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Dr Hua Mao

Assistant Professor

School: Computer Science

Hua Mao

Research Themes and Scholarly Interests

Dr. Hua Mao has been an assistant professor in the Department of Computer and Information Sciences at Northumbria University since July 2019. Before that, she was with the School of Computer Science at Sichuan University, China. She worked as a Lecturer, followed by an Associate Professor from Jan. 2014 – Dec. 2018. Dr. Mao received her Ph.D. degree from Aalborg University, Denmark, in 2013. Her research interests include deep learning and AI. 

Key Publications

  • Please visit the Pure Research Information Portal for further information
  • Conditional Distribution Learning for Graph Classification, Chen, J., Mao, H., Liu, C., Wang, Z., Peng, X. 7 Nov 2026, The 40th Annual AAAI Conference on Artificial Intelligence
  • Cross-View Graph Consistency Learning for Invariant Graph Representations, Chen, J., Mao, H., Woo, W., Liu, C., Peng, X. 11 Apr 2025, Proceedings of the 39th Annual AAAI Conference on Artificial Intelligence, Washington, DC, United States, Association for the Advancement of Artificial Intelligence (AAAI)
  • DiPACE: Diverse, Plausible and Actionable Counterfactual Explanations, Sanderson, J., Mao, H., Woo, W. 25 Feb 2025, Proceedings of the 17th International Conference on Agents and Artificial Intelligence, Scitepress
  • Efficient algorithms for collecting the statistics of large-scale IP address data, Liu, H., Cao, Y., Cai, Z., Mao, H., Chen, J. 18 Jul 2025, In: Computer Science and Information Systems
  • GradCFA: A Hybrid Gradient-Based Counterfactual and Feature Attribution Explanation Algorithm for Local Interpretation of Neural Networks, Sanderson, J., Mao, H., Woo, W. 1 Oct 2025, In: IEEE Transactions on Artificial Intelligence
  • Hierarchical Sparse Representation Clustering for High-Dimensional Data Streams, Chen, J., Mao, H., Gou, Y., Peng, X. Oct 2025, In: IEEE Transactions on Neural Networks and Learning Systems
  • One-Step Adaptive Graph Learning for Incomplete Multiview Subspace Clustering, Chen, J., Mao, H., Woo, W., Liu, C., Wang, Z., Peng, X. 1 May 2025, In: IEEE Transactions on Knowledge and Data Engineering
  • Progressive Low-Confidence Pseudolabeling for Semisupervised Node Classification, Zhou, T., Mao, H., Liu, H., Chen, J. 1 Dec 2025, In: Neurocomputing
  • Deep Multiview Clustering by Contrasting Cluster Assignments, Chen, J., Mao, H., Woo, W., Peng, X. 15 Jan 2024, Proceedings of the 2023 IEEE/CVF International Conference on Computer Vision (ICCV), Piscataway, US, IEEE
  • Dynamic Graph Embedding via Meta-Learning, Mao, Y., Hao, Y., Cao, X., Fang, Y., Lin, X., Mao, H., Xu, Z. 1 Jul 2024, In: IEEE Transactions on Knowledge and Data Engineering

Current and Recent Projects

PGR Supervision

Jacob Sanderson Explainable Artificial Intelligence: Improving AI Interpretability through Advances in Counterfactual Explanations Start Date: 01/10/2023

Qualifications

Computing Science PhD June 30 2013

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