Le Gan

Le Gan

Nanjing University of Science and Technology

Le Gan is currently an Associate Professor in School of Computer Science and Engineering at the Nanjing University of Science and Technology(NJUST). I received my Ph.D. degree of GIS from Nanjing University in Aug. 2018. In the same year, I was fortunate to join in the LAMDA Group led by Prof. Zhi-Hua Zhou, working closely with Prof. De-Chuan Zhan. From Oct. 2018 to Feb. 2025, I worked as an Assistant Researcher and Associate Researcher of School of Computer Science at Nanjing University. From Mar. 2025, I joined the School of Computer Science and Engineering of Nanjing University of Science and Technology as an Associate Professor. My research interest includes artificial intelligence and machine learning, mainly focus on reinforcement learning, world model, model reuse, and incremental learning, etc.

Publications [Google Scholar] [DBLP]

  • Yi Shi, Rui-Xiang Li, Le Gan, De-Chuan Zhan, Han-Jia Ye. Generalized Conditional Similarity Learning via Semantic Matching, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025.
  • Hai-Long Sun, Da-Wei Zhou, Hanbin Zhao, Le Gan, De-Chuan Zhan, Han-Jia Ye. MOS: Model Surgery for Pre-Trained Model-Based Class-Incremental Learning, In: Proceedings of the 39th AAAI Conference on Artificial Intelligence (AAAI’25, CCF-A), Pennsylvania, USA, 2025.
  • Kaichen Huang, Minghao Shao, Shenghua Wan, Hai-Hang Sun, Le Gan, Shuai Feng, De-Chuan Zhan. Leveraging Separated World Model for Exploration in Visually Distracted Environments, In: Advances in Neural Information Processing Systems 37 (NeurIPS’24, CCF-A), Vancouver, Canada, 2024.
  • Yichu Xu, Xin-Chun Li, Le Gan, De-Chuan Zhan. Weight Scope Alignment: A Frustratingly Easy Method for Model Merging, In: Proceedings of the 27th European Conference on Artificial Intelligence(ECAI’24, CCF-B), Santiago de Compostela, 2024.
  • Wen-Shu Fan, Su Lu, Xin-Chun Li, De-Chuan Zhan, Le Gan. Revisit the Essence of Distilling Knowledge through Calibration, In: Proceedings of the 41th International Conference on Machine Learning (ICML’24, CCF-A), Vienna, Austria, 2024.
  • Yucen Wang, Shenghua Wan, Le Gan, Shuai Feng, De-Chuan Zhan. AD3: Implicit Action is the Key for World Models to Distinguish the Diverse Visual Distractors. In: Proceedings of the 41th International Conference on Machine Learning (ICML’24, CCF-A), Vienna, Austria, 2024.
  • Shenghua Wan, Ziyuan Chen, Le Gan, Shuai Feng, De-Chuan Zhan. SeMOPO: Learning High-quality Model and Policy from Low-quality Offline Visual Datasets, In: Proceedings of the 41th International Conference on Machine Learning (ICML’24, CCF-A), Vienna, Austria, 2024.
  • Shenghua Wan, Hai-Hang Sun, Le Gan, De-Chuan Zhan. MOSER: Learning Sensory Policy for Task-specific Viewpoint via View-conditional World Model, In: Proceedings of the 33th International Joint Conference on Artificial Intelligence (IJCAI’24, CCF-A), Jeju, Korea, 2024.

  • Jia-Qi Yang, De-Chuan Zhan, Le Gan. Beyond Probability Partitions: Calibrating Neural Networks with Semantic Aware Grouping, In: Advances in Neural Information Processing Systems 36 (NeurIPS’23, CCF-A), New Orleans, LA, 2023.

  • Xin-Chun Li , Yan-Jia Wang, Le Gan, De-Chuan Zhan. Exploring Transferability Measures and Domain Selection in Cross-Domain Slot Filling. In: Proceedings of the 2022 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP’22, CCF-B), Virtual, Singapore, 2022.

  • Xin-Chun Li, Jin-Lin Tang, Shaoming Song, Bingshuai Li, Yinchuan Li, Yunfeng Shao, Le Gan, De-Chuan Zhan. Avoid Overfitting User Specific Information in Federated Keyword Spotting. In: Proceedings of the 2022 Conference of the International Speech Communication Association (Interspeech’22, CCF-C), Incheon, Korea. 2022.

  • Su Lu, Han-Jia Ye, Le Gan, De-Chuan Zhan. Towards Enabling Meta-Learning from Target Models. In: Advances in Neural Information Processing Systems 34 (NeurIPS’21, CCF-A), Virtual, 2021.

  • Le Gan, Junshi Xia, Peijun Du, Jocelyn Chanussot, Multiple Feature Kernel Sparse Representation Classifier for Hyperspectral Imagery, IEEE Transactions on Geoscience and Remote Sensing, 2018, 56(9): 5343-5356. DOI:10.1109/TGRS.2018.2814781.

  • Le Gan, Junshi Xia, Peijun Du, Jocelyn Chanussot, Class-oriented Weighted Kernel Sparse Representation with Region-level Kernel for Hyperspectral Imagery Classification, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018, 11(4): 1118-1130. DOI: 10.1109/JSTARS.2017.2757475.

  • Peijun Du, Le Gan, Junshi Xia, Daming Wang, Multikernel Adaptive Collaborative Representation for Hyperspectral Image Classification, IEEE Transactions on Geoscience and Remote Sensing, 2018, 56(8): 4664-4677. DOI:10.1109/TGRS.2018.2833882.

  • Le Gan, Peijun Du, Junshi Xia, and Yaping Meng, Kernel Fused Representation-Based Classifier for Hyperspectral Imagery, IEEE Geoscience and Remote Sensing Letters, 2017, 14(5) : 684-688. DOI:10.1109/LGRS.2017.2671852.

  • Le Gan, Junshi Xia, Peijun Du, and Zhigang Xu, Dissimilarity-Weighted Sparse Representation for Hyperspectral Image Classification, IEEE Geoscience and Remote Sensing Letters, 2017, 14(11): 1968-1972. DOI:10.1109/LGRS.2017.2743742.

  • Yeting Fan, Xiaobin Jin, Le Gan, Qingke Yang, Linzhi Wang, Ligang Lyu, Ying Li. Exploring an integrated framework for “dynamic-mechanism-clustering” of multiple cultivated land functions in the Yangtze River Delta region. Applied Geography, 2023, 159, 103061. DOI:10.1016/j.apgeog.2023.103061.

  • Yeting Fan, Xiaobin Jin, Le Gan, Laura H Jessup, Bryan C Pijanowski, Jinhuang Lin, Qingke Yang, Ligang Lyu. Dynamics of spatial associations among multiple land use functions and their driving mechanisms: A case study of the Yangtze River Delta region, China. Environmental Impact Assessment Review, 2022, 97, 106858. DOI:10.1016/j.eiar.2022.106858.

  • Yeting Fan, Le Gan, Changqiao Hong, Laura H.Jessup, Xiaobin Jin, Bryan C.Pijanowski, Yan Sun, Ligang Lv. Spatial identification and determinants of trade-offs among multiple land use functions in Jiangsu Province, China. Science of the Total Environment, 2021, 772, 145022. DOI:10.1016/j.scitotenv.2021.145022.

  • Zhigang Xu, Jike Chen, Junshi Xia, Peijun Du, Hongrui Zheng, Le Gan. Multisource Earth Observation Data for Land-Cover Classification Using Random Forest. IEEE Geoscience and Remote Sensing Letters. 2018, 15(5): 789-793. DOI:10.1109/LGRS.2018.2806223.

  • Yeting Fan, Xiaobin Jin, Le Gan, Laura H.Jessup, Bryan C.Pijanowski, Xuhong Yang, Xiaomin Xiang, Yinkang Zhou. Spatial identification and dynamic analysis of land use functions reveals distinct zones of multiple functions in eastern China. Science of the Total Environment, 2018, 642, 33-44. DOI:10.1016/j.scitotenv.2018.05.383.

  • Yeting Fan, Xiaobin Jin, Xiaomin Xiang, Le Gan, Xuhong Yang, Zhihong Zhang, Yinkang Zhou. Evaluating and predicting the effectiveness of farmland consolidation on improving agricultural productivity in China. Plos One, 2018, 13(6). DOI:10.1371/journal.pone.0198171.

Correspondence

  • Email: ganle@njust.edu.cn; ganle@nju.edu.cn; ganleatlas@gmail.com
  • Office: Ding-xin Building, Nanjing University of Science and Technology
  • Address: School of Computer Science and Engineering, Nanjing University of Science and Technology, Xuanwu District, Nanjing, China.