教育经历：

• 2008 – 2012: Ph.D. in Computer Science and Technology, Harbin Institute of Technology
• 2006 – 2008: M.S. in Computer Science and Technology, Harbin Institute of Technology
• 2002 – 2006: B.S. in Computer Science and Technology, Harbin Institute of Technology

Work Experience：

• 2017 – Present:  Professor, School of Computer Science and Technology, Harbin Institute of Technology
• 2014 – 2016 : Associate Professor, School of Computer Science and Technology, Harbin Institute of Technology
• 2014 – 2017: Project Researcher, National Institute of Informatics (NII), Japan
• 2012 – 2013：Postdoctoral Fellow, McMaster University, Canada

Xianming Liu, PhD, is a Professor and Doctoral Supervisor at the Faculty of Computing, Harbin Institute of Technology (HIT), Harbin, China. He graduated from HIT with a PhD in Computer Science and Technology. He worked  at McMaster University, Canada and  National Institute of Informatics,  Japan for four years. His research focuses on Trustworthy AI and Multimeida Signal Processing. He has hosted 5 key projects of the National Natural Science Foundation of China and published over 200 papers in top journals/conferences such as Nature Methods、Nature Communications、TPAMI、JMLR、NeurIPS、ICML、ICLR、CVPR、ICCV、ECCV、AAAI. Cooperation in AI related fields and applications from outstanding students are welcome.

Representative Publications：

【Nature Communications】Feilong Zhang, Deming Zhai, Guo Bai, Junjun Jiang, Qixiang Ye, Xiangyang Ji*, Xianming Liu*, "Towards Fairness-aware and Privacy-preserving Enhanced Collaborative Learning for Healthcare", Nature Communications 16, 2852 (2025).  

【JMLR】Xiong Zhou, Xianming Liu*, Hanzhang Wang, Deming Zhai, Junjun Jiang, Xiangyang Ji,  "On the Dynamics under the Unhinged Loss and Beyond", Journal of Machine Learning Research, 2023, 21(108):1−5.  CCF-A

【TPAMI】Xiong Zhou, Xianming Liu*, Demin Zhai, Junjun Jiang, Xiangyang Ji,  "Asymmetric Loss Functions for Noise-tolerant Learning: Theory and Applications", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 45, no. 7, pp. 8094-8109, 2023. CCF-A

【TPAMI】Wenbo Zhao, Xianming Liu*, D. Zhai, Junjun Jiang, Xiangyang Ji,  "Self-Supervised Arbitrary-Scale Implicit Point Clouds Upsampling", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 45, no. 10, pp. 12394-12407, Oct. 2023. CCF-A

【TPAMI】Yuanchao Bai, Xianming Liu*,  Kai, Wang, Xiangyang Ji, Wen Gao,  "Deep Lossy Plus Residual Coding for Lossless and Near-lossless Image Compression", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 46, no. 5, pp. 3577-3594, May 2024.  CCF-A

【TPAMI】Zhiwei Zhong, Xianming Liu*, Junjun Jiang, Debin Zhao, Shiqi Wang, "Dual-Level Cross-Modality Neural Architecture Search for Guided Image Super-Resolution", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 47, no. 9, pp. 8249-8267, Sept. 2025.  CCF-A

【TPAMI】Yuru Xiao, Deming Zhai, Wenbo Zhao, Kui Jiang, Junjun Jiang and Xianming Liu, "MCGS: Multiview Consistency Enhancement for Sparse-View 3D Gaussian Radiance Fields," IEEE Transactions on Pattern Analysis and Machine Intelligence, doi: 10.1109/TPAMI.2025.3607103. CCF-A

【TRO】Bo Pang, Deming Zhai, Jianan Zhen, Long Wang, Xianming Liu*, "Fast and Accurate 6D Object Pose Refinement via Implicit Surface Optimization", IEEE Transactions on Robotics, 2025   清华A类

【TIP】Zhiwei Zhong, Xianming Liu*, Junjun Jiang, Debin Zhao, Zhiwen Chen, Xiangyang Ji: High-Resolution Depth Maps Imaging via Attention-Based Hierarchical Multi-Modal Fusion. IEEE Transactions on Image Processing 31: 648-663 (2022)  CCF-A

【TIP】Kai Wang, Yuanchao Bai, Daxin Li, D. Zhai, Junjun Jiang, Xianming Liu*,  "Learning Lossless Compression for High Bit-Depth Volumetric Medical Image", IEEE Transactions on Image Processing, vol. 34, pp. 113-125, 2025. CCF-A

【NeurIPS】Jialiang Wang, Xiong Zhou, Deming Zhai, Junjun Jiang, Xiangyang Ji, Xianming Liu*, "ε-Softmax: Approximating One-Hot Vectors for Mitigating Label Noise", NeurIPS 2024 CCF-A

【NeurIPS】Jian Liu, Jianyu Wu, Hairun Xie, Guoqing zhang, Jing Wang, Liu Wei, Wanli Ouyang, Junjun Jiang, Xianming Liu*, Shixiang Tang*, Miao Zhang*, "AFBench: A Large-scale Benchmark for Airfoil Design", NeurIPS 2024    CCF-A

【ICLR】 Xiong Zhou, Xianming Liu*, H. Yu, Jialiang Wang, Zeke Xie, Junjun Jiang, Xiangyang Ji, "Variance-enlarged Poisson Learning for Graph-based Semi-Supervised Learning with Extremely Sparse Labeled Data", ICLR2024  CCF-A

【ICLR】Xiong Zhou, Xianming Liu*, Feilong Zhang, Gang Wu, Deming Zhai, Junjun Jiang, Xiangyang Ji, "Zero-Mean Regularized Spectral Contrastive Learning", ICLR2024  CCF-A

【ICLR】Xiong Zhou, Xianming Liu*, Deming Zhai, Junjun Jiang, Xiangyang Ji, "Learning Towards the Largest Margins", ICLR2022.  CCF-A

【ICML】Xiong Zhou, Xianming Liu*, Deming Zhai, Junjun Jiang, Xin Gao, Xiangyang Ji, "Prototype-anchored Learning for Learning with Imperfect Annotations", ICML2022  CCF-A

【ICML】Xiong Zhou, Xianming Liu*, Junjun Jiang, Xin Gao, Xiangyang Ji, "Asymmetric Loss Functions for Learning with Noisy Labels", ICML2021   CCF-A

【CVPR】Yiqi Zhong, Xianming Liu*， Deming Zhai, Junjun Jiang, Xiangyang Ji, "Shadows can be Dangerous: Stealthy and Effective Physical-world Adversarial Attack by Natural Phenomenon", CVPR2022   CCF-A

【CVPR】Feilong Zhang, Xianming Liu*, Cheng Guo, Shiyi Lin, Junjun Jiang, Xiangyang Ji: Physics-Based Iterative Projection Complex Neural Network for Phase Retrieval in Lensless Microscopy Imaging. CVPR 2021: 10523-10531.  CCF-A

【CVPR】Wenbo Zhao, Xianming Liu*, Zhiwei Zhong, Junjun Jiang, Wei Gao, Ge Li, Xiangyang Ji: Self-Supervised Arbitrary-Scale Point Clouds Upsampling via Implicit Neural Representation. CVPR 2022: 1989-1997.  CCF-A

【CVPR】Yuanchao Bai, Xianming Liu*, Wangmeng Zuo, Yaowei Wang, Xiangyang Ji, "Learning Scalable L∞-constrained Near-lossless Image Compression via Joint Lossy Image and Residual Compression"， CVPR2021   CCF-A

【CVPR】Yuchen Pan, Junjun Jiang, Kui Jiang, Keyuan Yu, Xianming Liu, "OpticalDR: A Deep Optical Imaging Model for Privacy-Protective Depression Recognition", CVPR 2024  CCF-A 

【ICCV】Jialiang Wang, Xianming Liu*, Xiong Zhou, Gangfeng Hu, Deming Zhai, Junjun Jiang, Xiangyang Ji, "Joint Asymmetric Loss for Learning with Noisy Labels", ICCV2025  CCF-A

【ICCV】Xiong Zhou, Xianming Liu*, Chenyang Wang, Deming Zhai, Junjun Jiang, Xiangyang Ji, "Learning with Noisy Labels via Sparse Regularization", ICCV2021  CCF-A

【AAAI】Wenbo Zhao, Xianming Liu*, Junjun Jiang, Debin Zhao, Xiangyang Ji: Local Surface Descriptor for Geometry and Feature Preserved Mesh Denoising. AAAI 2022: 3446-3453. CCF-A

【AAAI】Daxin Li, Yuanchao Bai, Kai Wang, J. Jiang, Xianming Liu*, Wen Gao,  "CALLIC: Content Adaptive Learning for Lossless Image Compression", AAAI2025  CCF-A

【AAAI】Yuanchao Bai, Xu Yang, Xianming Liu*, Junjun Jiang, Yaowei Wang, Xiangyang Ji, Wen Gao, "Towards End-to-End Image Compression and Analysis with Transformers", AAAI2022  CCF-A