About Me

Peng Han is currently a Ph.D. candidate in Computer Science, at the King Abdullah University of Science and Technology (KAUST), Saudi Arabia. He is under the supervision of Prof. Xiangliang Zhang. Prior to that, he was a Research Associate in the School of Computer Science and Engineering, Nanyang Technological University (NTU) under the supervision of Prof. Aixin Sun, Singapore. He received his M.E. in Computer Science from Renmin University of China (RUC) at BDAI lab (leaded by Prof. Ji-rong Wen) in 2017.

Competition Award

• IJCAI-Alibaba Competation 2015
• Predicted purchasers’ desire to purchase commodity via computer modeling;
• Our team outstood as the 4th place among 753 teams from 258 colleges and 28 countries.
• ImagNet Competition 2015 [Team Leader]
• Our team was awarded 2nd place in the Object Detection from Video.

Publications [Google Citations]

1. A Graph-based Approach for Trajectory Similarity Computation in Spatial Networks
   Peng Han, Jin Wang, Di Yao, Shuo Shang, Xiangliang Zhang
   KDD-2021The 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining
2. Point-of-interest recommendation with global and local context
   Peng Han, Shuo Shang, Aixin Sun, Peilin Zhao, Kai Zheng, Xiangliang Zhang
   TKDE-2021IEEE Transactions on Knowledge and Data Engineering
3. Detecting thoracic diseases via representation learning with adaptive sampling
   Hao Wang, Yuan-Yuan Yang, Yang Pan, Peng Han, Zhong-Xiao Li, He-Guang Huang, Shun-Zhi Zhu
   Neurocomputing-2020Neurocomputing
4. Contextualized Point-of-Interest Recommendation
   Peng Han, Zhongxiao Li, Yong Liu, Peilin Zhao, Jing Li, Hao Wang, Shuo Shang
   IJCAI-2020TThe 29th International Joint Conference on Artificial Intelligence
5. Learning Personalized Itemset Mapping for Cross-Domain Recommendation
   Yinan Zhang, Yong Liu, Peng Han, Chunyan Miao, Lizhen Cui, Baoli Li, Haihong Tang
   IJCAI-2020TThe 29th International Joint Conference on Artificial Intelligence
6. GCN-MF: Disease-Gene Association Identification By Graph Convolutional Networks and Matrix Factorization
   Peng Han, Peng Yang, Peilin Zhao, Shuo Shang, Yong Liu, Jiayu Zhou, Xin Gao, Panos Kalnis
   KDD-2019The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
7. AUC-MF: Point of Interest Recommendation with AUC Maximization
   Peng Han, Shuo Shang, Aixin Sun, Peilin Zhao, Kai Zheng, Panos Kalnis
   ICDE-2019IEEE 35th International Conference on Data Engineering
8. Graph-boosted convolutional neural networks for semantic segmentation
   Guangzhen Liu, Peng Han, Yulei Niu, Wenwu Yuan, Zhiwu Lu, Ji-Rong Wen
   IJCNN-2017International Joint Conference on Neural Networks
9. Large-scale sparse learning from noisy tags for semantic segmentation
   Aoxue Li, Zhiwu Lu, Liwei Wang, Peng Han, Ji-Rong Wen
   Cybernetics-2017IEEE Transactions on Cybernetics
10. Segmentation with Selectively Propagated Constraints
    Peng Han, Guangzhen Liu, Songfang Huang, Wenwu Yuan, Zhiwu Lu
    ICONIP-2016International Conference on Neural Information Processing
11. Learning from weak and noisy labels for semantic segmentation
    Zhiwu Lu, Zhenyong Fu, Tao Xiang, Peng Han, Liwei Wang, Xin Gao
    TPAMI-2016IEEE Transactions on Pattern Analysis and Machine Intelligence
12. Weakly supervised matrix factorization for noisily tagged image parsing
    Yulei Niu, Zhiwu Lu, Songfang Huang, Peng Han, Ji-Rong Wen
    IJCAI-2015TThe 24th International Joint Conference on Artificial Intelligence
13. Semantic sparse recoding of visual content for image applications
    Zhiwu Lu, Peng Han, Liwei Wang, Ji-Rong Wen
    TIP-2015IEEE Transactions on Image Processing

Professional Services

• Journal Reviewers
• IEEE Transactions on Knowledge and Data Engineering (TKDE)
• Elsevier, Neurocomputing
• IEEE Access