Recent news

Updates might not be frequent due to various commitments, but I will share exciting developments and news as they come. Stay tuned!

  • [07/14/2025] We are honored to announce that our paper "Causally Fair Node Classification on Non-IID Graph Data" has received the Best Paper Award at the 4th Workshop on Ethical Artificial Intelligence: Methods and Applications (co-located with ACM SIGKDD'25). We look forward to presenting our work and connecting with the community at KDD!
  • [01/07/2025] Received two NSF National AI Research Resource (NAIRR) Pilot awards to support the research and education in trustworthy AI. NAIRR Pilot.
  • [01/05/2025] Awarded a $96k grant from TraCr to advance research in AI fairness and security for transportation systems.
  • [09/01/2024] Received a major grant ($758k) from VIPR-GS to develop Hyperspectral AI technologies for next-generation autonomous vehicles!
  • [05/15/2024] Awarded a research grant ($60k) from SC EPSCoR to advance Causal AI applications in precision healthcare and medical decision-making!
  • [07/12/2023] One paper entitled "AI-Cybersecurity Education Through Designing AI-based Cyberharassment Detection Lab." is accepted by the 2023 IEEE ASEE Frontiers in Education Conference.
  • [06/13/2023] I was invited as a postsecondary expert to support SC K12 teachers to incorporate AI into their classroom.
  • [04/07/2023] Two papers on causality and fairness are accepted by IJCNN 2023.
  • [03/10/2023] One project entitled "Detecting and mitigating AI bias in automated medical diagnosis" has been funded by the Prisma Health Seed program.
  • [02/22/2023] One paper entitled "Achieving Counterfactual Fairness for Anomaly Detection" by Xiao Han, Lu Zhang, Yongkai Wu, and Shuhan Yuan has been accepted by PAKDD 2023.
  • [11/15/2022] Two papers entitled "Fair Collective Classification in Networked Data" by Karuna Bhaila, Yongkai Wu, and Xintao Wu and and "SCM-VAE: Learning Identifiable Causal Representations via Structural Knowledge" by Aneesh Komanduri, Yongkai Wu, Wen Huang, Feng Chen, and Xintao Wu have been accepted by IEEE Big Data Conference.
  • [05/27/2021] The collaborative project entitled "Learning Platform and Education Curriculum for Artificial Intelligence-Driven Socially-Relevant Cybersecurity" among Clemson University (Long Cheng and Yongkai Wu), University at Buffalo and North Carolina A&T State University has been funded by NSF SaTC-Edu program.
  • [12/02/2020] One paper entitled "A Generative Adversarial Framework for Bounding Confounded Causal Effects" by Yaowei Hu, Yongkai Wu, Lu Zhang, and Xintao Wu has been accepted by AAAI 2021. AAAI 2021 received 9034 submissions and accepted approximately 1692 papers.
  • [09/25/2020] One paper entitled "Fair Multiple Decision Making through Soft Interventions" by Yaowei Hu, Yongkai Wu, Lu Zhang, and Xintao Wu has been accepted by NeurIPS 2020.
  • [07/17/2020] I will co-teach a fairness course at NSF Track 2 CRESH: Summer School on AI & Smart Health on July 21, 2020. More details can be found here.
  • [04/17/2020] I successfully defended the Ph.D. dissertation! Thanks to my committee and teammates!
  • [04/15/2020] One paper entitled "Multi-cause Discrimination Analysis Using Potential Outcomes" by Wen Huang, Yongkai Wu and Xintao Wu has been accepted by SBP-BRiMS 2020. Due to COVID-19, SBP-BRiMS plans to hold a virtual meeting.
  • [04/06/2020] I officially accept the Assistant Professor offer from the Department of Electrical and Computer Engineering at Clemson University, starting in August 2020.
  • [02/07/2020] One full paper entitled "Fairness through Equality of Effort" by Wen Huang, Yongkai Wu, Lu Zhang, and Xintao Wu has been accepted by FATES 2020 (the 2nd workshop on Fairness, Accountability, Ethics, and Society on the Web). FATES 2020 will be co-located with The Web Conference 2020 in Taipei, Taiwan, April 20-21, 2020.
  • [09/03/2019]: "PC-Fairness: A Unified Framework for Measuring Causality-based Fairness," authored by Yongkai Wu, Lu Zhang, Xintao Wu and Hanghang Tong, has been accepted for poster presentation at the 33rd Conference on Neural Information Processing Systems (NeurIPS), which will be held at Vancouver, Canada, Dec 8-14, 2019. This year, NeurIPS received a record-breaking 6743 submissions, of which 1428 were accepted (including 36 orals and 164 spotlights).
  • [05/10/2019]: Two papers, "Achieving Causal Fairness through Generative Adversarial Networks" and "Counterfactual Fairness: Unidentification, Bound and Algorithm.", have been accepted by IJCAI 2019, to be held at Macao, China, during August 10-16, 2019. This year, out of 4752 submissions, only 850 have been accepted.