IEEE ICDM 2019, Beijing, China

I will be attending Institute of Electrical and Electronics Engineers International Conference on Data Mining 2019 at the China National Convention Center (CNCC), Beijing, China from November 8th to 11th, 2019.

  1. I will tentatively be the session chair for 1st IEEE ICDM Workshop on Deep Learning for Spatiotemporal Data, Algorithms, and Systems (DeepSpatial 2019) on November 8, 2019.
    ICDM Workshop on Deep Learning for Spatiotemporal Data, Algorithms, and Systems (DeepSpatial 2019)
    13:00-13:05 Welcome
    13:05-13:30 “Deep Learning Prediction of Incoming Rainfalls: An Operational Service for the City of Beijing China”
    Kuan Song, Guowei Yang, Qixun Wang, Chunmeng Xu, Jianzhong Liu, Wenjun Liu, Chen Shi, Ying Wang, Gong Zhang, Xiaochen Yu, Zhu Gu, and Wenpeng Zhang
    13:30-13:55 “Nearest-Neighbor Neural Networks for Geostatistics”Haoyu Wang, Yawen Guan, and Brian Reich
    13:30-13:55 Spatial Interpolation with Message Passing Framework
    Evgeniy Faerman, Manuel Rogalla, Niklas Strauß, Adrian Krüger, Benedict Blümel, Max Berrendorf, Michael Fromm, and Matthias Schubert
    13:30-13:55 Estimation of economic indicators using residual neural network ResNet50
    Peng Wu and Yumin Tan
    13:30-13:55 Paper 6: Spatiotemporal Attention Networks for Wind Power Forecasting
    Xingbo Fu, Feng Gao, Jiang Wu, Xinyu Wei, and Fangwei Duan
  2. I will give a presentation on my accepted work on Bank Stress Test Analytics.
    Session 20: Deep Learning and its Applications
    13:30pm-15:20pm, Nov. 10
    Room 301B
    DM1172 “Identifying High Potential Talent: A Neural Network based Dynamic Social Profiling Approach”
    Yuyang Ye, Hengshu Zhu, Tong Xu, Fuzhen Zhuang, Runlong Yu, and Hui Xiong
    DM1054 “Relation Structure-Aware Heterogeneous Graph Neural Network”
    Shichao Zhu, Chuan Zhou, Shirui Pan, Xingquan Zhu, and Bin Wang
    DM206 “Bi-Directional Causal Graph Learning through Low-rank Approximated Neural Network”
    Hao Huang, Chenxiao Xu, and Shinjae Yoo
    DM644 “An Integrated Multimodal Attention-Based Approach for Bank Stress Test Prediction”
    Farid Razzak, Fei Yi, Yang Yang, and Hui Xiong
  3. Also, I am the tentative session chair for Session 31: Semi-supervised & Active Learning on November 11th, 2019:
    Session 31: Semi-supervised & Active Learning
    13:30pm-16:00pm, Nov. 11
    Room 301B
    DM574 “Discriminative Regularized Deep Generative Models for Semi-Supervised Learning”
    Qianqian Xie, Min Peng, and HUA WANG
    DM767 “Collaborative Graph Walk for Semi-supervised Multi-Label Node Classification”
    Uchenna Akujuobi, Han Yufei, Qiannan Zhang, and Xiangliang Zhang
    DM1195 “Learning to Sample: an Active Learning Framework”
    Jingyu Shao, Qing Wang, and Fangbing Liu
    DM217 “Neural Embedding Propagation on Heterogeneous Networks”
    Carl Yang, Jieyu Zhang, and Jiawei Han
    DM1062 “A Semi-supervised Graph Attentive Network for Fraud Detection”
    Daixin Wang, Jianbin Lin, Peng Cui, Quanhui Jia, Zhen Wang, Yanming Fang, Quan Yu, Jun Zhou,
    Shuang Yang, and Qi Yuan
    DM1041 “A Factorized Version Space Algorithm for “Human-In-the-Loop” Data Exploration”
    Luciano Di Palma, Yanlei Diao, and Anna Liu
    DM1093 “Semi-supervised Adversarial Domain Adaptation for Seagrass Detection in Multispectral Images”
    Kazi Aminul Islam, Victoria Hill, Blake Schaeffer, Richard Zimmerman, and Jiang Li

More details of the conference schedule can be found at

Please join me if interested in discussing session papers, my research, networking for future collaborations, career ambitions, and faculty opportunities.

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#ieeecs #icdm #datamining  @icdm2019

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