• 2008-2012：哈尔滨工业大学 计算机科学与技术 博士学位（全日制）
• 2006-2008：哈尔滨工业大学 计算机科学与技术 硕士学位（全日制）
• 2002-2006：哈尔滨工业大学 计算机科学与技术 学士学位（全日制）

工作经历

• 2017-至今：哈尔滨工业大学计算机学院 教授
• 2014-2016: 哈尔滨工业大学计算机学院 副教授
• 2014-2017：日本国立情报学研究所 特任研究员
• 2012-2013: 加拿大麦克马斯特大学 博士后

刘贤明，现任哈工大计算机学院长聘教授、副院长，国家自然科学杰青/优青基金获得者。研究方向为可信赖人工智能、多媒体信息处理，在Nature Methods、Nature Communications、TPAMI、JMLR、TRO、NeurIPS、ICML、ICLR、CVPR、ICCV、ICRA等国际顶级期刊和会议上发表论文200余篇。获得中国电子学会青年科学家奖、黑龙江省青年科技奖、中国人工智能学会吴文俊自然科学一等奖和优秀青年奖、中国图象图形学学会自然科学二等奖。主持国家重点研发计划重点专项项目、课题，国家自然科学杰青、优青、重大研究计划、面上和青年等项目。指导的博士生获评中国人工智能学会优秀博士论文奖、首届黑龙江人工智能学会优秀博士论文一等奖（唯一获奖者）、首批国家自然科学基金青年学生基础研究项目资助。荣获哈工大“育人新星”青年导师荣誉称号和黑龙江省研究生教学成果奖特等奖（第二完成人）。

代表论文：

【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

科研奖励：

2025年：中国电子学会青年科学家奖

2025年：中国人工智能学会吴文俊自然科学一等奖

2023年：黑龙江省青年科技奖

2018年：中国人工智能学会吴文俊优秀青年奖