Hao WANG

Ph.D. Assistant Researcher

Reasoning & Learning Group
Dept. Computer Science and Technology
Nanjing University

163 Xianlin Avenue
Nanjing, Jiangsu 210023, China
Email: wanghao@nju.edu.cn

I received my Bachelor's Degree in Mathematics from the Department of Mathematics, Nanjing University (NJU) in 2005 and Master's Degree in Computer Science from the Department of Computer Science and Technology, NJU in 2008. I received my PhD from the Department of Computer Science, The University of Hong Kong (HKU) in 2014. Currently, I am an assistant researcher at the Department of Computer Science and Technology, NJU. I visited King Abdullah University of Science and Technology (KAUST) in July 2011, National Technical University of Athens (NTUA) from September to December 2012, and University of Macau (UM) from August to October 2013.

Research Interests

I am interested in many aspects of Data Management and Machine Learning, with recent focus on:
  • Rank-aware query processing / data indexing
  • Recommender systems / location-based social networking
  • Reinforcement learning & transfer learning

Publications

    Conference Papers

    • Yan Li, Ngai Meng Kou, Hao Wang, Leong Hou U, and Zhiguo Gong, "A confidence-aware top-k query processing toolkit on crowdsourcing," in: 43rd International Conference on Very Large Data Bases (VLDB), Munich, Germany, August 2017.
    • Yonghong Yu, Hao Wang, Shuanzhu Sun, and Yang Gao, "Exploiting location significance and user authority for point-of-interest recommendation," in: 21st Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Jeju, South Korea, May 2017.
    • Ngai Meng Kou, Yan Li, Hao Wang, Leong Hou U, and Zhiguo Gong, "Crowdsourced top-k queries by confidence-aware pairwise judgments," in: 2017 ACM SIGMOD International Conference on Management of Data (SIGMOD), Chicago, US, May 2017.
    • Huihui Wang, Yang Gao, Yinghuan Shi, and Hao Wang, "A fast distributed classification algorithm for large-scale imbalanced data," in: 2016 IEEE International Conference on Data Mining (ICDM), Barcelona, Spain, December 2016.
    • Chenyu Zhang, Hao Wang, Shangdong Yang, and Yang Gao, "Incremental nonnegative matrix factorization based on matrix sketching and k-means clustering," in: 17th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), Yangzhou, Jiangsu, China, October 2016.
    • Jinhua Song, Yang Gao, Hao Wang, and Bo An, "Measuring the distance between finite Markov decision processes," in: 2016 International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Singapore, May 2016.
    • Shangdong Yang, Yang Gao, Bo An, Hao Wang, and Xingguo Chen, "Efficient average reward reinforcement learning using constant shifting values," in: 30th AAAI Conference on Artificial Intelligence (AAAI), Phoenix, Arizona, February 2016.
    • Ziyu Lu, Hao Wang, Nikos Mamoulis, Wenting Tu, and David W. Cheung, "Personalized location recommendation by aggregating multiple recommenders in diversity," in: 1st ACM RecSys Workshop on Location-Aware Recommendations (LocalRec) at the 9th ACM Conference on Recommender Systems (RecSys), Vienna, Austria, September 2015.
    • Wenbing Li, Yinghuan Shi, Wanqi Yang, Hao Wang, and Yang Gao, "Interactive image segmentation via cascaded metric learning," in: IEEE International Conference on Image Processing (ICIP), Québec City, Canada, September 2015.
    • Hao Wang, Nana Pan, Leong Hou U, Bohan Zhan, and Zhiguo Gong, "On dynamic top-k influence maximization," in: 16th International Conference on Web-Age Information Management (WAIM), Qingdao, Shandong, China, June 2015. [poster]
    • Hao Wang, Manolis Terrovitis, and Nikos Mamoulis, "Location recommendation in location-based social networks using user check-in data," in: 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (GIS), Orlando, Florida, November 2013. [code]
    • Xingguo Chen, Hao Wang, Weiwei Wang, Yinghuan Shi, and Yang Gao, "Apply ant colony optimization to Tetris," in: 2009 Genetic and Evolutionary Computation Conference (GECCO), Montréal, Québec, Canada, July 2009.
    • Yang Gao, Hao Wang, and Ruili Wang, "The computation method for batch belief revision of autonomous agent," in: 3rd International Conference on Autonomous Robots and Agents (ICARA), Palmerston North, New Zealand, December 2006.

    Journal Articles

    • Ziyu Lu, Hao Wang, Nikos Mamoulis, Wenting Tu, and David W. Cheung, "Personalized location recommendation by aggregating multiple recommenders in diversity," GeoInformatica, accepted, 2017.
    • Tingting Zhai, Yang Gao, Hao Wang, and Longbing Cao, "Classification of high-dimensional evolving data streams via a resource-efficient online ensemble," Data Mining and Knowledge Discovery (DAMI), accepted, 2017.
    • Yonghong Yu, Can Wang, Hao Wang, and Yang Gao, "Attributes coupling based matrix factorization for item recommendation," Applied Intelligence, DOI: 10.1007/s10489-016-0841-8, 2016.
    • Hao Wang, Shunguo Fan, Jinhua Song, Yang Gao, and Xingguo Chen, "Reinforcement learning transfer based on subgoal discovery and subtask similarity," IEEE/CAA Journal of Acta Automatica Sinica, 1(3): 257-266, 2014.
    • Hao Wang, Yilun Cai, Yin Yang, Shiming Zhang, and Nikos Mamoulis, "Durable queries over historical time series," IEEE Transactions on Knowledge and Data Engineering (TKDE), 26(3): 595-607, 2014. [code]
    • Lili Diao, Chengzhong Yang, and Hao Wang, "Training SVM email classifiers using very large imbalanced dataset," Journal of Experimental and Theoretical Artificial Intelligence (JETAI), 24(2): 193-210, 2012.
    • Hao Wang, Yang Gao, and Xingguo Chen, "RL-DOT: a reinforcement learning NPC team for playing domination games," IEEE Transactions on Computational Intelligence and AI in Games (TCIAIG), 2(1): 17-26, 2010.
    • Hao Wang, Yang Gao, and Xingguo Chen, "Transfer of reinforcement learning: the state of the art," Acta Electronica Sinica, 36(12A): 39-43, 2008. (in Chinese)
    • Hao Wang, Wenjie Luo, Yang Gao, and Fanzhang Li, "An agent-based intelligent game platform and the design of its NPCs," Computer Science, 34(9A): 66-69, 2007. (in Chinese)
    • Yang Gao, Ruyi Zhou, Hao Wang, and Zhixin Cao, "Study on an average reward reinforcement learning algorithm," Chinese Journal of Computers, 30(8): 1372-1378, 2007. (in Chinese)
    • Hao Wang, and Yang Gao, "Meta-equilibria and MetaQ algorithm for multi-agent reinforcement learning," Journal of Computer Research and Development, 43(Suppl.): 137-141, 2006. (in Chinese)

    Book Chapters

    • Yang Gao, Hao Wang, and Ruili Wang, "Three perspectives on multi-agent reinforcement learning," book chapter in: Architectural Design of Multi-Agent Systems: Technologies and Techniques, Hong Lin (Ed.), IGI Global, pp:234-246, 2007.

    Thesis / Dissertation