个人信息
Personal Information
联系方式
Contact Information
个人简介
Personal Profile
本人为同济大学副教授，现受聘于同济大学软件学院。2002年获得同济大学计算机应用专业学士学位，2005年获得同济大学计算机系统结构专业硕士学位，2017年获得英国Bolton大学博士学位。主要研究方向为：影像解译、时空图数据分析等，在多源异构数据融合、遥感影像解译、图表示学习、序列数据分析处理等方面具有丰富经验。先后主持和参与了国家科技部、上海市科委、上海市经信委等多项项目。近5年在国际会议和核心刊物上发表学术论文30余篇。获得发明专利3项，长期指导各类学生创新项目和竞赛获国际级奖项7项，国家级奖项18项。专利《一种图数据存取方法及系统》已在企业获得应用并应邀在QCon进行专题报告。
• 科技部，No. 2018YFB05050091，国家科技部2018重点研发计划地球观测与导航专项，“全球综合观测成果管理及共享服务系统关键技术研究”项目，“基于深度学习的典型要素提取识别与融合技术研究”课题。
• 上海市科学技术委员会，No.20511102700，基于深度语义图谱和流程自动化的行政智能审批系统研发及示范应用
• 科技部，No. 2016YFB1000805，国家科技部2016重点研发计划云计算和大数据专项，“基于大数据的软件智能开发方法和环境”项目，
• 上海市科学技术委员会，No.17511107300，基于海量异构数据分析的大型航空枢纽分类安检及资源优化关键技术研究的示范应用
• 上海市科学技术委员会，No.17511110200, 尿细胞自动染色智能分析机器人及其在糖尿病临床诊断中的应用示范
• 上海市科学技术委员会，No.12510706200，基于云平台的物联网数据分析和处理技术研究
• 中央高校基本科研业务费项目，2100219063，互联网点击流欺诈分析关键方法与应用
• 国际合作，利用物联网技术解决全球水资源危机问题研究
• 企业合作，基于iOS系统的的车联网数据采集咨询服务
• 企业合作，基于大数据技术的车联网数据分析咨询服务
• 企业合作，电动汽车数据采集和管理
• 企业合作，同济大学SAP物联网及工业4.0咨询项目
1. Zhu, H., Tan, R., Han, L., Fan, H., Wang, Z., Du, B., ... & Liu, Q. (2022). DSSM: A Deep Neural Network with Spectrum Separable Module for Multi-Spectral Remote Sensing Image Segmentation. Remote Sensing, 14(4), 818.
2. Liu, Q., Han, L., Tan, R., Fan, H., Li, W., Zhu, H., ... & Liu, S. (2021). Hybrid Attention Based Residual Network for Pansharpening. Remote Sensing, 13(10), 1962.
3. Qian, Y., Liu, Q., Zhu, H., Fan, H., Du, B., & Liu, S. (2019, August). Mask R-CNN for object detection in multitemporal SAR images. In 2019 10th International Workshop on the Analysis of Multitemporal Remote Sensing Images (MultiTemp) (pp. 1-4). IEEE.
4. Luo, M., Du, B., Klemmer, K., Zhu, H., & Wen, H. (2021). Deployment Optimization for Shared e-Mobility Systems with Multi-agent Deep Neural Search. IEEE Transactions on Intelligent Transportation Systems.
5. Zhu, H., Wang, X., Jiang, Y., Fan, H., Du, B., & Liu, Q. (2021). FTRLIM: Distributed instance matching framework for large-scale knowledge graph fusion. Entropy, 23(5), 602.
6. Wang, X., Zhu, H., Jiang, Y., Li, Y., Tang, C., Chen, X., ... & Liu, Q. (2022). PRODeepSyn: predicting anticancer synergistic drug combinations by embedding cell lines with protein–protein interaction network. Briefings in Bioinformatics.
7. Wang, X., Jiang, Y., Fan, H., Zhu, H., & Liu, Q. (2020, December). FTRLIM results for OAEI 2020. In OM@ ISWC (pp. 187-193).
8. Zhou, Q., Zhu, H., Luo, Y., & Liu, Q. (2020, January). A Spatio-temporal Network for Demand Prediction of Electric Vehicle Sharing Systems. In Proceedings of the 2020 2nd Asia Pacific Information Technology Conference (pp. 157-164).
9. Zhu, H., Jiang, Y., Wang, X., Fan, H., Liu, Q., & Du, B. (2020). Modeling Relation Path for Knowledge Graph via Dynamic Projection. In SEKE (pp. 65-70).
10. Luo, M., Zhang, W., Song, T., Li, K., Zhu, H., Du, B., & Wen, H. (2021, January). Rebalancing expanding EV sharing systems with deep reinforcement learning. In Proceedings of the Twenty-Ninth International Conference on International Joint Conferences on Artificial Intelligence (pp. 1338-1344).
11. Zhu, H., Luo, Y., Liu, Q., Fan, H., Song, T., Yu, C. W., & Du, B. (2019). Multistep flow prediction on car-sharing systems: A multi-graph convolutional neural network with attention mechanism. International Journal of Software Engineering and Knowledge Engineering, 29(11n12), 1727-1740.
12. Luo, M., Du, B., Klemmer, K., Zhu, H., Ferhatosmanoglu, H., & Wen, H. (2020). D3p: Data-driven demand prediction for fast expanding electric vehicle sharing systems. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 4(1), 1-21.
13. Liu, Q., Liu, Z., Zhu, H., Fan, H., Du, B., & Qian, Y. (2019, May). Generating commit messages from diffs using pointer-generator network. In 2019 IEEE/ACM 16th International Conference on Mining Software Repositories (MSR) (pp. 299-309). IEEE.
14. Wang, X., Jiang, Y., Luo, Y., Fan, H., Jiang, H., Zhu, H., & Liu, Q. (2019, October). FTRLIM Results for OAEI 2019. In OM@ ISWC (pp. 146-152).
15. Liu, Q., Li, X., Zhu, H., & Fan, H. (2017, December). Acquisition of open source software project maturity based on time series machine learning. In 2017 10th International Symposium on Computational Intelligence and Design (ISCID) (Vol. 1, pp. 296-299). IEEE.
16. Liu, Q., Xiao, J., & Zhu, H. (2019). Feature selection for software effort estimation with localized neighborhood mutual information. Cluster computing, 22(3), 6953-6961.
17. Liu, Q., Guo, X., Fan, H., & Zhu, H. (2017, December). A novel data visualization approach and scheme for supporting heterogeneous data. In 2017 IEEE 2nd Information Technology, Networking, Electronic and Automation Control Conference (ITNEC) (pp. 1259-1263). IEEE.
18. Fan, H., Gao, J., Zhu, H., Liu, Q., Shi, Y., & Sun, C. (2017, September). Balancing conflict prevention and concurrent work in real-time collaborative programming. In Proceedings of the 12th Chinese Conference on Computer Supported Cooperative Work and Social Computing (pp. 217-220).
19. Liu, Q., Chen, R., Zhu, H., & Fan, H. (2017, September). Research and comparison of data dimensionality reduction algorithms. In Proceedings of the International Conference on Bioinformatics and Computational Intelligence (pp. 49-54).
20. Fan, H., Zhu, H., Liu, Q., Shi, Y., & Sun, C. (2017, April). Shared-locking for semantic conflict prevention in real-time collaborative programming. In 2017 IEEE 21st International Conference on Computer Supported Cooperative Work in Design (CSCWD) (pp. 174-179). IEEE.
申请人主要专利：
1. 基于非正交坐标系下软件成本评估方法，China, 同济大学, 201210378855.9, 发明专利
2. 一种图数据存取方法及系统，China, 同济大学, 201510028305.8, 发明专利
文件上传中...
同济大学