张海鹏
助理教授、研究员、博导
博士毕业院校:美国印第安纳大学
电话:(021)20684458
办公室:信息学院1A-404C室
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研究领域
个人简历
代表性论文

研究领

  • 数据挖掘、金融科技、时间地理数据挖掘、社交媒体挖掘



个人简历

张海鹏博士于2018年8月全职加入上海科技大学信息科学与技术学院,任助理教授、研究员。2009年本科毕业于南京大学,获软件工程学士学位,2007年秋季学期在香港科技大学交换学习。2014年博士毕业于美国印第安纳大学,获计算机科学博士学位,导师为Prof. David J. Crandall。

论文发表于WWW、WSDM、CIKM等国际顶级会议,并获得美国专利。大规模时空地理数据挖掘与建模的成果被英国《新科学家》(New Scientist)杂志以及美国计算机协会(ACM)报道。2010年至2013年期间曾在日本东京National Institute of Informatics,美国加州eBay研究院,英国剑桥微软研究院以及美国加州三星研究院进行数据挖掘研究。2014年至2018年,分别在IBM研究院与中国金融期货交易所从事数据科学与金融科技研究工作,参与IBM人机辩论系统Project Debater研发,在中国证监会系统刊物上发表多篇金融科技研究报告。入选上海市青年英才扬帆计划,并主持中国博士后科学基金、上海市软科学重点项目以及中国外汇交易中心、深圳证券交易所等大型金融机构金融科技研究课题。


代表性论文

  1. Ling, S., Yu, Z.*, Cao, S.*, Zhang, H.*, and Hu, S., STHAN: Transportation Demand Forecasting with Compound Spatial-temporal Relationships. ACM Transactions on Knowledge Discovery from Data (TKDD). (CCF B)

  2. Lyu, S., Cai, H., Zhang, C., Ling, S., Shen, Y., Zeng, X., Gu, J. and Zhang, H.*. See Clicks Differently: Modeling User Clicking Alternatively with Multi Classifiers for CTR Prediction. ACM International Conference on Information & Knowledge Management (CIKM) 2022. (CCF B)

  3. Zhao, Y., Zhang, H.*, Lyu, S., Jiang, R., Gu, J. and Zhang, G. Multiple Instance Learning for Uplift Modeling. ACM International Conference on Information & Knowledge Management (CIKM) 2022. (CCF B)

  4. Chen, L., Ouyang, Y., Zhang, H., Hong, S., and Li, Q. RISeer: A Visual Analytics Approach to Inspecting the Dynamics of Regional Industrial Structure. IEEE Visualization, 2022, to appear. (CCF A)

  5. Li, Z., Hu, H., Wang, H., Cai L., Zhang, H.*, and Zhang, K. Why does the president tweet this? discovering reasons and contexts for politicians’ tweets from news articles. Information Processing & Management, 2022. (IF 6.22, CAS 1, CCF B)

  6. Wang Z., Wang F., Zhang H., Yang M., Cao S., Wen Z., and Zhang Z., “Could You Describe the Reason for the Transfer?': A Reinforcement Learning Based Voice-Enabled Bot Protecting Customers from Financial Frauds”, in Proceedings of 2021 ACM Conference on Information and Knowledge Management, 2021. (CCF B)

  7. Guo K, Jiang T., and Zhang H.*, “Knowledge Graph Enhanced Event Extraction in Financial Documents”, in Proceedings of 2020 IEEE International Conference on Big Data, 2020. (CCF C)

  8. Li, Z., Lyu, S., Zhang, H.*, and Jiang, T. (2021). “One Step Ahead: A Framework for Detecting Unexpected Incidents and Predicting the Stock Markets”. IEEE Access, 9, 30292-30305.

  9. Zhang H., Korayem M., Crandall D. J., and LeBuhn G., “Mining photo-sharing websites to study ecological phenomena”, in Proceedings of the 21st international conference on World Wide Web, ACM, pp. 749-758, 2012. (oral, 12%, CCF A)

  10. Zhang H., Korayem M., You E., and Crandall D. J., “Beyond co-occurrence: discovering and visualizing tag relationships from geo-spatial and temporal similarities”, in Proceedings of the fifth ACM international conference on Web search and data mining, ACM, pp. 33-42, 2012. (plenary talk, 8.3%, CCF B)

  11. Zhang H., Parikh N., Singh G., and Sundaresan N. “Chelsea won, and you bought a t-shirt: Characterizing the interplay between twitter and e-commerce”, in Proceedings of the 2013 IEEE/ACM international conference on advances in social networks analysis and mining, ACM, pp. 829-836, 2013. (oral, Best Paper Award)

  12. Zhang H., Yan, Z., Yang, J., Tapia, E. M., and Crandall, D. J., “Mfingerprint: Privacy-preserving user modeling with multimodal mobile device footprints”, in Proceedings of International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction, Springer, pp. 195-203, 2014. (oral, 24%)

  13. Lee S., Zhang H., and Crandall D. J., “Predicting geo-informative attributes in large-scale image collections using convolutional neural networks”, in Proceedings of 2015 IEEE Winter Conference on Applications of Computer Vision, pp. 550-557, 2015. (oral, 36.7%)