The 4th Workshop on Ethical Artificial Intelligence: Methods and Applications
(held in conjunction with ACM SIGKDD’25)
August 3, 2025, Toronto, ON, Canada
(held in conjunction with ACM SIGKDD’25)
August 3, 2025, Toronto, ON, Canada
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Chen Zhao, Baylor University. Short bio: Dr. Zhao is an Assistant Professor in the Department of Computer Science at Baylor University. His research focuses on machine learning, data mining, and artificial intelligence, particularly fairness-aware machine learning, novelty detection, domain generalization, and computational biology. His publications have been accepted and published in premier conferences, including KDD, CVPR, IJCAI, AAAI, WWW, etc. Dr. Zhao served as a PC member of top international conferences, such as KDD, NeurIPS, IJCAI, ICML, AAAI, ICLR, etc. He has organized and chaired multiple workshops on topics of Ethical AI, Uncertainty Quantification, Distribution Shifts, and Trustworthy AI for Healthcare at KDD (2022, 2023, 2024), AAAI (2023), IEEE BigData (2024), and SDM (2025). He serves as the chair of the Challenge Cup of the IEEE Bigdata 2024 conference, the tutorial chair for the PAKDD 2025 and the ICDM 2025 conferences, and the workshop chair for the IEEE Bigdata 2025 conference. |
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Feng Chen, The University of Texas at Dallas Short bio: Dr. Chen is an Associate Professor in Computer Science at the University of Texas at Dallas. His research has been funded by NSF, NIH, ARO, IARPA, and the U.S. Department of Transportation and published in more than 100 peer-reviewed papers in premier conferences, such as KDD, ICDM, WWW, CIKM, AAAI, IJCAI, ICML, and NeurIPS, and top journals, such as TKDD, TKDE, TIST, KAIS, and Proceedings of the IEEE. He received the NSF CAREER award in 2018 and the medium NSF award entitled “MUDL: Multidimensional Uncertainty-Aware Deep Learning Framework” in 2021 as the lead principal investigator (PI). |
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Xintao Wu, University of Arkansas Short bio: Dr. Wu is a Professor and the Charles D. Morgan/Acxiom Endowed Graduate Research Chair and leads the Social Awareness and Intelligent Learning (SAIL) Lab in the Electrical Engineering and Computer Science Department at the University of Arkansas. Dr. Wu is an associate editor or editorial board member of several journals and program committees as area chair, senior PC, and PC of top international conferences. He has served as the program co-chair of the ACM EAI-KDD workshops (2022-204), IEEE BigData'2022, IEEE ICMLA'2024, and PAKDD'2025. He also gave multiple tutorials on causality-based ethical AI at top international conferences, including ACM KDD and IEEE BigData. |
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Haifeng Chen, NEC Laboratories America. Short bio: Dr. Haifeng Chen is heading the Data Science and Systems Security Department at NEC Laboratories America. Haifeng has served on the program committee for several top conferences, such as SigKDD and AAAI, and has been on the panel of NSF programs. He has co-authored more than a hundred conference/journal publications, including best papers from top conferences such as SigKDD, and has over 60 patents. Most research results have led to advanced solutions and products for various industrial domains, including IT & data centers, network security, power plants, petroleum, satellite, natural disaster, finance, and retail businesses. In recognition of his extraordinary research contribution, Haifeng has received many awards in the past years, including the 2014 “NEC Contributors of the Year.” |
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Bingzhe Li, The University of Texas at Dallas. Short bio: Dr. Li is currently an Assistant Professor in the Department of Computer Science at the University of Texas at Dallas. His research interests focus on memory and storage systems, DNA storage, systems for machine learning, and low-cost computing architecture. He has authored and co-authored more than 35 research articles in refereed international conferences and premier journals, including USENIX FAST, ASPLOS, HPCA, SIGMOD, ACM Systor, DAC, ICCAD, ICCD, ISPA, HotStorage, FPGA, IEEE Transactions (TC, T-ED), ACM Journals/Transactions (TECS, TOS, TOMPECS, JETC), etc. He has served as conference organization committees, technical program committees, reviewers for several major conferences and journals in computer system, storage, and computing architecture including ICCD, DAC, IISWC, etc. In recognition of his research, he received the Best Paper Nomination at the ICCD’21 and the featured paper of the Month at IEEE Transactions of Computers on March 2021. |
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Hang Liu, Rutgers University. Short bio: Dr. Liu is an Assistant Professor and Associate Undergraduate Director of Electrical and Computer Engineering at Rutgers, the State University of New Jersey. His research exploits emerging hardware — such as Graphics Processing Unit (GPU), Field-Programmable Gate Array (FPGA), high-end CPU, and Solid-State Drive (SSD) — to build high-performance systems for graph computing, machine learning, computational omics, numerical simulation, and cloud computing. He has received the prestigious NSF CAREER award, IEEE CS TCHPC Early Career Researchers Award for Excellence in High Performance Computing – 2022, the Best Dissertation Award of Electrical and Computer Engineering from George Washington University, the Champion of GraphChallenge 2018 and 2019, the Lawrence Berkeley National Laboratory SRP fellowship 2019 and 2021, One of the best papers in VLDB '20, and Provost Early Career Award for Research Excellence 2022. |
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Qiannan Li, University of California, Davis. Short bio: Dr. Li is an Assistant Professor in the Department of Philosophy at the University of California, Davis. She obtained her Ph.D. degree at the University of Minnesota, advised by Prof. Valerie Tiberius. Her research focuses on normative ethics, philosophy of well-being, moral psychology, and comparative study between early Chinese philosophy and Western philosophy. |