Chen Zhao, Ph.D. (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 University at Albany - State University of New York 1400 Washington Ave, Albany, New York 12222, United States Email: chen[underscore]zhao[at]baylor[dot]edu

To Prospective Students: I am always looking for students with high motivations and strong coding skills to join my research group or work with me as summer interns. There are several RA openings for graduate students in my lab at Baylor University. These positions are supported by a monthly stipend and tuition waiver. Students are expected to work closely with me on several research projects. Applicants with a degree in related fields (e.g., CS/CE/EE/STAT) are preferred. Research backgrounds in machine learning, artificial intelligence, data mining, big data, and statistics are desired. If you are interested, please email me your application materials (e.g., Curriculum Vitae, Publications, GitHub/GitLab Accounts, Undergraduate/Graduate Transcripts, Personal Statement, and GRE/TOEFL Reports).
NOTE: Unfortunately, due to the volume of emails, I will not respond to all of them.

Biography

Dr. Chen Zhao is an Assistant Professor in the Department of Computer Science at Baylor University. Prior to joining Baylor, he was a senior R&D computer vision engineer at Kitware Inc. He earned his Ph.D. degree in Computer Science from the University of Texas at Dallas in 2021. He received dual M.S. degrees in Computer Science and Biomedical Science from University at Albany, SUNY and Albany Medical College in 2016.

His 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, ICDM, ICASSP, etc. He has served as a PC member for several international conferences and workshops, such as NeurIPS, KDD, AAAI, IJCAI, ICML, etc.

News []

• [11/2023] A recent work (fairness in domain generalization) has been uploaded to Arxiv (arXiv:2311.13816).
• [11/2023] I will serve as one of the Co-PIs for the Center on Responsible artificial intelligence and Governance (CRaiG), supported by the NSF IUCRC program.
• [11/2023] I will serve as one of the organizers for the 3rd Southwest Data Science Conference, 2024.
• [10/2023] I will serve as a reviewer for WWW 2024.
• [10/2023] I was invited to give an academic talk at the Data Science Seminar by Baylor University, Waco, TX.
• [10/2023] I will serve as a Program Committee for PAKDD 2024.
• [10/2023] I will serve as a reviewer for NeurIPS Worksop on Diffusion Models 2023.
• [09/2023] A recent work (counterfactual fairness in time series) has been uploaded to Arxiv (arXiv:2309.13005).
• [09/2023] A recent work (semantic OOD detection in unseen domains) has been uploaded to Arxiv (arXiv:2309.10209).
• [09/2023] I will serve as a reviewer for AAAI 2024.
• [09/2023] I will serve as a reviewer for ICASSP 2024.
• [09/2023] I will serve as a PC member for SDM 2024.
• [09/2023] I will serve as a reviewer for AISTATS 2024.
• [09/2023] I will serve as a reviewer for ICLR 2024.
• [08/2023] Two papers are accepted by CIKM 2023.
• [07/2023] I will serve as a Session Chair for the ADS track at KDD 2023.
• [07/2023] I will serve as a reviewer for TKDD 2023.
• [07/2023] I was invited to give an academic talk by AI TIME, Beijing, China.
• [05/2023] I will serve as a reviewer for the SPIGM workshop at ICML 2023.
• [05/2023] I was invited to give an academic talk by Yunnan University, Kunming, China.
• [05/2023] I was invited to give an academic talk by the Southwestern University of Finance and Economics, Chengdu, China.
• [05/2023] I was invited to give an academic talk by AI TIME, Beijing, China.
• [05/2023] One paper was accepted by KDD 2023.
• [05/2023] I will serve as a PC member for CIKM 2023.
• [04/2023] I will join Baylor University as a tenure-track Assistant Professor in the Department of Computer Science.
• [04/2023] I will serve as a reviewer for NeurIPS 2023.
• [04/2023] I was invited to give an academic talk by Indiana State University, Terre Haute, IN.
• [03/2023] I was invited to give an academic talk by SUNY at Albany, Albany, NY.
• [03/2023] I was invited to give an academic talk by Tennessee State University, Nashville, TN.
• [03/2023] Two workshop proposals were accepted by KDD 2023. I will serve as organizer and chair.
• [03/2023] I will serve as a PC member for IEEE Bigdata 2023.
• [02/2023] One paper was accepted by CVPR 2023.
• [02/2023] I will serve as a PC member for ICDM 2023.
• [02/2023] I will serve as a PC member for ECMLPKDD 2023.
• [02/2023] I was invited to give an academic talk by Baylor University, Waco, TX.
• [02/2023] One paper was accepted by ICASSP 2023.
• [02/2023] I was invited to give an academic talk by the University of Mississippi, Oxford, MS.
• [01/2023] I will serve as a PC member (applied data science track) for ACM SIGKDD 2023.
• [12/2022] I will serve as a PC member (research track) for ACM SIGKDD 2023.

Publications

2023

1. [ArXiv] Fairness-Aware Domain Generalization under Covariate and Dependence Shifts. PDF
   Chen Zhao, Kai Jiang, Xintao Wu, Haoliang Wang, Latifur Khan, Christan Grant, Feng Chen
   ArXiv preprint, 2311.13816, 2023
2. [ArXiv] Pursuing Counterfactual Fairness via Sequential Autoencoder Across Domains. PDF
   Yujie Lin, Chen Zhao, Minglai Shao, Baoluo Meng, Xujiang Zhao, Haifeng Chen
   ArXiv preprint, 2309.13005, 2023
3. [ArXiv] Towards Effective Semantic OOD Detection in Unseen Domains: A Domain Generalization Perspective. PDF
   Haoliang Wang, Chen Zhao, Yunhui Guo, Kai Jiang, Feng Chen
   ArXiv preprint, 2309.10209, 2023
4. [CIKM'23] Adaptation Speed Analysis for Fairness-aware Causal Models. PDF
   Yujie Lin, Chen Zhao, Minglai Shao, Xujiang Zhao and Haifeng Chen.
   In Proceedings of the ACM International Conference on Information and Knowledge Management (full paper), 2023
5. [CIKM'23] Contrastive Representation Learning Based on Multiple Node-centered Subgraphs. PDF
   Dong Li, Wenjun Wang, Minglai Shao, Chen Zhao.
   In Proceedings of the ACM International Conference on Information and Knowledge Management (full paper), 2023
6. [KDD'23] Towards Fair Disentangled Online Learning for Changing Environments. PDF
   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 (research track), 2023
7. [KDD'23-W] Learning Fair and Domain Generalization Representation.
   Dong Li, Chen Zhao, Minglai Shao, Xujiang Zhao
   KDD workshop on Ethical Artificial Intelligence: Methods and Applications (EAI), 2023
8. [KDD'23-W] Adaptation Speed of Causal Models Concerning Fairness.
   Yujie Lin, Chen Zhao, Minglai Shao, Xujiang Zhao, Haifeng Chen
   KDD workshop on Ethical Artificial Intelligence: Methods and Applications (EAI), 2023
9. [AAAI'23-W] Detecting Multi-Label Out-of-Distribution Nodes on Graphs.
   Ruomeng Ding, Xujiang Zhao, Chen Zhao, Minglai Shao
   AAAI workshop on Uncertainty Reasoning and Quantification in Decision Making (UDM), 2023
10. [CVPR'23] Open Set Action Recognition via Multi-Label Evidential Learning. PDF
    Chen Zhao, Dawei Du, Anthony Hoogs, Christopher Funk.
    In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
11. [ICASSP'23] Multi-Label Temporal Evidential Neural Networks for Early Event Detection. PDF
    Xujiang Zhao, Xuchao Zhang, Chen Zhao, Jin-Hee Cho, Lance Kaplan, Dong Hyun Jeong, Audun Jøsang, Haifeng Chen, Feng Chen
    In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, 2023
12. [ArXiv] An Automated Vulnerability Detection Framework for Smart Contracts. PDF
    Feng Mi, Chen Zhao, Zhuoyi Wang, Sadaf MD Halim, Xiaodi Li, Zhouxiang Wu, Latifur Khan, Bhavani Thuraisingham
    ArXiv preprint, 2301.08824, 2023

2022

1. [KDD'22] Adaptive Fairness-Aware Online Meta-Learning for Changing Environments. PDF
   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 (research track), 2022
2. [ArXiv] xFBD: Focused Building Damage Dataset and Analysis. PDF
   Dennis Melamed, Cameron Johnson, Chen Zhao, Russell Blue, Philip Morrone, Anthony Hoogs, Brian Clipp
   ArXiv preprint, 2212.13876, 2022
3. [PAKDD'22] Layer Adaptive Deep Neural Networks for Out-of-distribution Detection. PDF
   Haoliang Wang, Chen Zhao, Xujiang Zhao, Feng Chen
   In Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2022
4. [AAAI'22] A Nested Bi-level Optimization Framework for Robust Few-Shot Learning. PDF
   Krishnateja Killamsetty, Changbin Li, Chen Zhao, Rishabh Krishnan Iyer, Feng Chen
   In Proceedings of the AAAI Conference on Artificial Intelligence, 2022

2021

1. [KDD'21] Fairness-Aware Online Meta-learning. PDF
   Chen Zhao, Feng Chen, Bhavani Thuraisingham
   In Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (research track), 2021
2. [ICBC'21] VSCL: Automating Vulnerability Detection in Smart Contracts with Deep Learning. PDF
   Feng Mi, Zhuoyi Wang, Chen Zhao, Jinghui Guo, Fawaz Ahmed, Latifur Khan
   In Proceedings of the IEEE International Conference on Blockchain and Cryptocurrency, 2021
3. [NeurIPS’21-W] A Reweighted Meta Learning Framework for Robust Few Shot Learning.
   Krishnateja Killamsetty, Changbin Li, Chen Zhao, Rishabh Krishnan Iyer, Feng Chen
   NeurIPS Workshop on Meta-Learning (MetaLearn), 2021
4. [WWW'21] CLEAR: Contrastive-Prototype Learning with Drift Estimation for Resource Constrained Stream Mining. PDF
   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

2020

1. [ArXiv] PDFM: A Primal-Dual Fairness-Aware Framework for Meta-learning. PDF
   Chen Zhao, Feng Chen, Zhuoyi Wang, Latifur Khan
   ArXiv preprint, 2009.12675v2, 2020
2. [ICDM'20] A Primal-Dual Subgradient Approach for Fair Meta Learning. PDF
   Chen Zhao, Feng Chen, Zhuoyi Wang, Latifur Khan
   In Proceedings of the IEEE International Conference on Data Mining(full paper), 2020
3. [ICKG'20] Fair Meta-Learning for Few-Shot Classification. PDF
   Chen Zhao, Changbin Li, Jincheng Li, Feng Chen
   In Proceedings of the IEEE International Conference on Knowledge Graph, 2020
4. [ICKG'20] Unfairness Discovery and Prevention for Few-Shot Regression. PDF
   Chen Zhao, Feng Chen
   In Proceedings of the IEEE International Conference on Knowledge Graph, 2020

Before 2020

1. [ICDM'19] Rank-Based Multi-task Learning for Fair Regression. PDF
   Chen Zhao, Feng Chen
   In Proceedings of the IEEE International Conference on Data Mining(full paper), 2019
2. [Development'17] CDC42 is required for epicardial and pro-epicardial development by mediating FGF receptor trafficking to plasma membrane. PDF
   Jingjing Li, Lianjie Miao, Chen Zhao, Wasay Mohiuddin Shaikh Qureshi, David Shieh, Hua Guo, Yangyang Lu, Saiyang Hu, Alice Huang, Lu Zhang, Chen-leng Cai, Leo Q. Wan, Hongbo Xin, Peter Vincent, Harold A. Singer, Yi Zheng, Ondine Cleaver, Zhen-Chuan Fan, Mingfu Wu
   Development, 147-173, 2017
3. [Development'14] Numb family proteins are essential for cardiac morphogenesis and progenitor differentiation. PDF
   Chen Zhao, Hua Guo, Jingjing Li, Thomas Myint, William Pittman, Le Yang, Weimin Zhong, Robert J. Schwartz, John J. Schwarz, Harold A. Singer, Michelle D. Tallquist, Mingfu Wu
   Development, 141(2):281-95, 2014

Academic Services

Conference PC Member and Reviewer

• [PC Member] The Web Conference (WWW), 2024.
• [PC Member] Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2024.
• [PC Member] AAAI Conference on Artificial Intelligence (AAAI), 2022, 2024.
• [Reviewer] IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2024.
• [Reviewer] International Conference on Artificial Intelligence and Statistics (AISTATS), 2021, 2024.
• [PC Member] SIAM International Conference on Data Mining (SDM), 2022, 2024.
• [Reviewer] International Conference on Learning Representations (ICLR), 2024.
• [Reviewer] The Conference on Neural Information Processing Systems (NeurIPS), 2023.
• [PC Member on Research Track] ACM Conference on Knowledge Discovery and Data Mining (KDD), 2020-2023.
• [PC Member on Applied Science Track] ACM Conference on Knowledge Discovery and Data Mining (KDD), 2020-2023.
• [PC Member] European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2023.
• [PC Member] International Joint Conference on Artificial Intelligence (IJCAI), 2023.
• [Reviewer] IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2023.
• [PC Member] ACM International Conference on Information and Knowledge Management (CIKM), 2022-2023.
• [PC Member] IEEE International Conference on Big Data (BigData), 2021-2023.
• [PC Member] IEEE International Conference on Data Mining (ICDM), 2021-2023.
• [PC Member] AAAI Conference on Artificial Intelligence (AAAI), 2022.
• [PC Member] International Conference on Web Search and Data Mining (WSDM), 2022.
• [Reviewer] International Conference on Intelligent Computing (ICIC), 2023.
• [TPC Member] International Congress on Blockchain and Applications (BLOCKCHAIN), 2022.
• [PC Member] International Conference on Automated Machine Learning (AutoML), 2022.
• [TPC member] International Conference on Networks, Communication and Information Technology (NCIT), 2023.

Workshop Reviewer

• [Reviewer] NeurIPS Workshop on Diffusion Models, 2023.
• [Reviewer] ICML Workshop on Structured Probabilistic Inference & Generative Modeling (SPIGM), 2023.
• [Reviewer] WACV Workshop on Dealing with Novelty in Open Worlds, 2022-2023.
• [Reviewer] AutoML Workshop on Late-Breaking, 2022.
• [Reviewer] NeurIPS Workshop on Meta-Learning, 2021.

Journal Reviewer

• [Reviewer] Transactions on Knowledge Discovery from Data (TKDD), 2023.
• [Reviewer] Journal of Frontiers in Big Data, 2022-2023.
• [Reviewer] Journal of Knowledge-based Systems (KBS), 2022.
• [Reviewer] Journal of IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.
• [Reviewer] Journal of Springer Machine Learning (MACH), 2022.
• [Reviewer] Journal of IEEE Transactions on Software Engineering (TSE), 2022.
• [Reviewer] Environment and Planning B: Urban Analytics and City Science, 2022.
• [Reviewer] Journal of Big Data Research (JBDR), 2020.

Others

• [Orgnizer] The Southwest Data Science Conference, 2024.
• [Session Chair at ADS] ACM Conference on Knowledge Discovery and Data Mining (KDD), 2023.
• [Orgnizer, Chair] KDD Workshop on Uncertainty Reasoning and Quantification in Decision Making, 2023.
• [Orgnizer, Chair] AAAI Workshop on Uncertainty Reasoning and Quantification in Decision Making, 2023.
• [Orgnizer, Chair] KDD Workshop on Ethical Artificial Intelligence: Methods and Applications, 2022-2023.
• [Mentor at KDD-UC] ACM Conference on Knowledge Discovery and Data Mining (KDD), 2022.
• [Editorial Board Member] American Journal of Data Mining and Knowledge Discovery (AJDMKD), 2022-2024.

Academic Talks

Invited Talks

• 10/2023: Baylor University, Data Science Seminar, Waco TX, USA.
• 07/2023: AI TIME, Beijing, China.
• 05/2023: Yunnan University, School of Information Science and Engineering, Kunming, China.
• 05/2023: Southwestern University of Finance and Economics, School of Business Administration, Chengdu, China.
• 05/2023: AI TIME, Beijing, China.
• 04/2023: Indiana State University, Department of Electronics and Computer Engineering Technology, Terre Haute, IN, USA.
• 04/2023: SUNY at Albany, Department of Computer Science, Albany NY, USA.
• 03/2023: Tennessee State University, Department of Computer Science, Nashville TN, USA.
• 03/2023: Millersville University, Department of Computer Science, Millersville PA, USA.
• 03/2023: Baylor University, Department of Computer Science, Waco TX, USA.
• 02/2023: University of Mississippi, Department of Computer and Information Science, Oxford MS, USA.
• 01/2023: University of Alabama at Birmingham, Department of Computer Science, Birmingham AL, USA.
• 12/2022: University of Central Missouri, Department of Computer Science, Warrensburg CO, USA.
• 11/2022: East Carolina University, Department of Computer Science, Greenville NC, USA.
• 11/2022: The University of Texas at Dallas, Department of Computer Science, Richardson TX, USA.
• 10/2022: NEC America Laboratory, Data Science and System Security team, Princeton NJ, USA.
• 07/2022: AI TIME, Beijing, China.
• 05/2022: Tianjin University, Smart Society and Big Data Intelligence Lab, Tianjin, China.
• 11/2021: AI TIME, Beijing, China.
• 04/2015: Shaker High School, Latham NY, USA.

Others

• 08/2023: ACM Conference on Knowledge Discovery and Data Mining, Long Beach, California, USA (oral and poster).
• 06/2023: IEEE/CVF Conference on Computer Vision and Pattern Recognition, Vancouver, Canada (poster).
• 08/2022: ACM Conference on Knowledge Discovery and Data Mining, Washington D.C., USA (oral and poster).
• 08/2021: ACM Conference on Knowledge Discovery and Data Mining, Singapore (oral and poster).
• 11/2020: IEEE International Conference on Data Mining, Sorrento, Italy (oral).
• 08/2020: IEEE International Conference on Knowledge Graph, Nanjing, China (two oral talks).
• 11/2019: IEEE International Conference on Data Mining, Beijing, China (oral).
• 05/2015: Weinstein Cardiovascular Development Conference, Boston MA, USA (poster).
• 10/2013: North American Vascular Biology Organization (NAVBO) Conference, Hyannis MA, USA (poster).

Teaching

Baylor University

• Spring 2024, Instructor, DSC 4320 Data Visualization.
• Fall 2023, Instructor, DSC 2350 Discrete Structures for Data Science.

The State University of New York at Albany

• Fall 2023, Spring 2023, Spring 2022, Instructor, INF 108 Programming for Problem Solving.
• Spring 2024, Fall 2022, Spring 2022, Instructor, INF 428/528 Analysis, Visualization, and Prediction in Analytics.
• Spring 2019, Fall 2018, Spring 2018, Teaching Assistant, ICSI 500 Operating Systems.
• Fall 2017, Teaching Assistant, ICSI 518 Software Engineering.
• Fall 2016, Spring 2016, Fall 2015, Teaching Assistant, ICSI 201 Introduction of Computer Science.

The University of Texas at Dallas

• Summer 2021, Teaching Assistant, CS 6385 Algorithmic Aspects of Telecommunication Networks.
• Summer 2021, Teaching Assistant, CS 4365 Artificial Intelligence.
• Summer 2021, Lab Instructor, CS 1136 Computer Science Laboratory.
• Fall 2019, Co-Instructor, CS 6364 Artificial Intelligence.
• Fall 2019, Teaching Assistant, CS 6301 Convolutional Neural Network.

Albany Medical College

• Spring 2015, Spring 2014, Teaching Assistant, MCP 608 Cardiovascular Physiology.
• Spring 2015, Spring 2014, Teaching Assistant, MCP 609 Respiratory & Renal Physiology.

Awards & Honors

• Dissertation Research Award, $1,224, 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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Last Updated on August, 2023 Published with GitHub Pages