Ph.D. Associate Professor

National Key Laboratory for Novel Software Technology

National Institute of Healthcare Data Science

Department of Computer Science and Technology

Reasoning and Learning Research Group

Nanjing University

Room 508, No.163, Xianlin Avenue

Nanjing, Jiangsu, China, 210023

syh AT nju.edu.cn

About Me

Hi, I am Yinghuan. I received my B.Sc. and Ph.D. degree both in Computer Science at Nanjing University in 2007 and 2013, respectively. Currently, I am an Associate Professor in the Department of Computer Science and Technology at Nanjing University, and a member of the National Key Laboratory for Novel Software Technology. Also, I am a member of the Reasoning and Learning Research Group, led by Prof. Yang Gao.

In 2011-2012, I visited the IDEA Lab of the University of North Carolina at Chapel Hill (UNC) under the support from the China Scholarship Council (CSC), and worked with Prof. Dinggang Shen. In 2016, I returned to the IDEA Lab for a three months visiting. Also, I spent two months in 2014 as a Visiting Scholar at the Data Science Lab of the University of Technology, Sydney (UTS), working with Prof. Longbing Cao.

Chinese Version (中文简介)

News!

Research Interest

Currently, I am broadly interested in medical image analysis, clinical data mining, and also including the other related topics in image processing, computer vision, and machine learning.

In particular, the main goal of our research is to develop the machine learning-based algorithms for the data analysis problems in medical imaging and clinical data. The difficulties in medical data, e.g., complicated connection, unpredictable noise, limited amount and insufficient labeling, pose the considerable challenges for the data analysis. We wish to develop the effective and efficient methods to tackle these challenges. Also, these methods are used to guide the development of the real systems in the clinical scenario.

Preprints

• Generalizable Semantic Segmentation via Model-agnostic Learning and Target-specific Normalization

  Jiang Zhang, Lei Qi, Yinghuan Shi, Yang Gao

  [Arxiv][Code]

• Unsupervised Few-shot Learning via Distribution Shift-based Augmentation

  Tiexin Qin, Wenbin Li, Yinghuan Shi, Yang Gao

  [Arxiv][Code]

• Crossover-Net: Leveraging the Vertical-horizontal Crossover Relation for Robust Segmentation

  Qian Yu, Yinghuan Shi, Yefeng Zheng, Yang Gao, Jianbing Zhu, Yakang Dai

  [Arxiv][Code]

Recent Publication

• Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation and Diagnosis for COVID-19

  Feng Shi, Jun Wang, Jun Shi, Ziyan Wu, Qian Wang, Zhenyu Tang, Kelei He, Yinghuan Shi, Dinggang Shen

  IEEE Reviews in Biomedical Engineering (RBME), 2020 [Arxiv]

• Learning-based Computer-aided Prescription Model for Parkinson's Disease: A Data-driven Perspective

  Yinghuan Shi, Wanqi Yang, Kim-Han Thung, Hao Wang, Yang Gao, Yang Pan, Li Zhang, Dinggang Shen

  IEEE Journal of Biomedical and Health Informatics (JBHI), 2020

• Consistent MetaReg: Alleviating Intra-task Discrepancy for Better Meta-knowledge

  Pinzhuo Tian, Lei Qi, Shaokang Dong, Yinghuan Shi, Yang Gao

  Int. Joint Conf. on Artificial Intelligence (IJCAI), 2020

• Asymmetric Distribution Measure for Few-shot Learning

  Wenbin Li, Lei Wang, Jing Huo, Yinghuan Shi, Yang Gao, Jiebo Luo

  Int. Joint Conf. on Artificial Intelligence (IJCAI), 2020

• [More Papers]

Courses

Spring 2020: Discrete Mathematics

Awards

• WuWenJun AI Excellent Young Scientist Award (2019)

  中国人工智能学会，吴文俊人工智能优秀青年奖

• Young Elite Scientists Sponsorship Program by CAST (2016)

  中国科协“青年人才托举工程”

• Prize of Jiangsu Science and Technology Award (2018) (2/7)

  江苏省科学技术二等奖（第二完成人）

• Computer Federation Excellent Young Scientist Award (2017)

  江苏省计算机学会青年科技奖

• BigData Best Application Paper Award (2017)

  中国计算机学会大数据学术会议最佳应用论文奖

• The Medical Productive Award (2015)

  中国人民解放军军队医疗成果奖（第三完成人）

• Nanjing Rising Star Award (2017)

  ACM南京分会新星奖