1. 基本情况：

  敬蒙蒙，男，中共党员，计算机科学与技术专业博士，信息与软件工程学院讲师。

  主要研究迁移学习，零样本学习，跨模态检索等。

  近年来发表20多篇论文，其中CCF-A / 中科院一区Top论文17篇，包括NeurIPS，ICCV，CVPR，TIP等，CCF-B/中科院二区论文3篇，2篇论文引用量进入全球计算机领域前1%，入选ESI高被引论文。所发表论文多次提出了该领域内的原创性概念，如快速域适应，不完整跨模态检索，自适应分量嵌入等。Google学术引用超过1100次，H指数15，累计影响因子超过100，连续3年担任顶会ACM CIKM的程序委员会委员，担任计算机领域多个顶级期刊和会议的审稿人，包括IEEE TPAMI, CVPR, ICCV，TMM等。受邀在第二届CCF全国优秀博士生论坛作口头报告。近年来，主研和参与多项国家自然科学基金重大项目、 国家自然科学基金面上项目及青年基金等各类科研项目。

2. 个人主页：

  学院主页：https://sise.uestc.edu.cn/info/1037/11598.htm

  谷歌学术：https://scholar.google.com.hk/citations?user=gVByeFUAAAAJ&hl=zh-CN

3. 代表性论文： 

  [1] Jing Mengmeng, Zhen Xiantong, Li Jingjing, et al. Order-preserving Consistency Regularization

  for Domain Adaptation and Generalization. ICCV, 2023. CCF-A

  [2] Jing Mengmeng, Zhen Xiantong, Li Jingjing, et al. Variational model perturbation for 

  source-free domain adaptation . NeurIPS, 2023. CCF-A

  [3] Jing Mengmeng, Li Jingjing, Lu Ke, et al. Visually Source-Free Domain Adaptation via 

  Adversarial Style Matching. IEEE Transactions on Image Processing , 2024. 中科院一区Top

  [4] Jing Mengmeng, Zhao Jidong, Li Jingjing, et al. Adaptive Component Embedding for Domain

  Adaptation. IEEE Transactions on Cybernetics , 2021. 中科院一区Top

  [5] Jing Mengmeng, Meng Lichao, Li Jingjing, et al. Adversarial Mixup Ratio Confusion for

  Unsupervised Domain Adaptation. IEEE Transactions on Multimedia,2023. 中科院一区Top

  [6] Jing Mengmeng, Li Jingjing, Zhu Lei, et al. Balanced Open Set Domain Adaptation via Centroid

  Alignment. AAAI, 2021. CCF-A

  [7] Jing Mengmeng, Li Jingjing, Zhu Lei, et al. Incomplete Cross-modal Retrieval with Dual-Aligned

  Variational Autoencoders. ACM Multimedia, 2020. CCF-A

  [8] Jing Mengmeng, Li Jingjing, Lu Ke, et al. Learning explicitly transferable representations for

  domain adaptation. Neural Networks, 2020. 中科院一区Top

  [9] Zuo Lin, Jing Mengmeng, Li Jingjing,et al. Challenging tough samples in unsupervised domain

  adaptation. Pattern Recognition, 2021. 中科院一区Top

  [10] Li Jingjing, Jing Mengmeng, Lu Ke,et al. Locality Preserving Joint Transfer for Domain

  Adaptation. IEEE Transactions on Image Processing, 2019. 中科院一区Top

  [11] Liu Jieyan, Jing Mengmeng, et al. Open Set Domain Adaptation via Joint Alignment and

  Category Separation. IEEE Transactions on  Neural Networks and Learning Systems,2023. 中科院一区

  Top

  [12] Li Jingjing, Jing Mengmeng, Lu Ke, et al. Leveraging the Invariant Side of Generative

  Zero-Shot Learning. CVPR, 2019. CCF-A

  [13] Li Jingjing, Jing Mengmeng, Lu Ke, et al. From Zero-Shot Learning to Cold-Start

  Recommendation. AAAI, 2019. CCF-A

  [14] Li Jingjing, Jing Mengmeng, Lu Ke,et al. Investigating the Bilateral Connections in Generative

  Zero-Shot Learning. IEEE Transactions on Cybernetics , 2021. 中科院一区Top

  [15] Li Jingjing, Jing Mengmeng, Su Hongzu, et al. Faster Domain Adaptation Networks. IEEE

  Transactions on Knowledge and Data Engineering, 2022. 中科院一区Top

  [16] Li Jingjing, Jing Mengmeng, Zhu Lei, et al. Learning Modality-Invariant Latent Representations

  for Generalized Zero-shot Learning. ACM Multimedia, 2020. CCF-A

  [17] Li Jingjing, Jing Mengmeng, Lu Ke, et al. Alleviating Feature Confusion for Generative

  Zero-shot Learning. ACM Multimedia, 2020. CCF-A

  [18] Xie Yue, Du Zhekai, Li Jingjing, Jing Mengmeng, et al. Joint metric and feature representation

  learning for unsupervised domain adaptation. Knowledge Based Systems, 2020. 中科院一区Top

  [19] Ma Ao, You Fuming, Jing Mengmeng, et al. Multi-source domain adaptation with graph

  embedding and adaptive label prediction.Information Processing & Management, 2020. 中科院一区

  Top

  [20] Jing Mengmeng, Li Jingjing, Zhao Jidong, et al. Learning Distribution-Matched Landmarks for

  Unsupervised Domain Adaptation. DASFAA, 2018. CCF-B

  [21] Jing Mengmeng, Li Jingjing, Lu, Ke, et al. Adaptive component embedding for unsupervised

  domain adaptation. ICME, 2019. CCF-B

  [22] Ding Yongqi, Zuo Lin, Jing Mengmeng, et al. Shrinking Your TimeStep: Towards Low-Latency

  Neuromorphic Object Recognition with Spiking Neural Networks. AAAI, 2024. CCF-A

4. 科研项目：

  [1] 面向集成电路封装缺陷检测的视觉领域自适应方法研究，国家自然科学基金面上项目，主研

  [2] 面向跨领域跨模态迁移的自适应机器学习算法研究，国家自然科学基金面上项目，主研

  [3] 协同视觉语义理解和社会媒体分析的关键技术研究，国家自然科学基金面上项目，参研

  [4] 移动交互环境下的大媒体内容分析与检索，国家自然科学基金重点项目，参研

  [5] 深度流形网络机理及其应用研究，国家自然科学基金专项项目，主研

5. 荣誉和奖励：