张健，博士，北京大学信息工程学院长聘副教授/研究员、博士生导师，视觉信息智能学习实验室（VILLA）负责人。哈尔滨工业大学数学与应用数学理学学士（2007）、计算机科学与技术工学硕士（2009）及计算机应用工学博士（2014），并分别在北京大学、香港科技大学和沙特国王科技大学做博士后研究工作。2019年创立了视觉信息智能学习实验室（VILLA），主要从事视觉内容重建与生成、AIGC内容鉴伪和版权保护等前沿方向研究。已在Nature Commun Eng、IEEE TPAMI、TIP、IJCV、SPM、CVPR、NeurIPS、ICCV等高水平国际期刊和会议上发表论文120余篇。近三年，以第一作者/通讯作者发表CCF A类论文40余篇。谷歌学术引用10000余次，h-index值为50（单篇一作最高引用1300余次）。相关研究成果申请/授权中国专利15项。主持国家科技重大专项课题、国自然重点项目课题、国自然面上、深圳市重点、以及与字节/华为/OPPO/创维/兔展等知名企业学术合作项目10余项。

教学方面，获得北京大学第二十三届青年教师教学基本功比赛一等奖（以及最佳教学演示奖和最受学生欢迎奖）、北京大学“优秀班主任”、北京大学“优秀共产党员”荣誉称号等，多名学生荣获硕士/博士研究生国家奖学金、北京大学三好学生、北京大学三好学生标兵、北京大学优秀毕业生、北京市优秀毕业生等；科研方面，获得IEEE视觉通讯与图像处理（VCIP）国际会议2011年度最佳论文奖以及该国际会议2015年度最佳学生论文奖、IEEE多媒体IEEE MultiMedia国际期刊2018年度最佳论文奖、中国多媒体大会ChinaMM 2021年度最佳论文奖、深圳市科学技术协会2021/2023年优秀自然科学学术论文奖、2023中国人工智能学会—华为MindSpore学术奖励基金项目优秀奖，携手字节获“NTIRE 2023全球挑战赛全景图像超分辨率赛道”总冠军、连续五年入选斯坦福大学评选“全球前2%顶尖科学家”榜单等。 服务方面，担任深圳市人工智能学会青年工作委员会主任、广东省图象图形学会理事、中国图象图形学学会青年工作委员会委员、视觉与学习青年学者研讨会（VALSE）执行委员等；同时担任Journal of Visual Communication and Image Representation、Signal, Image and Video Processing、CAAI Transactions on Intelligence Technology等国际期刊编委。

欢迎优秀的本科生和硕士生保送和报考北京大学信息工程学院的硕士和博士研究生，课题组博士后职位也已开放，更多招生、实习以及科研最新信息请查看个人主页：https://jianzhang.tech/cn/。

[1]J. Zhang, B. Chen, R. Xiong, and Y. Zhang. Physics-Inspired Compressive Sensing: BeyondDeepUnrolling.IEEE Signal Processing Magazine (SPM), vol. 40, no. 1, pp. 58-72, Jan. 2023.（信号处理领域旗舰期刊，影响因子=9.4，引用69次）

[2]J. Zhang, C. Zhao, and W. Gao. Optimization-Inspired Compact Deep Compressive Sensing.IEEE Journal of Selected Topics in Signal Processing(JSTSP), vol. 14, no. 4, pp. 765-774, May 2020.（信号处理领域知名期刊，影响因子=8.7，引用185次）

[3]J. Zhangand B. Ghanem. ISTA-Net: Interpretable Optimization-Inspired Deep Network for Image Compressive Sensing.Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1828-1837, June 2018.（计算机视觉领域顶级会议，引用1314次）

[4]B. Chen, Z. Zhang, W. Li, C. Zhao, J. Yu, S. Zhao, J. Chen,J. Zhang. Invertible Diffusion Models for Compressed Sensing,IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 10.1109/TPAMI.2025.3538896, 2025.（人工智能领域顶级期刊，影响因子=20.8）

[5]B. Chen,J. Zhang. Practical Compact Deep Compressed Sensing.IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI),vol. 47, no.3, pp.1610-1626,March2025.（人工智能领域顶级期刊，影响因子=20.8）

[6]C. Mou, X. Wang, Y. Wu, Y. Shan, andJ. Zhang. Empowering Real-World Image Super-Resolution with Flexible Interactive Modulation.IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 46, no.11, pp. 7317-7330,November2024.（人工智能领域顶级期刊，影响因子=20.8）

[7]C. Mou andJ. Zhang.TransCL: Transformer Makes Strong and Flexible Compressive Learning.IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 45, no. 4, pp. 5236-5251, April 2023.（人工智能领域顶级期刊，影响因子=20.8）

[8]S. Liu, B. Chen, W. Zou, H. Sha, X. Feng, X. Li, X. Yao,J. Zhang, and Y. Zhang.CompressiveConfocalMicroscopy Imagingatthe Single-Photon Levelwith Ultra-Low Sampling Ratios.Communications Engineering, vol. 3, no. 88, pp. 1-9, June 2024.（Nature系列子刊）

[9]B.Chen,X.Zhang, S.Liu, Y.Zhang,J.Zhang. Self-Supervised Scalable Deep Compressed Sensing.International Journal of Computer Vision (IJCV), 2024.（计算机视觉领域顶级期刊，影响因子=11.6）

[10]S.Yang, X.Zhang, Y.Wang, J.Yu, Y.Wang,J.Zhang.DiffLLE: Diffusion-guided Domain Calibration for Unsupervised Low-light Image Enhancement.International Journal of Computer Vision (IJCV), 2024.（计算机视觉领域顶级期刊，影响因子=11.6）

[11]J. Song, B. Chen, andJ. Zhang. Deep Memory-Augmented Proximal Unrolling Network for Compressive Sensing.International Journal of Computer Vision (IJCV), vol. 131, no. 6, pp. 1477-1496, March 2023.（计算机视觉领域顶级期刊，影响因子=11.6）

[12]B. Chen, J. Song, J. Xie, andJ. Zhang. Deep Physics-Guided Unrolling Generalization for Compressed Sensing.International Journal of Computer Vision (IJCV),vol. 131, no. 11, pp. 2864-2887, July 2023.（计算机视觉领域顶级期刊，影响因子=11.6）

[13]J. Song, B. Chen, andJ. Zhang*. Dynamic Path-Controllable Deep Unfolding Network for Compressive Sensing.IEEE Transactions on Image Processing (TIP), vol. 32, pp. 2202-2214, April 2023.（图像处理领域顶级期刊，影响因子=10.8）

[14]B. Chen andJ. Zhang. Content-Aware Scalable Deep Compressed Sensing.IEEE Transactions on Image Processing (TIP), vol. 31, pp. 5412-5426, Aug. 2022.（图像处理领域顶级期刊，影响因子=10.8）

[15]D. You,J. Zhang, J. Xie, B. Chen, and S. Ma. COAST: COntrollable Arbitrary-Sampling NeTwork for Compressive Sensing.IEEE Transactions on Image Processing (TIP), vol. 30, pp. 6066-6080,June 2021.（图像处理领域顶级期刊，影响因子=10.8，引用126次）

[16]C. Mou, X. Wang, L. Xie, Y. Wu,J. Zhang, Z. Qi, and Y. Shan. T2I-Adapter: Learning Adapters to Dig Out More Controllable Ability for Text-to-Image Diffusion Models.Proc. of the AAAI Conference on Artificial Intelligence (AAAI), pp. 4296-4304, March 2024.（人工智能领域顶级会议，引用864次，3.6k star）

[17]C. Mou,M. Cao, X. Wang, Z. Zhang, Y. Shan,J. Zhang. ReVideo: Remake a Video with Motion and Content Control.Proc. of the Advances in Neural Information Processing Systems (NeurIPS), Dec. 2024.（机器学习领域顶级会议）

[18]X. Zhang, J. Meng, R. Li, Z. Xu, Y. Zhang,J. Zhang.GS-Hider: Hiding Messages into 3D Gaussian Splatting.Proc.ofthe Advances in Neural Information Processing Systems (NeurIPS), Dec. 2024.（机器学习领域顶级会议）

[19]Y. Wu, J. Meng, H. Li, C. Wu, Y. Shi, X. Cheng, C. Zhao, H. Feng, E. Ding, J. Wang,J. Zhang. OpenGaussian: Towards Point-Level 3D Gaussian-based Open Vocabulary Understanding.Proc. of the Advances in Neural Information Processing Systems (NeurIPS), Dec. 2024.（机器学习领域顶级会议）

[20]Q. Gao, J. Meng, C. Wen, J. Chen,J. Zhang.HiCoM: Hierarchical Coherent Motion for Dynamic Streamable Scenes with 3D Gaussian Splatting.Proc. of the Advances in Neural Information Processing Systems (NeurIPS), Dec. 2024.（机器学习领域顶级会议）

[21]X. Zhang, R. Li, J. Yu, Y. Xu, W. Li, andJ. Zhang. EditGuard: Versatile Image Watermarking for Tamper Localization and Copyright Protection.Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 11964-11974, June 2024.（计算机视觉领域顶级会议）

[22]Q. Wang, W. Li, C. Mou, X. Cheng, andJ. Zhang. 360DVD: Controllable Panorama Video Generation with 360-Degree Video Diffusion Model.Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 6913-6923, June 2024.（计算机视觉领域顶级会议）

[23]C. Mou, X. Wang, J. Song, Y. Shan, andJ. Zhang. DiffEditor: Boosting Accuracy and Flexibility on Diffusion-based Image Editing.Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 8488-8497, June 2024.（计算机视觉领域顶级会议）

[24]C. Mou, X. Wang, J. Song, Y. Shan, andJ. Zhang. DragonDiffusion: Enabling Drag-style Manipulation on Diffusion Models.Proc. of the International Conference on Learning Representations (ICLR), May 2024.（机器学习领域顶级会议，引用124次）

[25]J. Yu, X. Zhang, Y. Xu, andJ. Zhang. CRoSS: Diffusion Model Makes Controllable, Robust and Secure Image Steganography.Proc. of the Advances in Neural Information Processing Systems (NeurIPS), pp.80730-80743, Dec. 2023.（机器学习领域顶级会议）

[26]Y. Wang, J. Yu^, andJ. Zhang. Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model.Proc. of the International Conference on Learning Representations (ICLR), pp. 1-12, May 2023.（机器学习领域顶级会议，引用385次，1.1k star）

[27]Q. Gao, C. Zhao, Y. Sun, T. X, G. Zhang, B. Ghanem,andJ. Zhang. A Unified Continual Learning Framework with General Parameter-Efficient Tuning.Proc. of the IEEE International Conference on Computer Vision (ICCV), pp. 11483-11493, Oct. 2023.（计算机视觉领域顶级会议）

[28]J. Yu, Y. Wang, C. Zhao, B. Ghanem, andJ. Zhang. FreeDoM: Training-Free Energy-Guided Conditional Diffusion Model.Proc. of the IEEE International Conference on Computer Vision (ICCV), pp. 23174-23184, Oct. 2023.（计算机视觉领域顶级会议，引用115次）

[29]S. Yang, M. Ding, Y. Wu, Z. Li, andJ. Zhang. Implicit Neural Representation for Cooperative Low-light Image Enhancement”,Proc. of the IEEE International Conference on Computer Vision (ICCV), pp. 12918-12927, Oct. 2023.（计算机视觉领域顶级会议，引用108次）

[30]Y. Wu, X. Cheng, R. Zhang, Z. Cheng, andJ. Zhang. EDA: Explicit Text-Decoupling and Dense Alignment for 3D Visual Grounding.Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 19231-19242, June 2023.（计算机视觉领域顶级会议）

[31]C. Mou, Y. Xu, J. Song, C. Zhao, B. Ghanem, andJ. Zhang. Large-Capacity and Flexible Video Steganography via Invertible Neural Network.Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 22606-22615, June 2023.（计算机视觉领域顶级会议）J. Song, C. Mou, S. Wang, S. Ma, andJ. Zhang. Optimization-Inspired Cross-Attention Transformer for Compressive Sensing.Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 6174-6184, June 2023.（计算机视觉领域顶级会议）

[32]Y. Xu, C. Mou, Y. Hu, J. Xie, andJ. Zhang. Robust Invertible Image Steganography.Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 7875-7884, June 2022.（计算机视觉领域顶级会议，引用116次）

[33]X. Zhang, Y. Zhang, R. Xiong, Q. Sun, andJ. Zhang.HerosNet: Hyperspectral Explicable Reconstruction and Optimal Sampling Deep Network for Snapshot Compressive Imaging.Proc. of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 17532–17541, June 2022.（计算机视觉领域顶级会议）

[34]C. Mou, Q. Wang, andJ. Zhang. Deep Generalized Unfolding Networks for Image Restoration.Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 17399-17410, June 2022.（计算机视觉领域顶级会议，引用237次）

1、《计算视觉理论、模型与方法》（必修）

2、《算法分析与复杂性理论》（必修）

1、基于扩散模型的条件图像生成

2、超高清沉浸媒体技术研究

3、AIGC内容篡改检测研究

1、专业范围：计算机/软件工程/人工智能等相关学科；

2、外语/数学能力：英语六级、雅思、托福；

3、研究/开发能力：熟练的程序设计能力，具有一定的探索能力和创新精神；

4、其他要求：对做科研工作有热情、有兴趣。