个人简介
工作经历
2017年6月至今 南京理工大学 副教授
2015年6月至2017年5月 南京理工大学 讲师
访问学者经历
2019年3月至今 University of Pittsburgh（匹兹堡大学），电气与计算机工程系，访问学者
2017年7月至2017年9月 University of Technology Sydney（悉尼科技大学），工程与信息技术学部， 访问学者
工业界工作经历
2006年7月至2012年8月 著名IT企业 历任软件工程师，高级软件工程师，项目经理，研发主管等职位
教育经历
2012年9月至2015年6月 合肥工业大学 计算机应用技术 工学博士
2013年9月至2014年9月 University of Central Arkansas 计算机系 国家留学基金委联合培养博士生
2003年9月至2006年7月 中科院研究生院 计算机软件与理论 工学硕士
1999年9月至2003年7月 安徽大学 工学学士
近期论文
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[1] Jing Zhang, Victor S. Sheng, & Jian Wu. (Online). Crowdsourced Label Aggregation Using Bilayer Collaborative Clustering. IEEE Transactions on Neural Networks and Learning Systems, DOI:10.1109/TNNLS.2018.2890148. (中科院大类1区, CCF B类)
[2] Jing Zhang, Min Wu, & Victor S. Sheng. (Aug. 2019). Ensemble Learning from Crowds. IEEE Transactions on Knowledge and Data Engineering, vol. 31, no. 8, pp. 1506–1519. (CCF A类, 中科院大类2区)
[3] Victor S. Sheng, Jing Zhang*, Bin Gu*, & Xindong Wu. (July 2019). Majority Voting and Pairing with Multiple Noisy Labeling. IEEE Transactions on Knowledge and Data Engineering, vol. 31, no. 7, pp. 1355–1368. (CCF A类, 中科院大类2区)
[4] Jing Zhang, Victor S. Sheng, Tao Li, & Xindong Wu. (May 2018). Improving Crowdsourced Label Quality Using Noise Correction. IEEE Transactions on Neural Networks and Learning Systems,vol. 29, no. 5, pp. 1675–1688. (中科院大类1区, CCF B类)
[5] Jing Zhang, Shicheng Cui, Yan Xu, Qianmu Li, & Tao Li. (May 2018). A Novel Data-Driven Stock Price Trend Prediction System. Expert Systems with Applications, vol. 97, pp. 60–69. (中科院大类2区, CCF C类)
[6] Jing Zhang, Victor S. Sheng, Qianmu Li, Jian Wu, & Xindong Wu. (Mar. 2017). Consensus Algorithms for Biased Labeling in Crowdsourcing. Information Sciences, vol. 382, pp. 254–273. (中科院大类2区, CCF B类)
[7] Jing Zhang, Xindong Wu, & Victor S. Sheng. (Dec. 2016). Learning from Crowdsourced Labeled Data: a Survey. Artificial Intelligence Review, vol. 46, no. 4, pp. 543–576. (中科院大类3区)
[8] Jing Zhang, Qianmu Li, & Wei Zhou. (Sept. 2016). HDCache: A Distributed Cache System for Real-Time Cloud Services. Journal of Grid Computing. vol. 14, no. 3, pp. 407–428. (中科院大类3区, CCF C类)
[9] Jing Zhang, Victor S. Sheng, Jian Wu, & Xindong Wu. (Apr. 2016). Multi-Class Ground Truth Inference in Crowdsourcing with Clustering. IEEE Transactions on Knowledge and Data Engineering, vol. 28, no. 4, pp. 1080–1085. (CCF A类, 中科院大类2区)
[10] Jing Zhang, Victor S. Sheng, Bryce A. Nicholson, & Xindong Wu. (Dec. 2015). CEKA: A Tool for Mining the Wisdom of Crowds. Journal of Machine Learning Research, vol. 16, pp. 2853–2858. (CCF A类, 中科院大类2区)
[11] Jing Zhang, Xindong Wu, & Victor S. Sheng. (May 2015). Active Learning with Imbalanced Multiple Noisy Labeling. IEEE Transactions on Cybernetics, vol. 45, no. 5, pp. 1081–1093. (中科院大类1区, CCF B类)
[12] Jing Zhang, Xindong Wu, & Victor S. Sheng. (Feb. 2015). Imbalanced Multiple Noisy Labeling. IEEE Transactions on Knowledge and Data Engineering, vol. 27, no. 2, pp. 489–503. (CCF A类，中科院大类2区)
[13] Victor S. Sheng & Jing Zhang*. (Jan. 27-Feb. 1, 2019). Machine Learning with Crowdsourcing: A Brief Summary of the Past Research and Future Directions. In Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI), Honolulu, Hawaii, USA. (CCF A类)
[14] Jing Zhang & Xindong Wu. (Aug. 19-23, 2018). Multi-Label Inference for Crowdsourcing. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), London, United Kingdom. (CCF A类)
[15] Jing Zhang, Victor S. Sheng, & Tao Li. (Aug. 7-11, 2017). Label Aggregation for Crowdsourcing with Bi-Layer Clustering. In Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), Tokyo, Japan, pp. 921–924. (CCF A类)
[16] Jing Zhang, Victor S. Sheng, Jian Wu, Xiaoqin Fu, & Xindong Wu. (Oct. 19-23, 2015). Improving Label Quality in Crowdsourcing Using Noise Correction. In Proceedings of the 24th ACM International Conference on Information and Knowledge Management (CIKM), Melbourne, Australia, pp. 1931–1934. (CCF B类会议)
[17] Jing Zhang, Xindong Wu, & Victor S. Sheng. (Aug. 25-28, 2013). A Threshold Method for Imbalanced Multiple Noisy Labeling. In Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Niagara Falls, Canada, pp. 61–65.
[18] Jing Zhang, Xindong Wu, & Victor S. Sheng. (Jul. 14-18, 2013). Imbalanced Multiple Noisy Labeling for Supervised Learning. In Proceedings of the 27th AAAI Conference on Artificial Intelligence (AAAI), Bellevue, Washington, USA, pp. 1651–1652. (CCF A类)
[19] Jing Zhang, Gongqing Wu, Xuegang Hu. & Xindong Wu. (Sept. 20-23, 2012). A Distributed Cache for Hadoop Distributed File System in Real-Time Cloud Services. In Proceedings of the 13th ACM/IEEE International Conference on Grid Computing (GRID), Beijing, China, pp.12–21.
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