Wang Ran, PhD, is a tenured associate professor, master's supervisor, and doctoral supervisor at Shenzhen University. She is a senior member of IEEE and a member of CAAI. She has received funding from the Guangdong Provincial Outstanding Youth Science Fund, is a Shenzhen Overseas High-Level Talent, and a recipient of the Shenzhen University "Liyuan Excellent Young Scientist" award. She graduated from City University of Hong Kong in February 2014 with her PhD and joined Shenzhen University in March 2016. Since 2009, she has been engaged in research on machine learning and pattern recognition, publishing numerous papers, leading 5 National Natural Science Foundation of China projects, and receiving over 4000 citations on Google Scholar. She has also received the Shenzhen Artificial Intelligence Natural Science Award, among other awards.
Email: wangran@szu.edu.cn
Recruitment Information: Recruiting master's and doctoral students in machine learning and pattern recognition. Applicants should have a solid theoretical foundation, strong programming skills, a strong interest in scientific research, and the ability to work diligently.
Research Interests: Uncertainty-based artificial intelligence, supervised learning, semi-supervised learning, active learning, multi-label classification, robust generalization research in deep learning, heuristic optimization.
Research Projects:
01/2026–12/2029 Research on Robust Generalization Relationship of Deep Learning from the Perspective of Distribution Misalignment (Principal Investigator, National Natural Science Foundation of China, General Program)
01/2022–12/2025 Research and Application of Adversarial Robustness of Deep Networks Based on Uncertainty Modeling (Principal Investigator, National Natural Science Foundation of China, General Program)
01/2018–12/2021 Research on Uncertainty Analysis and Active Learning Methods for Multi-Label Problems (Principal Investigator, National Natural Science Foundation of China, General Program)
04/2018–03/2020 Key Issues in Multi-Label Active Learning: Multi-Objective Optimization, Uncertainty Modeling, and Multi-Criterion Decision Making (Principal Investigator, National Natural Science Foundation of China, International Cooperation and Exchange Project)
01/2015–12/2017 Research on Rapid Learning Machine Method Based on Divide-and-Conquer Fusion and Active Learning (Principal Investigator, National Natural Science Foundation of China, Youth Science Foundation Project)
01/2018–12/2022 Uncertainty Modeling Theory and Methods for Big Data Machine Learning (Participant, National Natural Science Foundation of China Key Project)
01/2024–12/2027 Research and Application of Cost-Sensitive Deep Network Adversarial Robustness (Principal Investigator, Guangdong Provincial Natural Science Foundation Outstanding Youth Project)
01/2022–12/2024 Uncertainty Analysis, Modeling and Application in Deep Learning (Principal Investigator, Guangdong Provincial Natural Science Foundation General Project)
Recent Representative Publications:
[1] Farhad Pourpanah, Moloud Abdar, Yuxuan Luo, Xinlei Zhou, Ran Wang*, Chee Peng Lim, Xi-Zhao Wang, and Q. M. Jonathan Wu. A review of generalized zero-shot learning methods, IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(4): 4051–4070 (2023). ESI Hot Topics, Highly Cited
[2] Xinyin Zhang, Ran Wang*, Shuyue Chen, Yuheng Jia and Debby D. Wang. AME-LSIFT: Attention-Aware Multi-Label Ensemble with Label Subset-SpecIfic FeaTures, IEEE Transactions on Knowledge and Data Engineering, 36(12): 7627-7642 (2024).
[3] Yuheng Jia, Jia-Nan Li, Wenhui Wu, and Ran Wang*. Semi-supervised symmetric non-negative matrix factorization with low-rank tensor representation, IEEE Transactions on Circuits and Systems for Video Technology, 35(2): 1534–1547 (2025).
[4] Ran Wang* and Zichao Zhang. Set theory based operator design in evolutionary algorithms for solving knapsack problems, IEEE Transactions on Evolutionary Computation, 25(6): 1133–1147 (2021).
[5] Hong Zhu, Xizhao Wang*, and Ran Wang*. Fuzzy monotonic k-nearest neighbor versus monotonic fuzzy k-nearest neighbor, IEEE Transactions on Fuzzy Systems, 30(9): 3501–3513 (2022).
[6] Ran Wang*, Chi-Yin Chow, Yan Lyu, Victor C. S. Lee, Sam Kwong, Yanhua Li, and JiaZeng. TaxiRec: Recommending road clusters to taxi drivers using ranking-based extreme learning machines. IEEE Transactions on Knowledge and Data Engineering, 30(3): 585-598 (2018).
[7] Xi-Zhao Wang, Ran Wang*, and Chen Xu. Discovering the relationship between generalization and uncertainty by incorporating complexity of classification. IEEE Transactions on Cybernetics, 48(2): 703-715 (2018). ESI Hot Topics, Highly Cited
[8] Ran Wang, Xi-Zhao Wang*, Sam Kwong, and Chen Xu. Incorporating diversity and informativeness in multiple-instance active learning. IEEE Transactions on Fuzzy Systems, 25(6): 1460-1475 (2017).
[9] Ran Wang, Meng Hu, Haopeng Ke, and Wenhui Wu. Adversarially robust neural networks with feature uncertainty learning and label embedding, Neural Networks, 172: 106087 (2024).
[10] Ran Wang*, Shuyue Chen, and Yu Yu. Extending version space theory to multi-label active learning with imbalanced data, Pattern Recognition, 142: 109690 (2023).
