Education

• PhD, The University of Texas at Dallas (2021) 
• MS, University of Albany – State University of New York (2016) 
• MS, Albany Medical College (2016) 

Contact Info:

Email: Chen_Zhao@baylor.edu
Phone: (254) 710-6896

Google Scholar

Research Interests

• Fairness-Aware Machine Learning 
• Uncertainty Quantification 
• Domain Generalization 
• Graph Learning 
• Causal Learning and Structural Causal Mechanisms 

Research Focus

• Dr. Zhao’s research focuses on machine learning, data mining, and artificial intelligence, particularly fairness-aware machine learning, novelty detection, and domain generalization. His publications have appeared in prestigious conferences and journals including KDD, CVPR, WWW, AAAI, CIKM, ICDM, ICASSP, etc. He has served as PC members for several international conferences and workshops, such as NeurIPS, KDD, AAAI, IJCAI, ICML, etc. 

Selected Publications

• Yujie Lin, Chen Zhao, Minglai Shao, Xujiang Zhao and Haifeng Chen. Adaptation Speed Analysis for Fairness-aware Causal Models. In Proceedings of the ACM International Conference on Information and Knowledge Management (full paper, oral), 2023 
• Dong Li, Wenjun Wang, Minglai Shao, Chen Zhao. Contrastive Representation Learning Based on Multiple Node-centered Subgraphs. In Proceedings of the ACM International Conference on Information and Knowledge Management (full paper, oral), 2023 
• Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Christan Earl Grant, Feng Chen. Towards Fair Disentangled Online Learning for Changing Environments. In Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (research track), 2023 
• Chen Zhao, Dawei Du, Anthony Hoogs, Christopher Funk. Open Set Action Recognition via Multi-Label Evidential Learning. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023 
• Xujiang Zhao, Xuchao Zhang, Chen Zhao, Jin-Hee Cho, Lance Kaplan, Dong Hyun Jeong, Audun Jøsang, Haifeng Chen, Feng Chen. Multi-Label Temporal Evidential Neural Networks for Early Event Detection. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, 2023 
• Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Feng Chen. Adaptive Fairness-Aware Online Meta-Learning for Changing Environments. In Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (research track), 2022 
• Haoliang Wang, Chen Zhao, Xujiang Zhao, Feng Chen. Layer Adaptive Deep Neural Networks for Out-of-distribution Detection. In Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2022 
• Krishnateja Killamsetty, Changbin Li, Chen Zhao, Rishabh Krishnan Iyer, Feng Chen. A Nested Bi-level Optimization Framework for Robust Few-Shot Learning. In Proceedings of the AAAI Conference on Artificial Intelligence, 2022 
• Chen Zhao, Feng Chen, Bhavani Thuraisingham. Fairness-Aware Online Meta-learning. In Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (research track), 2021