研究方向
| 研究方向： 赵勤，副教授，上海市徐汇区政协委员，智能社会与科学计算科研团队负责人，IEEE Senior Member，中国计算机学会杰出会员，任上海市科委智能教育大数据工程技术研究中心副主任，兼任中国计算机学会科学教育创新论坛秘书长。2016年毕业于同济大学嵌入式系统与服务计算教育部重点实验室，获工学博士学位，导师为中国工程院院士蒋昌俊教授。主持国家重点研发计划子课题、国家自然科学基金、上海张江重大项目课题、国家教育部重点实验室课题，以及上海市科委、教委、经信委等十余项重要科研项目，并作为主要研究人员参与国家973计划、863计划、国家基金委重大研究计划及上海市市级科技重大研究专项等多项研究工作，在IEEE TNNLS、TSMC、TCSS、J-STARS、ESWA、NEUCOM、ATMOSRES、IJCAI等国际高水平学术期刊和会议上发表学术论文五十余篇，申请发明专利十余项，获上海市科技进步奖二等奖一项，上海市计算机学会科技进步奖一等奖一项。 访问课题组网站 https://issc.group 可获取更多信息。
主要研究方向：智能教育、社交网络分析、金融风险防控、大气环境预测等。 主要项目： [1] 国家重点研发计划专项“面向微小型数据中心的系统软件”（项目编号2022YFB4501700）子课题“数据原位计算与热敏制导存储技术”，主持，在研。 [2] 国家自然科学基金青年科学基金项目“基于情感的社交网络信息推荐关键技术研究”（项目编号61702333），主持，已结题。 [3] 上海张江国家自主创新示范区专项发展资金重大项目委托课题“细胞培养AI质量监控与再生医学新模型构建研究”，主持，在研。 [4] 上海市经信委政策咨询项目“人工智能时代的职业教育发展趋势和政策咨询研究”，主持，在研。 [5] 上海市教委中小学在线教育研究基地项目“人工智能驱动的在线远程智能教育模式与建设路径研究”，主持，已结题。 [6] 国家教育部嵌入式系统与服务计算重点实验室开放课题“大数据环境下的社交网络信息表达方法研究”（项目编号ESSCKF2019-03），主持，已结题。 [7] 国家教育部嵌入式系统与服务计算重点实验室开放课题“基于情感的混合领域社交网络信息推荐方法研究”（项目编号ESSCKF 2016-01），主持，已结题。 [8] 上海高校青年教师培养资助计划项目“基于用户情感的重叠社区检测研究”，主持，已结题。 [9] 上海师范大学教学改革项目“新工科视野下的信息工程数学：《线性代数》数字课程建设”，主持，已结题。 [10] 国家重点基础研究发展计划（973计划）项目“信息服务的模型与机理研究”（项目编号2010CB328100），参与，已结题。 [11] 国家自然科学基金重大研究计划集成项目“可信网络交易软件系统试验环境与示范应用”（项目编号91218301），参与。 [12] 国家高技术研究发展计划（863计划）课题“软件安全性病态模型及其检测、防治技术研究”（2009AA01Z401），参与，已结题。 [13] 上海市基础研究领域重大科技项目“大规模信息流处理计算式的基础研究” (10DJ1400300)，参与，已结题。 代表性论文（标*为通讯作者）： 社交网络分析： [1] Q. Zhao, P. Wu, G. Liu, D. An, J. Lian*, and M. Zhou, "Sociological-Theories-Based Multi-Topic Self-Supervised Recommendation," IEEE Transactions on Neural Networks and Learning Systems, vol. 36, no. 6, pp. 11228-11242, 2025. (SCI, 中科院一区, TOP期刊) [2] Q. Zhao, C. Wang, P. Wang, M. Zhou, and C. Jiang*, "A Novel Method on Information Recommendation via Hybrid Similarity," IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 48, no. 3, pp. 448-459, 2018. (SCI, 中科院一区, TOP期刊) [3] P. Wu, H. Qi, S. Huang, D. An, J. Lian, and Q. Zhao*, "Wave-driven Graph Neural Networks with Energy Dynamics for Over-smoothing Mitigation," in Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence (IJCAI-25), 2025, pp. 6579–6587. (人工智能顶级会议, CCF-A) 金融风险防控： [4] Q. Zhao, J. Huang, G. Liu*, Y. Miao, and P. Wang*, "A Multiinterest and Social Interest-Field Framework for Financial Security," IEEE Transactions on Computational Social Systems, vol. 11, no. 2, pp. 1685-1695, 2024. (SCI, 中科院二区, 社会计算领域TOP期刊) [5] D. An, Y. Yang, X. Gao, H. Qi, Y. Yang, X. Ye, M. Li, and Q. Zhao*, "Reinforcement Learning-Based Secure Training for Adversarial Defense in Graph Neural Networks," Neurocomputing, vol. 630, pp. 129704, 2025. (SCI, 中科院二区, TOP期刊) 大气环境预测： [6] Q. Zhao, J. Liu, X. Yang, H. Qi, and J. Lian*, "Spatiotemporal PM2.5 Forecasting via Dynamic Geographical Graph Neural Network," Environmental Modelling and Software, vol. 186, pp. 106351, 2025. (SCI, 中科院二区) [7] J. Lian, X. Wang, S. Huang, D. Wang, and Q. Zhao*, "AirMamba: A Deep Learning Framework for Long-Term PM2.5 Forecasting Integrating Multi-Scale Correlations and Time-Frequency Dynamics," Expert Systems with Applications, vol. 299, no. 129937, 2026. (SCI, 中科院一区, TOP期刊) [8] J. Lian, J. Shao, H. Yu, R. Chen, S. Huang, G. Chen, and Q. Zhao*, "Multi-modal Fusion Learning for Predicting Tropical Cyclone Intensity over Western North Pacific," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 18, pp. 7048-7063, 2025. (SCI, 中科院二区, TOP期刊) 2025年： [1] Q. Zhao, P. Wu, G. Liu, D. An, J. Lian*, and M. Zhou, "Sociological-Theories-Based Multi-Topic Self-Supervised Recommendation," IEEE Transactions on Neural Networks and Learning Systems, vol. 36, no. 6, pp. 11228-11242, 2025. (SCI, 中科院一区, TOP期刊) [2] Q. Zhao, J. Liu, X. Yang, H. Qi, and J. Lian*, "Spatiotemporal PM2.5 Forecasting via Dynamic Geographical Graph Neural Network," Environmental Modelling and Software, vol. 186, pp. 106351, 2025. (SCI, 中科院二区) [3] D. An, Y. Yang, X. Gao, H. Qi, Y. Yang, X. Ye, M. Li, and Q. Zhao*, "Reinforcement Learning-Based Secure Training for Adversarial Defense in Graph Neural Networks," Neurocomputing, vol. 630, pp. 129704, 2025. (SCI, 中科院二区, TOP期刊) [4] Q. Zhao, G. Yang, Y. Miao, J. Lian, H. Qi*, and Z. Kou, "Adaptive Sampling-based Heterogeneous Graph Enhancement," Computing and Informatics, vol. 44. no. 3, pp. 635-660, 2025. (SCI) [5] J. Lian, J. Shao, H. Yu, R. Chen, S. Huang, G. Chen, and Q. Zhao*, "Multi-modal Fusion Learning for Predicting Tropical Cyclone Intensity over Western North Pacific," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 18, pp. 7048-7063, 2025. (SCI, 中科院二区, TOP期刊) [6] P. Wu, H. Qi, S. Huang, D. An, J. Lian, and Q. Zhao*, "Wave-driven Graph Neural Networks with Energy Dynamics for Over-smoothing Mitigation," in Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence (IJCAI-25), 2025, pp. 6579–6587. (人工智能顶级会议, CCF-A) [7] J. Lian, X. Wang, S. Huang, D. Wang, and Q. Zhao*, "AirMamba: A Deep Learning Framework for Long-Term PM2.5 Forecasting Integrating Multi-Scale Correlations and Time-Frequency Dynamics," Expert Systems with Applications, vol. 299, no. 129937, 2026. (SCI, 中科院一区, TOP期刊) [8] X. Yang, X. Li*, and Q. Zhao, "A Multi-View Fusion Data-Augmented Method for Predicting BODIPY Dye Spectra," Mathematics, vol. 13, no. 18, pp. 2947, 2025. (SCI, JCR Q1) 2024年： [1] Q. Zhao, J. Huang, G. Liu*, Y. Miao, and P. Wang*, "A Multiinterest and Social Interest-Field Framework for Financial Security," IEEE Transactions on Computational Social Systems, vol. 11, no. 2, pp. 1685-1695, 2024. (SCI, 中科院二区, 社会计算领域TOP期刊) [2] Q. Zhao, F. Yang, D. An, and J. Lian*, "Modeling Structured Dependency Tree with Graph Convolutional Networks for Aspect-level Sentiment Classification," Sensors, vol. 24, no. 2, pp. 418, 2024. (SCI) [3] Q. Zhao, C. Yu, J. Huang, J. Lian, and D. An*, "Sentiment Analysis Based on Heterogeneous Multi-relation Signed Network," Mathematics, vol. 12, no. 2, pp. 331, 2024. (SCI, JCR Q1) [4] Q. Zhao, Y. Miao, D. An, J. Lian*, and M. Li, "HGNN-QSSA: Heterogeneous Graph Neural Networks with Quantitative Sampling and Structure-aware Attention," IEEE Access, vol. 12, pp. 25512-25524, 2024. (SCI) [5] Q. Zhao, Y. Miao, J. Lian, X. Li, and D. An*, "Louvain-Based Fusion of Topology and Attribute Structure of Social Networks," Computing and Informatics, vol. 43, no.1, pp. 94-125, 2024. (SCI) [6] C. Yu, X. Lin, Y. Yan, Y. Cheng, H. Wang, Y. Huang, W. Zhao, L. Liu, Q. Zhao*, J. Wang*, and L. Zhang*, "AbDPP: Target-oriented Antibody Design with Pre-training and Prior Biological Structure Knowledge," Proteins: Structure, Function, and Bioinformatics, vol. 92, no. 10, pp. 1147-1160, 2024. (SCI) [7] J. Lian, S. Wu, S. Huang, and Q. Zhao*, "A Novel Sequence-to-Sequence Based Deep Learning Model for Satellite Cloud Image Time Series Prediction," Atmospheric Research, vol. 306, pp. 107457, 2024. (SCI, 中科院二区, TOP期刊) [8] Q. Zhao, P. Wu, J. Lian, D. An*, and M. Li, "TaneNet: Two-level Attention Network Based on Emojis for Sentiment Analysis," IEEE Access, vol. 12, pp. 86106-86119, 2024. (SCI) [9] D. An, Z. Pan, Q. Zhao, W. Liu, and J. Liu*, "Unsupervised Graph Structure Learning Based on Optimal Graph Topology Modeling and Adaptive Data Augmentation," Mathematics, vol. 12, no. 13, pp. 1991, 2024. (SCI, JCR Q1) [10] D. An, Y. Yang, W. Liu, Q. Zhao, J. Liu, H. Qi, and J. Lian*, "A Secure GNN Training Framework for Partially Observable Graph," Electronics, vol. 13, no. 14, pp. 2721, 2024. (SCI) [11] D. An, H. Zhang, Q. Zhao, J. Liu, J. Shi*, Y. Huang, Y. Yang, X. Liu, and S. Qin, "Graph Convolutional Network Robustness Verification Algorithm Based on Dual Approximation," in Proceedings of International Conference on Formal Engineering Methods, pp. 146-161, 2024. (CCF-C) 2023年： [1] Q. Zhao, G. Liu, F. Yang, R. Yang*, Z. Kou, and D. Wang, "Self-Supervised Signed Graph Attention Network for Social Recommendation," in Proceedings of the International Joint Conference on Neural Networks, pp. 1-9, 2023. (CCF-C) [2] H. Huang, P. Wang*, Z. Zhang, and Q. Zhao, "A Spatio-Temporal Attention-based GCN for Anti-Money Laundering Transaction Detection," in Proceedings of the 19th International Conference on Advanced Data Mining and Applications, pp. 634-648, 2023. (CCF-C) 2022年： [1] Q. Zhao, Z. Zhou, J. Li, S. Jia, and J. Pan*, "Time-Dependent Prediction of Microblog Propagation Trends Based on Group Features," Electronics, vol. 11, no. 16, pp. 2585, 2022. (SCI) [2] N. Fu, Q. Zhao*, Y. Miao, B. Zhang, and D. Wang, "A Representation Learning Method of Graph Convolutional Network Based on Structure Enhancement," Computing and Informatics, vol. 41, no. 6, pp. 1563–1588, 2022. (SCI) [3] J. Pan, H. Li, J. Teng, Q. Zhao*, and M. Li*, "Dynamic Network Representation Learning Method Based on Improved GRU Network," Computing and Informatics, vol. 41, no. 6, pp. 1491–1509, 2022. (SCI) 2021年以前： [1] Q. Zhao*, C. Wang, and C. Jiang, "HSim: A Novel Method on Similarity Computation by Hybrid Measure," in Proceedings of IEEE International Conference on Information and Communication Systems (ICICS), pp. 160-165, 2015. (EI) [2] 赵勤, 王成, 王鹏伟. 一种基于社区分类的社交网络用户推荐方法[J]. 计算机科学, 2016, 43(5): 198-203. (CCF-B) [3] Q. Zhao, Y. He, C. Jiang*, P. Wang, M. Qi, and M. Li, "Integration of Link and Semantic Relations for Information Discovery and Recommendation," Computing and Informatics, vol. 35, no. 1, pp. 30-54, 2016. (SCI) [4] B. Zhang, H. Zhang, M. Li*, Q. Zhao, and J. Huang, "Trust Traversal: A Trust Link Detection Scheme in Social Network," Computer Networks, vol. 120, pp. 105-125, 2017. (SCI) [5] B. Zhang, C. Mu, Q. Zhao*, Z. Peng, J. Ding, and B. Liu, "A Multidimensional Comprehensive Recommendation Method Based on Social Network," in Proceedings of 5th International Conference on Advanced Cloud and Big Data (CBD), Shanghai, China, 2017.08.13-08.16. (EI) [6] 张波, 金玉鹏, 张倩, 赵勤, 王娇燕. 试论一种新型在线教育资源大数据组织框架, 中国电化教育, 2018 (3): 41-46. (CSSCI) [7] Q. Zhao, C. Wang, P. Wang, M. Zhou, and C. Jiang*, "A Novel Method on Information Recommendation via Hybrid Similarity," IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 48, no. 3, pp. 448-459, 2018. (SCI, 中科院一区, TOP期刊) [8] D. Qin, J. Yu, G. Zou, R. Yong, Q. Zhao*, and B. Zhang*, "A Novel Combined Prediction Scheme Based on CNN and LSTM for Urban PM2.5 Concentration," IEEE Access, vol. 7, pp.20050-20059, 2019. (SCI) [9] W. Liu, P. Wang*, Y. Meng, Q. Zhao*, C. Zhao, and Z. Zhang, "A Novel Model for Optimizing Selection of Cloud Instance Types," IEEE Access, vol. 7, pp. 120508 – 120521, 2019. (SCI) [10] 秦东明, 丁志军, 金玉鹏, 赵勤*. 基于自编码网络的空气污染物浓度预测[J]. 同济大学学报: 自然科学版, 2019, 47(5): 681-687. (EI) [11] S. Huang, Q. Zhao*, X. Xu, B. Zhang*, and D. Wang, "Emojis-Based Recurrent Neural Network for Chinese Microblogs Sentiment Analysis," in Proceedings of IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI), pp. 59-64, November 2019. (EI) [12] 秦东明, 喻剑, 张波, 赵勤*. 基于分布式无共享架构的海量数据并行查询平台[J]. 计算机科学, 2019, 46(4): 44-49. (CCF-B) [13] B. Zhang, L. Zhang, C. Mu, Q. Zhao, Q. Song, and X. Hong*, "A Most Influential Node Group Discovery Method for Influence Maximization in Social Networks: A Trust-Based Perspective," Data & Knowledge Engineering, vol. 121, pp. 71–87, 2019. (SCI, CCF-B) [14] C. Wang, H. Zhu, C. Wang, Q. Zhao, and B. Zhang, "Transport Complexity of Data Dissemination in Large-Scale Online Social Networks," in Proceedings of the ACM Turing Celebration Conference-China, pp. 1–5, 2019. (EI) [15] G. Zou, B. Zhang*, R. Yong, D. Qin, and Q. Zhao, "FDN-learning: Urban PM2. 5-concentration Spatial Correlation Prediction Model Based on Fusion Deep Neural Network," Big Data Research, vol. 26, pp. 100269, 2021. (SCI)
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