Name: Meng Pang

Title: Distinguished Professor

Research Interests: AI Security and Smart Healthcare

Education:

(1) 2009–2013: Dalian University of Technology – Software Engineering (Diploma)

(2) 2013–2016: Dalian University of Technology– Software Engineering (M.S.)

(3) 2016–2019: Hong Kong Baptist University – Computer Science (Ph.D.)

Professional Experience:

(1) 2020–2022: School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore (Researcher)

(2) 2022–present: School of Mathematics and Computer Science, Nanchang University (Distinguished Professor)

Academic Service:

(1) Associate Editor: IEEE Transactions on Emerging Topics in Computational Intelligence, Expert Systems

(2) PC Member: CVPR、ICCV、NeurIPS、ICLR、ECCV、AAAI、ECAI、ICME

(3) Professional Reviewer: TPAMI、TIFS、TIP、TNNLS、TCYB、TMM、TCSVT、PR

Honors & Awards:

(1) The Top 10% Paper Award at the 22nd IEEE International Conference on Image Processing (ICIP) (ranked first)

(2) The Best Paper Award at the 21st International Conference on Computational Intelligence and Security (CIS'2025) (ranked first)

(3) "Young Outstanding Employee" of Nanchang University, 2025

Key Achievements:

1. Selected Journal Papers

[J11] Meng Pang, Houwei Xu, Zheng Huang, Yintao Zhou, Shengbo Chen, Binghui Wang, Wei Huang. A tri-factor adaptive federated learning framework for Parkinson’s disease diagnosis via multi-source facial expression analysis. IEEE Journal of Biomedical and Health Informatics (JBHI), 2025, in press.

[J10] Meng Pang, Binghui Wang, Mang Ye, Yintao Zhou, Wei Huang, Bihan Wen. Heterogeneous Prototype Learning from Contaminated Faces across Domains via Disentangling Latent Factors. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2025, 36(4): 7169-7183.

[J9] Wei Huang, Wenqiang Xu, Renjie Wan, Peng Zhang, Yufei Zha, Meng Pang* (Corresponding author). Auto diagnosis of Parkinson’s disease via a deep learning model based on mixed emotional facial expressions. IEEE Journal of Biomedical and Health Informatics (JBHI), 2024, 28(5): 2547-2557.

[J8] Wei Huang, Yintao Zhou, Yiu-ming Cheung, Peng Zhang, Yufei Zha, Meng Pang* (Corresponding author). Facial expression guided diagnosis of Parkinson’s disease via high-quality data augmentation. IEEE Transactions on Multimedia (TMM), 2023, 25: 7037–7050.

[J7] Meng Pang, Binghui Wang, Mang Ye, Yiu-ming Cheung, Yiran Chen, Bihan Wen. DisP+V: A unified framework for disentangling prototype and variation from single sample per Person, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023, 34(2): 867–881.

[J6] Meng Pang, Binghui Wang, Siyu Huang, Yiu-ming Cheung, Bihan Wen. A unified framework for bidirectional prototype learning from contaminated faces across heterogeneous domains, IEEE Transactions on Information Forensics and Security (TIFS), 2022, 17: 1544–1557.

[J5] Meng Pang, Yiu-ming Cheung, Qiquan Shi, Mengke Li. Iterative dynamic generic learning for face recognition from a contaminated singe-sample per person. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021, 32(4): 1560–1574.

[J4] Meng Pang, Binghui Wang, Yiu-ming Cheung, Yiran Chen, Bihan Wen. VD-GAN: A unified framework for joint prototype and representation learning from contaminated single sample per person. IEEE Transactions on Information Forensics and Security (TIFS), 2021, 16: 2246–2259.

[J3] Meng Pang, Yiu-ming Cheung, Binghui Wang, Jian Lou. Synergistic generic learning for face recognition from a contaminated single sample per person. IEEE Transactions on Information Forensics and Security (TIFS), 2020, 15: 195–209.

[J2] Meng Pang, Yiu-ming Cheung, Binghui Wang, Risheng Liu. Robust heterogeneous discriminative analysis for face recognition with single sample per person. Pattern Recognition (PR), 2019, 89: 91–107.

[J1] Meng Pang, Yiu-ming Cheung, Risheng Liu, Jian Lou, Chuang Lin. Toward efficient image representation: Sparse concept discriminant matrix factorization. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2019, 29(11): 3184–3198.

2. Selected Conference Papers

[C12] Shanshan Yan, Zexi Li, Chao Wu, Meng Pang, Yang Lu, Yan Yan, Hanzi Wang. You are your own best teacher: Achieving centralized-level performance in federated learning under heterogeneous and long-tailed data. IEEE/CVF International Conference on Computer Vision (ICCV), Honolulu, Hawaii, Oct 19-23th, 2025.

[C11] Wei Huang, Yinxuan Xu, Yintao Zhou, Zhengyu Li, Jing Huang, Meng Pang*(Corresponding author). A Multimodal In Vitro Diagnostic Method for Parkinson’s Disease Combining Facial Expressions and Behavioral Gait Data. Proceedings of the Annual Meeting of the Cognitive Science Society (COGSCI), Marriott Marquis, San Francisco, USA, July 30-Aug 2, 2025.

[C10] Meng Pang, Wenjun Zhang, Nanrun Zhou, Shengbo Chen, Hong Rao. UMFN: Unified multi-domain face normalization for joint cross-domain prototype learning and heterogeneous face recognition. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2025: 29299-29308.

[C9] Jiate Li, Meng Pang, Yun Dong, Binghui Wang. Deterministic certification of graph neural networks against poisoning attacks with arbitrary perturbations. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Nashville, USA, June 11-June 15, 2025.

[C8] Jiate Li, Meng Pang, Yun Dong, Jinyuan Jia, Binghui Wang. Provably robust explainable graph neural networks against graph perturbation attacks. International Conference on Learning Representations (ICLR), Singapore, Apr 24-Apr 28, 2025.

[C7] Jiate Li, Meng Pang*(Corresponding author), Binghui Wang. Practicable black-box evasion attacks on link prediction in dynamic graphs—A graph sequential embedding method. Annual AAAI Conference on Artificial Intelligence (AAAI), 2025, 39(25): 26265–26272.

[C6] Meng Pang, Houwei Xu, Zheng Huang, Yintao Zhou, Wei Huang, Binghui Wang. Breaking data silos in Parkinson’s disease diagnosis: An adaptive federated learning approach for privacy-preserving facial expression analysis. Annual AAAI Conference on Artificial Intelligence (AAAI), 2025, 39(13): 14352–14360.

[C5] Jiate Li, Meng Pang* (Corresponding author), Yun Dong, Jinyuan Jia, Binghui Wang*. Graph neural network explanations are fragile. International Conference on Machine Learning (ICML), Vienna, Austria, July 21-27, 2024.

[C4] Meng Pang, Binghui Wang, Nanrun Zhou, Yintao Zhou, Wei Huang. Reconstructing prototype from contaminated face with variations across heterogeneous domains. IEEE International Conference on Multimedia and Expo (ICME), Niagra Falls, Canada, July 15-19, 2024.

[C3] Yintao Zhou, Meng Pang* (Corresponding author), Wei Huang, Binghui Wang. Early Diagnosing Parkinson's disease via a deep learning model based on augmented facial expression data. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024: 1621–1625.

[C2] Yunpeng Wang, Meng Pang*(Corresponding author), Shengbo Chen, Hong Rao. Consistency-GAN: Training gans with consistency model. Annual AAAI Conference on Artificial Intelligence (AAAI), 2024, 38(14): 15743–15751.

[C1] Binghui Wang, Meng Pang*(Corresponding author), Yun Dong. Turning strengths into weaknesses: A certified robustness inspired attack framework against graph neural networks. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2023: 16394–16403.

Email: mengpang@ncu.edu.cn