in Chinese) 2017
统计建模 - 隐变量模型 Statistical Modeling - Latent Variable Models (in Chinese) 2017
词嵌入原理及应用 Principles and Applications of Word Embedding (in Chinese) 讲座录像 2016
Word Embedding Methods, Generative Word Embedding and Extension 2015
共轭梯度法简介 Introduction to Conjugate Gradient Methods (in Chinese) 2014
SOFTWARE CODE:
Generative Topic Embedding: TopicVec (in Python)
Generative Word Embedding: PSDVec (in Python)
Misc Writings: