Ph.D. Associate Professor
Room 508, No.163, Xianlin Avenue
Nanjing, Jiangsu, China, 210023
syh AT nju.edu.cn
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 State 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.
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.
A Novel Deep Multi-Modal Feature Fusion Method for Celebrity Video Identification
Jianrong Chen, Li Yang, Yuanyuan Xu, Jing Huo, Yinghuan Shi, Yang Gao
ACM Conf. on Multimedia (ACMMM), iQIYI Celebrity Video Identification Challenge, 2019
A Novel Unsupervised Camera-aware Domain Adaptation Framework for Person Re-identification
Lei Qi, Lei Wang, Jing Huo, Luping Zhou, Yinghuan Shi, Yang Gao
IEEE International Conference on Computer Vision (ICCV), 2019
Cross-Modal Attention-Guided Convolutional Network for Multi-Modal Cardiac Segmentation
Ziqi Zhou, Xinna Guo, Wanqi Yang, Yinghuan Shi, Luping Zhou, Lei Wang, Ming Yang
Machine Learning in Medical Imaging @ MICCAI (MLMI), 2019
Crossbar-Net: A Novel Convolutional Neural Network for Kidney Tumor Segmentation in CT Images
Qian Yu, Yinghuan Shi, Jinquan Sun, Yang Gao, Jianbing Zhu, Yakang Dai
IEEE Trans. on Image Processing (TIP), 2019
Leveraging Coupled Interaction for Multi-Modal Alzheimer’s Disease Diagnosis
Yinghuan Shi, Heung-Il Suk, Yang Gao, Seong-Whan Lee, Dinggang Shen
IEEE Trans. on Neural Networks and Learning Systems (TNNLS), 2019
Young Elite Scientists Sponsorship Program by CAST (2016)
Prize of Jiangsu Science and Technology Award (2018) (2/7)
Computer Federation Excellent Young Scientist Award (2017)
BigData Best Application Paper Award (2017)
The Medical Productive Award (2015)
Nanjing Rising Star Award (2017)