Di Ming

I am now a lecturer in School of Computer Science and Engineering at Chongqing University of Technology, and leading the Adversarial Machine Learning Group (AdvML-Group).

I obtained my Ph.D. degree in Computer Science from University of Texas at Arlington (UT Arlington) under the supervision of Prof. Chris H.Q. Ding in May 2020. Before that, I received my master degree in Computer Science from University of Electronic Science and Technology of China (UESTC) under the supervision of Prof. Quan Wen in June 2014, and received my bachelor degree in Computer Science from Sichuan Agricultural University (SICAU) in June 2011.

My primary research interests are machine learning and optimization, aiming at developing robust learning models and efficient optimization algorithms to solve real-world problems in various scenarios, such as feature selection, data reconstruction, subspace clustering, representation learning, graph learning, adversarial attack, foreground extraction, saliency detection, dermoscopy image segmentation, etc.

Office: Room B208, First Laboratory Building, 69 Hongguang Avenue, Banan District, Chongqing 400054.

news

Nov 11, 2024	Invited to serve as a reviewer for the IEEE Transactions on Neural Networks and Learning Systems (TNNLS)!
Nov 4, 2024	Invited to serve as a reviewer for 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR’25)!
Sep 26, 2024	One paper accepted by the Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024)!
Sep 13, 2024	Received the Natural Science Foundation of Chongqing, China grant 100K(RMB) to study efficient and robust multi-granularity sparse representation learning method!
Aug 25, 2024	Invited to serve as a reviewer for the Thirteenth International Conference on Learning Representations (ICLR 2025)!
May 23, 2024	Invited to serve as a reviewer for the Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024)!
May 10, 2024	Code for our method "Transferable Structural Sparse Adversarial Attack Via Exact Group Sparsity Training (CVPR 2024)" is released!
Feb 27, 2024	One paper accepted by Computer Vision and Pattern Recognition 2024 (CVPR 2024)! Acceptance rates: 23.6%, 2719/11532.
Feb 15, 2024	Invited to serve as a reviewer for the 18th European Conference on Computer Vision (ECCV 2024)!
Jan 17, 2024	Invited to serve as a reviewer for 2024 IEEE International Conference on Pattern Recognition (ICPR’24)!
Jan 10, 2024	One paper accepted by Elsevier Journal ‐ Expert Systems With Applications (ESWA)!
Nov 19, 2023	Invited to serve as a reviewer for 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR’24)!
Sep 28, 2023	Code for our method "TRM-UAP: Enhancing the Transferability of Data-Free Universal Adversarial Perturbation via Truncated Ratio Maximization (ICCV 2023)" is released!
Jul 15, 2023	One paper accepted by International Conference on Computer Vision 2023 (ICCV 2023)! Acceptance rates: 26.15%, 2160/8260.
Jun 16, 2023	Received the youth project of science and technology research program of Chongqing Education Commission of China grant 40K(RMB) to study transferable sparse adversarial attack algorithm!
Feb 15, 2023	Received the OMRON grant 125K(RMB) to study foreground extraction algorithm!
Jan 22, 2022	Received the Scientific Research Foundation of Chongqing University of Technology grant 200K(RMB) to study structural sparsity based robust and flexible learning model!
Aug 10, 2019	One paper accepted by 28th International Joint Conference on Artificial Intelligence (IJCAI 2019)! Acceptance rates: 17.9%, 850/4752.
Jan 27, 2019	One paper accepted by Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 2019)! Acceptance rates: 16.2%, 1150/7095.