获武汉大学计算机工学学士学位与经济法法学学士学位；获北京邮电大学硕士和博士学位；曾博士后访问UCLA。现任北京邮电大学教授，主要研究方向：视觉感知、计算摄影。

个人主页：http://www.vrobotit.cn/~mal

计算机属于实证类学科，个人更偏好与企业合作“实事求是”。部分与企业联合研发：

1、北邮-传音 视觉感知与计算联合实验室：http://kyy.bupt.edu.cn/info/1033/3869.htm

2、北邮-雷动云合 移动机器人联合实验室：http://www.vrobotit.cn/Detail.aspx?id=236

3、福星集团 “智慧养老” 联合研发工作组： http://www.vrobotit.cn/Detail.aspx?id=237

4、森蓝 “智能制造系统” 联合研发工作组： http://www.vrobotit.cn/Detail.aspx?id=249

近期部分代表作（更多论文见：publications）：

[1] Shuai He, Yongchang Zhang, Dongxiang Jiang, Rui Xie, Anlong Ming*, Rethinking Image Aesthetics Assessment: Models, Datasets and Benchmarks, the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJCAI-ECAI), 2022. 注：人工智能领域顶会

[2] Zhifeng Zhang, Xuejing Kang, Anlong Ming*, Domain Adversarial Learning for Color Constancy, in Proceedings of the 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJCAI-ECAI), 2022.  注：人工智能领域顶会

[3] Lei zhu, Xuejing Kang and Anlong Ming, Explored Normalized Cut with Random Walk Refining Term for Image Segmentation, IEEE Transactions on Image Processing (TIP), vol. 31, pp. 2893-2906, 2022. 注：图像处理领域顶刊

[4] Fei Sheng, Feng Xue, Wenteng Liang, Yichong Chang, Anlong Ming*, Monocular Depth Distribution Alignment with Low Computation, in Proceedings of the 2022 International Conference on Robotics and Automation (ICRA), 2022. 注：机器人领域顶会

[5] Yuxiang Tang, Xuejing Kang, Chunxiao Li, Zhaowen Lin, Anlong Ming*, Transfer Learning for Color Constancy via Statistic Perspective, in Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI), 2022. 注：人工智能领域顶会

[6] Panhe Feng, Qi She, Lei Zhu, Jiaxin Li, Lin Zhang, Zijian Feng, Changhu Wang, Chunpeng Li, Xuejing Kang, Anlong Ming , MT-ORL: Multi-Task Occlusion Relationship Learning, in Proceedings of International Conference on Computer Vision (ICCV), 2021. 注：计算机视觉领域顶会

[7] Lin Zhang, Xuejing Kang, Baoping Li, Yuzhong Chen, Anlong Ming, HDA-Net: Horizontal Deformable Attention Network for Stereo Matching, in Proceedings of  the 29th ACM International Conference on Multimedia (ACM MM), 2021. 注：多媒体领域顶会

[8] Feng Xue, Anlong Ming, Menghan Zhou, Yu Zhou, Tiny Obstacle Discovery by Occlusion-aware Multi-layer Regression, IEEE Transactions on Image Processing (TIP), vol. 29, pp. 9373-9386, 2020. 注：图像处理领域顶刊

[9] Lei zhu, Xuejing Kang and Anlong Ming*, Dynamic Random Walk for Superpixel Segmentation, IEEE Transactions on Image Processing (TIP),  vol. 29, pp. 3871-3884, 2020. 注：图像处理领域顶刊

[10] Rui Lu, Anlong Ming, Feng Xue, Menghan Zhou, Yu Zhou, Occlusion-shared and feature-separated Network for Occlusion Relationship Reasoning, in Proceedings of International Conference on Computer Vision (ICCV), 2019. 注：计算机视觉领域顶会