姜善成

教师简介

姜善成，博士，副教授，硕士生导师，中山大学“百人计划”引进人才。分别于2012年及2014年在东北大学获得学士及硕士学位。2018年于香港城市大学获得博士学位。并于2017年11月至2019年3月在香港理工大学容启亮讲座教授团队担任副研究员。

研究兴趣

目前主要研究方向为智能优化算法、鲁棒优化、深度学习、计算机视觉、对抗训练、智慧医疗等。

科研项目

国家自然科学基金-青年项目：医疗大数据环境下基于人工智能的皮肤病自动诊断系统研究,20万元，2019-2021，主持，结题。
国家重点研发计划-子课题：盐湖化工产业集聚区域网络协同制造集成技术研究与应用示范， 42万元，2020-11 至 2023-10，主持，在研。
广东省自然基金项目-面上项目：面向多元影像信息的皮肤病自动诊断系统研究, 10万元，2019-10 至 2022-09，主持，在研。
高校基本科研业务费中山大学青年教师培育项目：基于小样本学习的皮肤病自动诊断系统研究，15万元，2020-01 至 2021-08，主持，结题。
中山大学“百人计划”科研启动经费，2019-至今；

代表性成果

[1] 吴禄彬, 章宇, 连宗凯, 姜善成*. 共享汽车系统空车调度的鲁棒优化模型, 控制与决策, 2021, online published
[2]周晓婷,吴禄彬,章宇,姜善成*.基于不确定需求的无人驾驶出租车优化调度，计算机集成制造系统，2022，online published.
[3] Shancheng Jiang, Huichuan Li, and Zhi Jin*. A Visually Interpretable Deep Learning Framework for Histopathological Image-Based Skin Cancer Diagnosis, IEEE Journal of Biomedical and Health Informatics, 2021, 25(5): 1483-1494
[4] Kun Xiang#, Linlin Peng#, Haiqiong Yang, Mingxin Li, Zhongfa Cao, Shancheng Jiang*, and Gang Qu. A Novel Weight Pruning Strategy for Light Weight Neural Networks with Application to the Diagnosis of Skin Disease， Applied Soft Computing, 2021, 111(107707)
[5] S. Jiang*, K. L. Yung, W. H. W. Ip, Z. Lian and M. Gao, "Automated Detection of Multi-Type Landforms on Mars Using A Light-weight Deep Learning-Based Detector," in IEEE Transactions on Aerospace and Electronic Systems, doi: 10.1109/TAES.2022.3169454.
[6] Fan Wu#, Haiqiong Yang#, Linlin Peng, Zongkai Lian, Mingxin Li, Gang Qu, Shancheng Jiang*, and Yu Han*，AGNet: Automatic Generation Network for Skin Imaging Reports, Computers in Biology and Medicine, 2021, 141
[7] Shancheng Jiang*, Fan Wu, K. L. Yung, Yingqiao Yang, W. H. Ip, Ming Gao, and James Abbott Foster. A Robust End-To-End Deep Learning Framework for Detecting Martian Landforms with Arbitrary Orientations, Knowledge-based Systems, 2021, 234(107562)
[8] Leping Deng#, Weihe Zhong#, Lu Zhao#, Xuedong He, Zongkai Lian, Shancheng Jiang*, Calvin Yu-Chian Chen*. Artificial Intelligence-Based Application to Explore Inhibitors of Neurodegenerative Diseases, Frontiers in Neurorobotics, 2020, 14
 [9] Shancheng Jiang, K. S. Chin*, Gang Qu, and K. L. Tsui. An Integrated Machine Learning Framework for Hospital Readmission Prediction. Knowledge-Based Systems, 2018, 146: 73-90.
[10] Shancheng Jiang, K. S. Chin*, and K. L. Tsui. A universal deep learning approach for modeling the flow of patients under different severities. Computer methods and programs in biomedicine, 2018, 154: 191-203.
[11] Shancheng Jiang, K. S. Chin*, Long Wang, Gang Qu, and K. L. Tsui. Modified genetic algorithm-based feature selection combined with pre-trained deep neural network for demand forecasting in outpatient department. Expert Systems with Applications, 2017, 82: 216-230.
[12] Zongkai Lian, Haiqiong Yang, Fan Wu, Mingxin Li, Shancheng Jiang. C-ALGL NET: Pathological Images Generate Diagnostic Results. 2020 IEEE 17th International Symposium on Biomedical Imaging Workshops (ISBI Workshops), Iowa City, IA, USA (conference paper)
[13] Shancheng Jiang and K. S. Chin. Demand Forecasting in Outpatient Department with a Universal Deep Learning Framework, INFORMS 2016 International Meeting, Kona, U.S.A, (2016). (invited presentation)
[14] Shancheng Jiang, Jiafu Tang, and Guangwei Chen. Modeling the Scheduling Problem of Break-up and Make-up Process for Cargo Trains in Chinese Railway Marshalling Yard. Proceedings of 2013 International Conference on Industrial Engineering and Management Science (conference paper)
[15] 姜善成; 江汉康; 刘金朋; 黄俊嘉; 佘锦文; 黄孜颖，皮肤病自动诊断软件， 2021SR1196250, 原始取得, 全部权利, 2021-5-10 (软件著作权)

社会服务 

IEEE Transactions on Neural Networks and Learning Systems, IEEE Journal of Biomedical and Health Informatics, expert systems with applications, Industrial Engineering & Management Systems 等期刊审稿人。

联系我

电子邮箱： jiangshch3@mail.sysu.edu.cn; pfc24@126.com 。欢迎对我研究方向感兴趣的同学加入我的课题组相互交流学习。针对想跟我读研同学的要求：（1）为人诚实、正直。（2）英语过六级