基本信息
史晓雨  男    中国科学院重庆绿色智能技术研究院
电子邮件: xiaoyushi@cigit.ac.cn
通信地址: 重庆市北碚区方正大道266号
邮政编码:

研究领域

  • Data Science, Data Mining && Machine Learning: Methods and Applications

  • Recommender Systems && Social Network Analysis

招生信息

**欢迎执着创新、积极主动、志存高远而又能脚踏实地的本科生和研究生同学加入团队

招生专业
081202-计算机软件与理论
招生方向
大数据挖掘
信息推荐技术
人工智能

教育背景

2012-09--2014-06   美国田纳西大学电子工程与计算机科学系   联合培养博士(国家公派)
2008-09--2015-06   电子科技大学计算机学院   工学博士
2003-09--2007-06   解放军信息工程大学电子技术学院   本科学士

工作经历

   
工作简历
2018-01~现在, 中国科学院重庆绿色智能技术研究院, 副研究员
2015-07~2017-12,中国科学院重庆绿色智能技术研究院, 助理研究员

专利与奖励

   
专利成果
[1] 史晓雨, 尚明生. 一种融合用户偏好预测的深度强化学习推荐方法. CN202111519219.9, 2021-12-06.
[2] 王国胤, 董建华, 尚明生, 严胡勇, 王浩林, 郑志浩, 史晓雨. 基于邻域粗糙集和PCA融合的数据分类预测方法. CN: CN107016416B, 2021-02-12.
[3] 史晓雨, 尚明生, 王思源. 一种对抗攻击敏感的文本分类方法. CN: CN111984762A, 2020-11-24.
[4] 史晓雨, 尚明生, 吕元鑫, 冉龙玉. 一种混凝土生产配合比的智能设计方法. CN: CN110435009B, 2020-11-10.
[5] 史晓雨, 尚明生, 罗梦珍, 白亚男. 一种面向不平衡文本数据的自分类方法. CN: CN110609898A, 2019-12-24.
[6] 尚明生, 史晓雨. 一种基于用户自主选择的个性化推荐方法和系统. CN: CN105512183B, 2019-10-11.
[7] 史晓雨, 尚明生, 吕元鑫. 一种混凝土28d抗压强度预测方法. CN: CN110263431A, 2019-09-20.
[8] 封丽, 封雷, 李崇明, 尚明生, 周博天, 闪坤, 程艳茹, 张君, 刘鑫, 刘异齐, 张韵, 史晓雨. 一种基于用户优先度的遥感分发方法及系统. CN: CN107104956B, 2019-07-26.
[9] 史晓雨, 冀倩倩, 尚明生. 一种不完备专利自动标引方法. CN: CN109726299A, 2019-05-07.
[10] 史晓雨, 尚明生, 白亚男. 一种高效能数据中心云服务器资源自主管理方法和系统. CN: CN109491760A, 2019-03-19.
[11] 田文洪, 王金, 何博, 叶宇飞, 尚明生, 史晓雨. 一种基于深度强化学习的资源调度方法和系统. 中国: CN108595267A, 2018-09-28.
[12] 史晓雨, 尚明生, 田文洪, 罗辛. 一种能耗感知的云计算服务器资源在线管理方法和系统. 中国: CN106648890A, 2017-05-10.
[13] 尚明生, 李健, 史晓雨. 一种在线系统中用户定制推荐系统的方法. 中国: CN105404678A, 2016-03-16.

出版信息

   
发表论文
[1] Shi, Xiaoyu, He, Qiang, Luo, Xin, Bai, Yanan, Shang, Mingsheng. Large-Scale and Scalable Latent Factor Analysis via Distributed Alternative Stochastic Gradient Descent for Recommender Systems. IEEE TRANSACTIONS ON BIG DATA[J]. 2022, 8(2): 420-431, [2] wang qingxian, Shi,Xiaoyu. Siamese Generative Adversarial Predicting Network for Extremely Sparse Data in Recommendation System. 2021 IEEE Intl Conf on Parallel & Distributed Processing with Applicationsnull. 2021, [3] Chen, Lin, Gong, Saijun, Shi, Xiaoyu, Shang, Mingsheng. Dynamical Conventional Neural Network Channel Pruning by Genetic Wavelet Channel Search for Image Classification. FRONTIERS IN COMPUTATIONAL NEUROSCIENCE[J]. 2021, 15: http://dx.doi.org/10.3389/fncom.2021.760554.
[4] Shang, Tianqi, Li, Xinxin, Shi, Xiaoyu, Wang, Qingxian. Joint Modeling Dynamic Preferences of Users and Items Using Reviews for Sequential Recommendation. ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PAKDD 2021, PT IInull. 2021, 12713: 524-536, [5] Li, Xinxin, Shang, Tianqi, Peng, Dezhong, Shi, Xiaoyu. Deep Sentiment Learning Network for Temporal-aware Recommendation Based on User Reviews. 2021 IEEE 6TH INTERNATIONAL CONFERENCE ON BIG DATA ANALYTICS (ICBDA 2021)null. 2021, 339-343, [6] Longyu Ran, Xiaoyu Shi, Mingsheng Shang. SLAs-aware Online Task Scheduling based on Deep Reinforcement Learning Method in Cloud Environment. 2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems : Volume 3 of 4.null. 2020, 1518-1525, [7] Bai, Yanan, Shi, Xiaoyu, Wu, Wenyuan, Chen, Jingwei, Feng, Yong. seIMC: A GSW-Based Secure and Efficient Integer Matrix Computation Scheme With Implementation. IEEE ACCESS[J]. 2020, 8: 98383-98394, https://doaj.org/article/f86efe3eadca43a1a934916a9004bd41.
[8] Wang, Dexian, Chen, Yanbin, Guo, Junxiao, Shi, Xiaoyu, He, Chunlin, Luo, Xin, Yuan, Huaqiang. Elastic-net regularized latent factor analysis-based models for recommender systems. NEUROCOMPUTING[J]. 2019, 329: 66-74, http://119.78.100.138/handle/2HOD01W0/7197.
[9] Shi Xiaoyu. A Deep Temporal Collaborative Filtering Recommendation Framework via Joint Learning from Long and Short-Term Effects. 2019 IEEE Int’l Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, (ISPA). 2019, [10] Wang, Qingxian, Peng, Binbin, Shi, Xiaoyu, Shang, Tianqi, Shang, Mingsheng. DCCR: Deep Collaborative Conjunctive Recommender for Rating Prediction. IEEE ACCESS[J]. 2019, 7: 60186-60198, https://doaj.org/article/d522fc56faf64aca8146e94d4248af44.
[11] Zhang Ying, Shi Xiaoyu, Shang MingSheng, Mao Yelu. TCR: Temporal-CNN for Reviews Based Recommendation System. 2nd International Conference on Deep Learning Technologies, ICDLT 2018null. 2018, 71-75, http://119.78.100.138/handle/2HOD01W0/7948.
[12] Wang, QingXian, Luo, Xin, Li, Yan, Shi, XiaoYu, Gu, Liang, Shang, MingSheng. Incremental Slope-one recommenders. NEUROCOMPUTING[J]. 2018, 272: 606-618, http://dx.doi.org/10.1016/j.neucom.2017.07.033.
[13] Tian, Wenhong, He, Majun, Guo, Wenxia, Huang, Wenqiang, Shi, Xiaoyu, Shang, Mingsheng, Toosi, Adel Nadjaran, Buyya, Rajkumar. On minimizing total energy consumption in the scheduling of virtual machine reservations. JOURNAL OF NETWORK AND COMPUTER APPLICATIONS[J]. 2018, 113: 64-74, http://119.78.100.138/handle/2HOD01W0/8051.
[14] Shi, Xiaoyu, Luo, Xin, Shang, Mingsheng, Gu, Liang. Long-term performance of collaborative filtering based recommenders in temporally evolving systems. NEUROCOMPUTING[J]. 2017, 267: 635-643, http://dx.doi.org/10.1016/j.neucom.2017.06.026.
[15] Shi, Xiaoyu, Shang, MingSheng, Luo, Xin, Khushnood, Abbas, Li, Jian. Long-term effects of user preference-oriented recommendation method on the evolution of online system. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS[J]. 2017, 467: 490-498, http://dx.doi.org/10.1016/j.physa.2016.10.033.
[16] 董建华, 王国胤, 雍熙, 史晓雨, 李庆亮. 基于Spark的标准化PCA算法. 郑州大学学报:工学版. 2017, 38(5): 7-12, http://lib.cqvip.com/Qikan/Article/Detail?id=673442818.
[17] Yan, Huyong, Wang, Guoyin, Wu, Di, Huang, Yu, Shang, Mingsheng, Xu, Jianjun, Shan, Kun, Shi, Xiaoyu, Dong, Jianhua, Feng, Lei, Zhou, Botian, Yuan, Ye, Zhao, Yufei. Water Bloom Precursor Analysis Based on Two Direction S-Rough Set. WATER RESOURCES MANAGEMENT[J]. 2017, 31(5): 1435-1456, https://www.webofscience.com/wos/woscc/full-record/WOS:000398042800002.
[18] Wang, QingXian, Zhang, JunJie, Shi, XiaoYu, Shang, MingSheng. User Heterogeneity and Individualized Recommender. CHINESE PHYSICS LETTERS[J]. 2017, 34(6): http://lib.cqvip.com/Qikan/Article/Detail?id=672497629.
[19] Yan, Huyong, Wu, Di, Huang, Yu, Wang, Guoyin, Shang, Mingsheng, Xu, Jianjun, Shi, Xiaoyu, Shan, Kun, Zhou, Botian, Zhao, Yufei. Water eutrophication assessment based on rough set and multidimensional cloud model. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS[J]. 2017, 164: 103-112, http://dx.doi.org/10.1016/j.chemolab.2017.02.005.
[20] Shi, Xiaoyu, Dong, Jin, Djouadi, Seddik M, Feng, Yong, Ma, Xiao, Wang, Yefu. PAPMSC: Power-Aware Performance Management Approach for Virtualized Web Servers via Stochastic Control. JOURNAL OF GRID COMPUTING[J]. 2016, 14(1): 171-191, [21] Shi, Xiaoyu, Briere, Christopher A, Djouadi, Seddik M, Wang, Yefu, Feng, Yong. Power-aware performance management of virtualized enterprise servers via robust adaptive control. CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS[J]. 2015, 18(1): 419-433, https://www.webofscience.com/wos/woscc/full-record/WOS:000350395500035.
[22] 白亚男, 史永昌, 史晓雨. 基于自适应控制方法的云计算服务器性能管理. 计算机与数字工程. 2014, 42(9): 1668-1672, http://lib.cqvip.com/Qikan/Article/Detail?id=662322159.
[23] 白亚男, 史永昌, 史晓雨. 神经网络结合并行混沌粒子群优化算法的波前预测器. 计算机与数字工程. 2013, 41(6): 1024-1026, http://lib.cqvip.com/Qikan/Article/Detail?id=46332047.

科研活动

   
科研项目
( 1 ) 服务机器人云服务平台研制与应用, 主持, 省级, 2020-01--2021-12
( 2 ) 大数据在药物化学合成中的应用, 主持, 省级, 2019-08--2021-08
( 3 ) 新冠肺炎药物研发大数据平台关键技术研发, 主持, 省级, 2020-02--2020-06
( 4 ) 中科院青年创新会人才计划, 主持, 部委级, 2017-01--2020-12
( 5 ) 建筑行业大数据平台建设与应用示范, 主持, 省级, 2018-01--2020-06
参与会议
(1)A Deep Temporal Collaborative Filtering Recommendation Framework via Joint Learning from Long and Short-Term Effects   2019-12-18
(2)SLAs-aware Online Task Scheduling based on Deep Reinforcement Learning Method in Cloud Environment   2019-08-10