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      王鵬飛
      王鵬飛
      碩士生導(dǎo)師
      崗位:副研究員
      職務(wù):
      所屬部門:大數(shù)據(jù)技術(shù)與應(yīng)用發(fā)展部
      學(xué)歷:博士研究生
      郵箱:pfwang@cnic.cn
      通訊地址:
      學(xué)科專業(yè)(學(xué)術(shù)型/專業(yè)型):計(jì)算機(jī)應(yīng)用技術(shù)/計(jì)算機(jī)技術(shù) 
      招生方向:
      時(shí)空數(shù)據(jù)挖掘、圖網(wǎng)絡(luò)模型、強(qiáng)化學(xué)習(xí)
      承擔(dān)科研項(xiàng)目等情況
      參與科學(xué)大數(shù)據(jù)工程(十三五信息化專項(xiàng))、科學(xué)大數(shù)據(jù)管理系統(tǒng)(國(guó)家重點(diǎn)研發(fā)計(jì)劃)及多個(gè)政企合作項(xiàng)目,致力于應(yīng)用牽引的學(xué)術(shù)落地,在ACM KDD,IEEE ICDM等國(guó)際會(huì)議、期刊發(fā)表多篇論文,為學(xué)術(shù)頂級(jí)會(huì)議KDD,WWW,IJCAI,AAAI等審稿人。
      代表論著

      1. Pengfei Wang, Yanjie Fu, et, al. Human Mobility Synchronization and Trip Purpose Detection with Mixture of Hawkes Processes.  In Proceedings of the 23th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2017, KDD'17, 495-503.

      2. Pengfei Wang, Guannan Liu, Yanjie Fu, Yuanchun Zhou and Jianhui Li. Spotting trip purposes from taxi trajectories: A general probabilistic model[J]. ACM Transactions on Intelligent Systems and Technology (TIST), 2017, 9(3): 1-26.

      3. Pengfei Wang, Kunpeng Liu, et al. Unifying Human Mobility Forecasting and Trajectory Semantics Augmentation via Hawkes Process Based LSTM. Proceedings of the 2022 SIAM International Conference on Data Mining (SIAM SDM), 2022, 711-719.

      4. Kunpeng Liu, Pengfei Wang*, et al. Efficient Reinforced Feature Selection via Early Stopping Traverse Strategy. IEEE International Conference on Data Mining (ICDM). IEEE, 2021: 399-408.

      5. Pengyang Wang, Yanjie Fu, Jiawei Zhang, Pengfei Wang, et al. You Are How You Drive: Peer and Temporal-Aware Representation Learning for Driving Behavior Analysis. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining,2018, KDD'18, 2457-2466.

      6. Wenjuan Cui, Pengfei Wang, et al. An algorithm for event detection based on social media data. Neurocomputing.

      7. Kunpeng Liu, Yanjie Fu, Pengfei Wang, et al. Automating Feature Subspace Exploration via Multi-Agent Reinforcement Learning. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2019, KDD'19, 207-215.

      8. Xin Guo, Zhengxu Yu, Pengfei Wang, et al. Urban Traffic Light Control via Active Multi-agent Communication and Supply-Demand Modeling. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021.