基本信息

王浩, 海外人才引进

岗位教授,中国科学院大学

副研究员,软件研究所 

电子邮件:cashenry(--AT--)126.com

通信地址:中关村南四街4号中科院软件所

邮政编码:100190

研究兴趣

写在前面: 我们不培养成为日夜加班的码农,我们只培养成为数据科学领域的未来领袖。

致力于帮助学生们成为具有批判性思维的人、能用创新思维去解决问题(甚至是人们尚未发现的问题)的人,对世界充满好奇喜欢问问题的人

News:   2篇文章被 ICDM 2017 录用。
News:  时空用户建模与个性化推荐  被 KDD2017 (Research Track) 录用。 

News:  2017年2月,随着人工智能和大数据时代的到来, "数据科学与智能系统"国际团队正式成立,一支以国际学术前沿为导向,以国内外杰出青年人才为主的的科研和工程团队,隶属于"软件所协同创新中心-XLAB"


研究领域主要在(1)数据科学和(2)智能系统,具体研究方向在:
数据科学:
数据挖掘、机器学习、社交媒体挖掘、自然语言处理与信息检索等

智能系统:
智能软件系统、基于知识的系统 、决策支持系统
2015年10月11日,我们荣获智能系统国际会议SMC2015 唯一杰出论文奖(Franklin V. Taylor Memorial Award)。[新闻链接
]


与国际联合研究方向
智能推荐、用户画像和建模

计算机视觉 :人脸识别、目标检测

深度学习在图像和自然语言中的应用



当前面向大数据智能信息处理研究课题如下:
(1) 基于语义的大数据集成与融合
(2) 大数据挖掘与机器学习并行算法
(3) 大规模社交网络分析技术
(4) 大规模科学与信息可视化技术
(5) 大数据与深度学习技术
(6) 大数据社交媒体挖掘与分析
(7) 大规模用户行为挖掘与分析

受资助科研项目情况:

国家自然科学基金,2017-2020
所杰出青年人才发展专项, 2015-2018
教育部留学回国人员启动基金, 2015-2016
国家重点基础研究发展计划(973计划), 2014-2017
国家自然科学基金, 2014-2016
北京市自然科学基金, 2014-2015
所海外人才启动基金, 2014-2015 
北京市科委绿色通道项目, 2013-2014

招生信息

欢迎具有相关专业知识背景的优秀学生报考,Email是直接联系到我最有效的方式。

招生专业
081203-计算机应用技术

工作经历

2015-至今,岗位教授,中国科学院大学。

2012.12 至今,副研究员,海外人才引进,中科院软件所。

教育背景
博士,国家公派留学生。曾游走过日本东京大学以及美国加州大学伯克利分校。期间也曾经走访过斯坦福大学、麻省理工学院、哥伦比亚大学等。

专利与奖励

Young Researcher Shouldering The Future,海外, 2011 
Best Paper Award,国际会议,2011 
Outstanding Research Assistant,海外,2011
Best Poster Award,国际会议,2010 

出版信息

国际会议 Conference 【部分近几年成果 (2014-2017)

Wang Hao, Fu YM, Wang QY, Du CY, Hong ZY, Xiong H. A Location-Sentiment-Aware Recommender System for Both Home-Town and Out-of-Town Users. KDD2017.

Fredholm Multiple Kernel Learning for Semi-Supervised Domain Adaptation. AAAI 2017.

SuHierarchical Dynamic Parsing and Encoding for Action Recognition. ECCV 2016.

Xie M., Yin H., Wang Hao, et al. Learning Graph-based POI Embedding for Location-based Recommendation. CIKM 2016.

Yin,H.,Hu, Z., Zhou,X. Wang Hao, et.al. Discovering Interpretable Geo-Social Communities for User Behavior Prediction. ICDE 2016.

Gao, Y., Francesca T. and Wang Hao, Argumentation-Based Multi-Agent Decision Making with Privacy Preserved. AAMAS 2016.

Wang Hao, et al. A Unified Framework for Fine-Grained Opinion Mining from Online Reviews. HICSS 2016.
Zhang C., Wang Hao, EventPanorama: A Framework for Multi-grained Event Detection, Visualization and Perception from Online News, HICSS 2016.

Zhao M, Wang Hao*, et al(2015).. LSIF: A System for Large-scale Information Flow Detection Based on Topic-related Semantic Similarity Measurement. IEEE/WIC/ACM WI 2015.
Yin H,, Zhou X., Shao Y., Wang Hao, Sadiq, S. Joint Modeling of User Check-in Behaviors for Point-of-Interest Recommendation ". CIKM 2015.
Zhang C*, Wang Hao*, et al(2015). RCFGED: Retrospective Coarse and Fine-Grained Event Detection from Online News. SMC 2015
* equal contribution(Best Paper Award)
Wang, Y., Zhang C, Wang Hao, et al (2015). CiFDAL: A graph layout algorithm to enhance human cognition in Idea Discovery. SMC 2015
Wang, W, Wang Hao, et al (2015). Transfer Feature Representation via Multiple Kernel Learning. AAAI 2015.
Wang, QY, Wang Hao, et al(2014). A Parallel Implementation of IdeaGraph to Extract Rare Chances from Big Data. Modat, ICDM 2014.
Zhao, QY, Wang Hao * , et al (2014). Joint propagation and refinement for opinion minng words and targets. SENTIRE, ICDM 2014.
Zhao, QY, Wang Hao*, et al  (2014). A Bootstrapping Based Refinement Framework For Mining Opinion Words and Targets. CIKM 2014.
Wang Hao, et al (2014). Human-Centric Computational Knowledge Enviroment for Complex and Ill-Stutured Problem Solving. SMC 2014
Zhang C., Wang Hao, et al (2014). An Improved IdeaGraph Algorithm for Discovering Important Rare Events. SMC 2014
Wang Hao, Wang W.*  , et al (2014). Cross-Domain Metric Learning Based on Information Theory. AAAI 2014.

国际期刊 Journal 

Spatial-Aware Hierarchical Collaborative Deep Learning for POI Recommendation. IEEE Transaction on Knowledge and Data Engineering (TKDE). 2017. 

A cognition graph approach for insights generation from event sequences. Cluster Computing, 2017.

Discriminative Dimensionality Reduction for Multi-dimensional Sequences[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017.

Discriminative Transformation for Multi-Dimensional Temporal Sequences (TIP). 2017

Adapting to User Interest Drift for POI Recommendation.IEEE Transaction on Knowledge and Data Engineering (TKDE). 2016

A Hybrid Term-Term Relations Analysis Approach for Topic Detection. Knowledge-based Systems (KBS). 2016.

Idea discovery: A scenario-based systematic approach for decision making in market innovation, Expert Systems with Applications (ESWA), 2013. 

Innovation Support System for Creative Product Design Based on Chance Discovery, Expert Systems With Applications (ESWA), 2012.


论著章节 Book Chapters 
Wang, Hao. et al. Idea Discovery: A Context-Awareness Dynamic System Approach for Computational Creativity. In Smart Modeling and Simulation for Complex Systems.  Springer, 2015.
Wang Hao, et.al. IdeaGraph: Turning Data into Human Insights for Collective Intelligence. Foundations and Applications of Intelligent Systems, Springer, 2013. 
Wang Hao, et.al. Data-Driven Innovation Technologies for Smarter Business from Innovators’ Market Game to iChance Creativity Support System, Advances in Chance Discovery, Springer, 2012.