Chen Zhao (赵辰)

Assistant Professor
Department of Computer Science
School of Engineering and Computer Science
Baylor University
One Bear Place #97141, Waco, Texas 76798, United States

Adjunct Professor
Department of Information Sciences and Technology
College of Emergency Preparedness, Homeland Security & Cybersecurity
The State University of New York at Albany
1400 Washington Ave, Albany, New York 12222, United States

Email: chen_zhao [at] baylor [dot] edu

News []

• [09/2026] Two papers are accepted by NeurIPS 2026.
• [08/2026] I will serve as a reviewer for ICLR 2027.
• [08/2026] Two papers are accepted by ICDM 2026.
• [07/2026] I will serve as an AC for AAAI 2027.
• [07/2026] I will serve as an AC for WSDM 2027.
• [07/2026] I will serve as an AC for KDD 2027 (Research track).
• [06/2026] I will serve as an AC for KDD 2027 (AI4Sciences track).
• [06/2026] I will serve as a reviewer for AAAI 2027.
• [06/2026] One paper is accepted by Briefings in Bioinformatics.
• [06/2026] One paper is accepted by ACM Computing Surveys.
• [05/2026] One paper is accepted by KAIS.
• [05/2026] One tutorial is accepted by KDD 2026.
• [04/2026] Three papers are accepted by IJCAI 2026.
• [04/2026] I will serve as a reviewer for ICDM 2026.
• [04/2026] I will serve as a panelist for NSF.
• [04/2026] I will serve as a panelist for NASA.
• [04/2026] One paper is accepted by ACL 2026 (main conference).
• [03/2026] I will serve as a reviewer for CIKM 2026.
• [03/2026] I will serve as a reviewer for NeurIPS 2026.
• [03/2026] I will serve as a panelist for NSF.
• [02/2026] I will serve as the PhD Forum Chair for IEEE BigData 2026.
• [02/2026] I will serve as a PC member for ACM MM 2026.
• [02/2026] I will serve as an AC for KDD 2026 (Research track).
• [02/2026] I will serve as an AC for KDD 2026 (AI4Sciences track).
• [01/2026] I will serve as a reviewer for ECML-PKDD 2026.
• [01/2026] I will serve as the editor of the International Journal of Data Science and Analytics
• [01/2026] One paper is accepted by ICASSP 2026.
• [01/2026] One paper is accepted by WWW 2026.
• [01/2026] I will serve as a reviewer for IJCNN 2026.
• [01/2026] I will serve as a reviewer for ACL ARR 2026.
• [01/2026] I received a Gift Fund from NEC Laboratories America.

Biography

I am an Assistant Professor in the Department of Computer Science at Baylor University. Prior to joining Baylor, I was a senior R&D computer vision engineer at Kitware Inc. I earned my Ph.D. degree in Computer Science from the University of Texas at Dallas (UTD) in 2021, advised by Feng Chen. I received dual M.S. degrees in Computer Science and Biomedical Science from the State University of New York at Albany (UAlbany), and Albany Medical College in 2016. My publications have appeared in prestigious conferences and journals, including NeurIPS, KDD, CVPR, WWW, AAAI, IJCAI, ACL, ACM Computing Surveys, TMLR, TKDD, KAIS, KBS, BIB, etc. I have served as an Area Chair and PC member (Reviewer) for several international conferences and workshops, such as NeurIPS, KDD, AAAI, ICML, ICLR, etc.

Education

• Ph.D. (Computer Science), The University of Texas at Dallas, 2021.
• M.S. (Computer Science), The State University of New York at Albany, 2016.
• M.S. (Biomedical Science), Albany Medical College, 2016.

Selected Publications

For a full list of publications, see Publications.

• [NeurIPS'26] ColdDDI: Evaluating Knowledge Utilization in Cold-Start Drug-Drug Interaction Prediction.
  Jiheng Liang, Chen Zhao, Di Wu, Chenyang Bu, Yunpeng Hong, Xingquan Zhu, Yi He.
  In Proceedings of the 40th Annual Conference on Neural Information Processing Systems, 2026
• [NeurIPS'26] HierFlow: Hierarchical Coupled Dual-Space Search for Automatic Agentic Workflow Generation.
  Dong Li, Yanchi Liu, Xujiang Zhao, Wei Cheng, Zhengzhang Chen, Xintao Wu, Zhong Chen, Chen Zhao, Haifeng Chen.
  In Proceedings of the 40th Annual Conference on Neural Information Processing Systems, 2026
• [ACM Computing Surveys] A Survey of AI for Materials Science: Foundation Models, LLM Agents, Datasets, and Tools.
  Minh-Hao Van, Prateek Verma, Chen Zhao, Xintao Wu.
  ACM Computing Surveys, 2026
• [IJCAI'26] PURE: Purging Unrelated Representations for Content-Agnostic Forgery Detection.
  Xinyu Wu, Dong Li, Minglai Shao, Xintao Wu, Zhong Chen, Chen Zhao.
  In Proceedings of the 35th International Joint Conference on Artificial Intelligence, 2026
• [IJCAI'26] LEMD: Latent Environment Extrapolation and Message Disentanglement for Dynamic Graph under Distribution Shift.
  Xiaoran Wei, Chen Zhao, Minglai Shao, Xintao Wu, Zhong Chen, Wenjun Wang, Qin Tian, Chang Liu.
  In Proceedings of the 35th International Joint Conference on Artificial Intelligence, 2026
• [IJCAI'26] Property Prediction of Stacked Bilayer Materials: A Multimodal Learning Approach.
  An Vuong, Minh-Hao Van, Chen Zhao, Xintao Wu.
  In Proceedings of the 35th International Joint Conference on Artificial Intelligence, 2026
• [ACL'26] Uncertainty-Aware Test-Time Search for Optimization Problem Solving.
  Linlin Yu, Xujiang Zhao, Dong Li, Yanchi Liu, Wei Cheng, Zhengzhang Chen, Chen Zhao, Feng Chen, Haifeng Chen.
  In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics, 2026
• [WWW'26] Class-Domain Incremental Learning on Graphs via Disentangled Knowledge Distillation.
  Qin Tian, Chen Zhao, Xintao Wu, Dong Li, Minglai Shao, Xujiang Zhao, Wenjun Wang
  In Proceedings of the Web Conference, 2026
• [AAAI'26] SkillGen: Learning Domain Skills for In-Context Sequential Decision Making.
  Ruomeng Ding, Wei Cheng, Minglai Shao, Chen Zhao
  In Proceedings of the AAAI Conference on Artificial Intelligence (Oral), 2026
• [AAAI'26] Out-of-Distribution Detection with Positive and Negative Prompt Supervision Using Large Language Models.
  Zhixia He, Chen Zhao, Minglai Shao, Xintao Wu, Xujiang Zhao, Dong Li, Qin Tian, Linlin Yu
  In Proceedings of the AAAI Conference on Artificial Intelligence (Poster), 2026
• [AAAI'26] MARLIN: Multi-Agent Reinforcement Learning for Incremental DAG Discovery.
  Dong Li, Zhengzhang Chen, Xujiang Zhao, Linlin Yu, Zhong Chen, Yi He, Haifeng Chen, Chen Zhao
  In Proceedings of the AAAI Conference on Artificial Intelligence (Poster), 2026
• [AAAI'26] LLM-Enhanced Energy Contrastive Learning for Out-of-Distribution Detection in Text-Attributed Graphs.
  Xiaoxu Ma, Dong Li, Minglai Shao, Xintao Wu, Chen Zhao
  In Proceedings of the AAAI Conference on Artificial Intelligence (Poster), 2026
• [NeurIPS'25] SolverLLM: Leveraging Test-Time Scaling for Optimization Problem via LLM-Guided Search.
  Dong Li, Xujiang Zhao, Linlin Yu, Yanchi Liu, Wei Cheng, Zhengzhang Chen, Zhong Chen, Feng Chen, Chen Zhao, Haifeng Chen.
  In Proceedings of the 39th Annual Conference on Neural Information Processing Systems, 2025
• [ACL'25] Uncertainty Propagation on LLM Agent.
  Qiwei Zhao^*, Dong Li^*, Yanchi Liu, Wei Cheng, Yiyou Sun, Mika Oishi, Takao Osaki, Katsushi Matsuda, Huaxiu Yao, Chen Zhao, Haifeng Chen, Xujiang Zhao.
  In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics, 2025
• [IJCAI'25] FADE: Towards Fairness-aware Data Generation for Domain Generalization via Classifier-Guided Score-based Diffusion Models.
  Yujie Lin^*, Dong Li^*, Minglai Shao, Guihong Wan, Chen Zhao.
  In Proceedings of the 34th International Joint Conference on Artificial Intelligence, 2025
• [IJCAI'25] A Novel Sparse Active Online Learning Framework for Streaming Anomaly Detection in Open Feature Spaces.
  Zhong Chen, Yi He, Di Wu, Chen Zhao, Meikang Qiu.
  In Proceedings of the 34th International Joint Conference on Artificial Intelligence, 2025
• [ICDE'25] Fairness-aware Active Online Learning with Changing Environments.
  Sadaf Md Halim, Chen Zhao, Xintao Wu, Latifur Khan, Christan Grant, Feng Chen.
  In Proceedings of the IEEE International Conference on Data Engineering, 2025
• [AAAI'25] Metric-Agnostic Continual Learning for Sustainable Group Fairness.
  Heng Lian, Chen Zhao, Zhong Chen, Xingquan Zhu, My T. Thai, Yi He
  In Proceedings of the AAAI Conference on Artificial Intelligence, 2025
• [AAAI'25] Multi-View Unsupervised Column Subset Selection via Combinatorial Search.
  Guihong Wan, Ninghui Hao, Crystal Maung, Haim Schweitzer, Chen Zhao, Kun-Hsing Yu, Yevgeniy Semenov
  In Proceedings of the AAAI Conference on Artificial Intelligence, 2025
• [KDD'25] MLDGG: Meta-Learning for Domain Generalization on Graphs.
  Qin Tian, Chen Zhao, Minglai Shao, Wenjun Wang, Yujie Lin, Dong Li
  In Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2025
• [KDD'24] Algorithmic Fairness Generalization under Covariate and Dependence Shifts Simultaneously.
  Chen Zhao^*, Kai Jiang^*, Xintao Wu, Haoliang Wang, Latifur Khan, Christan Earl Grant, Feng Chen.
  In Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024
• [IJCAI'24] Supervised Algorithmic Fairness in Distribution Shifts: A Survey.
  Minglai Shao^*, Dong Li^*, Chen Zhao^*, Xintao Wu, Yujie Lin, Qin Tian.
  In Proceedings of the 33rd International Joint Conference on Artificial Intelligence, 2024
• [IJCAI'24] Towards Counterfactual Fairness-aware Domain Generalization in Changing Environments.
  Yujie Lin, Chen Zhao, Minglai Shao, Baoluo Meng, Xujiang Zhao, Haifeng Chen.
  In Proceedings of the 33rd International Joint Conference on Artificial Intelligence, 2024
• [KDD'23] Towards Fair Disentangled Online Learning for Changing Environments.
  Chen Zhao^*, Feng Mi^*, Xintao Wu, Kai Jiang, Latifur Khan, Christan Earl Grant, Feng Chen.
  In Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
• [CVPR'23] Open Set Action Recognition via Multi-Label Evidential Learning.
  Chen Zhao, Dawei Du, Anthony Hoogs, Christopher Funk.
  In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
• [KDD'22] Adaptive Fairness-Aware Online Meta-Learning for Changing Environments.
  Chen Zhao^*, Feng Mi^*, Xintao Wu, Kai Jiang, Latifur Khan, Feng Chen.
  In Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2022
• [AAAI'22] A Nested Bi-level Optimization Framework for Robust Few-Shot Learning.
  Krishnateja Killamsetty, Changbin Li, Chen Zhao, Rishabh Krishnan Iyer, Feng Chen.
  In Proceedings of the AAAI Conference on Artificial Intelligence, 2022
• [KDD'21] Fairness-Aware Online Meta-learning.
  Chen Zhao, Feng Chen, Bhavani Thuraisingham.
  In Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021
• [WWW'21] CLEAR: Contrastive-Prototype Learning with Drift Estimation for Resource Constrained Stream Mining.
  Zhuoyi Wang, Yuqiao Chen, Chen Zhao, Hemeng Tao, Yu Lin, Xujiang Zhao, Yigong Wang and Latifur Khan.
  In Proceedings of the ACM International World Wide Web Conference, 2021

Research

I am generally interested in machine learning, data mining, trustworthy AI, and agentic AI, with a primary focus on

• Fairness-aware Machine Learning;
• Uncertainty Quantification;
• Distribution Shift and Domain Generalization;
• Graph Learning;
• Computational Biology;
• Large Language Models.

Awards & Honors

• Bronze Tier Reviewer. The International Joint Conference on Artificial Intelligence (IJCAI 2026).
• Gold Reviewer. The 43rd International Conference on Machine Learning (ICML 2026).
• PI, Research Fund (01/2026). NEC Laboratories America.
• Co-PI, National Science Foundation (NSF). “IUCRC Phase I Baylor University: Center for Responsible Artificial Intelligence and Governance (CRAIG)” [Certificate]. Duration: 10/2025 - 09/2030. $510,814.
• PI, Research Fund (05/2025). NEC Laboratories America.
• Outstanding Reviewer. The 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2025).
• Co-PI, Schmidt Sciences, AI2050 Early Career Fellowship. "Exploring Analogical Reasoning through Iconicity in Sign Language and Gestures". Duration: 03/2024 - 12/2026. $33,614.
• Dissertation Research Award. The University of Texas at Dallas, 2021-2022.
• Student Travel Award. IEEE International Conference on Data Mining (ICDM), U.S. National Science Foundation, 2020.
• First Prize in the 11th "Challenge Cup" National Undergraduate Academic Science and Technology. Tianjin Municipal Education Commission, Top 5% among all works in Tianjin City, 2011.

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