I am a researcher working on data mining and machine learning, with a particular focus on computational behavior modeling. By leveraging the methodology of representation learning, I develop novel machine learning approaches for modeling the unique complementarity property of contextual behaviors and capturing their evolving temporal dynamics. I am currently an Applied Scientist on Amazon’s Product Graph team.

I hold a Ph.D. in Computer Science and Engineering from the University of Notre Dame. I was fortunate to be co-advised by Dr. Meng Jiang and Dr. Nitesh V. Chawla. Prior to ND, I received M.S. in Information Science from the University of Pittsburgh.

News

• 2022.6: One paper on graph learning was accepted to ICML 2022.
• 2022.4: One paper on complementarity learning was accepted to IEEE TNNLS.
• 2021.9: Joined Amazon as an Applied Scientist.

Recent Publications

• Tong Zhao, Gang Liu, Daheng Wang, Wenhao Yu and Meng Jiang. Learning from Counterfactual Links for Link Prediction. International Conference on Machine Learning (ICML), 2022.
• Daheng Wang, Tong Zhao, Wenhao Yu, Nitesh V. Chawla and Meng Jiang. Deep Multimodal Complementarity Learning. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022.
• Daheng Wang, Tong Zhao, Nitesh V. Chawla and Meng Jiang. Dynamic Attributed Graph Prediction with Conditional Normalizing Flows. IEEE International Conference on Data Mining (ICDM), 2021.
• Munira Syed, Daheng Wang, Meng Jiang, Oliver Conway, Vishal Juneja, Sriram Subramanian and Nitesh V. Chawla. Unified Representation of Twitter and Online News using Graph and Entities. Frontiers in Big Data, section Big Data Networks, 2021.
• Daheng Wang, Zhihan Zhang, Yihong Ma, Tong Zhao, Tianwen Jiang, Nitesh V. Chawla and Meng Jiang. Modeling Co-evolution of Attributed and Structural Information in Graph Sequence. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021.
• Daheng Wang, Tong Zhao, Nitesh V. Chawla and Meng Jiang. Evolutionary Graph Normalizing Flows. International Workshop on Deep Learning on Graphs: Methods and Applications (DLG) at ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2021.
• Daheng Wang, Qingkai Zeng, Nitesh V. Chawla and Meng Jiang. Modeling Complementarity in Behavior Data with Multi-Type Itemset Embedding. ACM Transactions on Intelligent Systems and Technology (TIST), 2021.
• Daheng Wang, Prashant Shiralkar, Colin Lockard, Binxuan Huang, Xin Luna Dong and Meng Jiang. TCN: Table Convolutional Network for Web Table Interpretation. The Web Conference (TheWebConf), 2021.

Service

• Conference SPC/PC/Reviewer: KDD, CIKM, WWW, WSDM, AAAI, IJCAI, etc.

• Journal Reviewer: TKDE, TKDD, DMKD, TOIS, TNNLS, etc.