基本信息

张玲玲 副教授 博士生导师

西安交通大学计算机科学与技术系

 陕西省天地网技术重点实验室

联系方式

 邮箱:zhanglling@xjtu.edu.cn

 地址:西安交通大学兴庆校区

            彭康楼228

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2024,西安自动化学会青年人才托举

2023,CCF-科技进步一等奖

2023,西安交通大学优秀研究生导师团队

2022, “互联网+”国赛金奖项目指导教师

2022,西安交通大学优秀博士学位论文

2021,全国知识图谱与语义计算大会CCKS最佳论文资源奖

2020,西安交通大学优秀博士毕业生

2020,徐宗本应用数学论文奖

2020,华为奖学金

2019,国睿奖学金

2016,蒋震奖学金

2013,谷歌女性奖学金

2012,国家奖学金

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隶属于郑庆华教授团队(跨媒体知识融合与工程应用研究所、陕西省天地网技术重点实验室)。近年来,主持各类科研项目10项,包括NSFC青年项目、NSFC重大项目子课题、CCF-联想蓝海基金、研究生教学改革重点项目博士后面上项目TPAMICVPRTIPTKDETCSVT、计算机研究与发展等高水平期刊会议发表一作或通讯论文17篇,申请发明专利10项,出版中英文学术著作3部。研究方向:小样本与零样本学习、计算机视觉、知识图谱、智慧教育。

 

招生信息:

常年招收计算机、软件、自动化、网安、物联网等方向的硕士生和博士生,也欢迎本科生加入课题组。

研究领域

  • 2023/01~至今西安交通大学计算机科学与技术系,副教授,博士生导师

  • 2020/07~2022/12,西安交通大学计算机科学与技术系,助理教授

  • 2018/092019/9,美国卡耐基梅隆大学计算机学院,访问学生

  • 2015/092020/06西安交通大学计算机科学与技术系,博士

  • 2011/092015/06,西安交通大学计算机科学与技术系,本科

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2023:

  • Fangzhi Xu, Jun Liu, Qika Lin, Tianzhe Zhao, Jian Zhang, Lingling Zhang, Mind Reasoning Manners: Enhancing Type Perception for Generalized Zero-shot Logical Reasoning over Text, IEEE TNNLS, 2023, Accepted.
  • 潘雨黛、张玲玲、蔡忠闵*、赵天哲、魏笔凡、刘均,基于大规模语言模型的知识图谱可微规则抽取,计算机科学与探索,2023.
  • 郑庆华、张玲玲、龚铁梁、刘欢. 大数据知识工程, 科学出版社, 2023.
  • Yaxian Wang, Bifan Wei, Jun Liu, Lingling Zhang, Jiaxin Wang, Qianying Wang, DisAVR: Disentangled Adaptive Visual Reasoning Network for Diagram Question Answering, IEEE TIP, 2023, Accepted.
  • Yudai Pan, Jun Liu*, Lingling Zhang, Yi Huang, Incorporating logic rules with textual representations for interpretable knowledge graph reasoning, Knowledge-Based Systems,2023.
  • Xin Hu, Lingling Zhang*, Jun Liu, Xinyu Zhang, Wenjun Wu, Qianying Wang. Diagram Visual Grounding: Learning to See with Gestalt-Perceptual Attention, IJCAI, 2023.
  • Fangzhi Xu, Qika Lin, Jun Liu, Lingling Zhang, Tianzhe Zhao, Qi Chai, Yudai Pan, Yi Huang, Qianying Wang. MoCA: Incorporating Domain Pretraining and Cross Attention for Textbook Question Answering, Pattern Recognition, 2023(140): 109588.
  • Lingling Zhang, Xinyu Zhang, Qianying Wang, Wenjun Wu, Xiaojun Chang, Jun Liu, RPMG-FSS: Robust Prior Mask Guided Few-Shot Semantic Segmentation, IEEE TCSVT, 2023.
  • Yaxian Wang,  Jun Liu, Ma jie,  Hongwei Zeng, Lingling Zhang, Junjun Li, Dynamic Dual Graph Networks for Textbook Question Answering, Pattern Recognition, 2023.
  • 郑庆华, 刘欢, 龚铁梁, 张玲玲, 刘均. 大数据知识工程发展现状与未来展望, 中国工程科学, 2023, 已录用.
  • Xin Hu, Lingling Zhang*, Jun Liu, Jinfu Fan,  Yang You, Yaqiang Wu. GPTR: Gestalt-Perception Transformer for Diagram Object Detection. AAAI 2023.

 

2022:

  • Yaxian Wang, Bifan Wei, Jun Liu, Qika Lin, Lingling Zhang, Yaqiang  Wu, Spatial-Semantic Collaborative Graph Network for Textbook Question Answering, IEEE TCSVT, 2022, Accepted.
  • Jiaxin Wang, Lingling Zhang*, Jun Liu, Kunming Ma, Wenjun Wu, Xiang Zhao, Yaqiang Wu, Yi Huang. TGIN: Translation-Based Graph Inference Network for Few-Shot Relational Triplet Extraction. IEEE Transactions on Neural Networks and Learning Systems, 2022, Accepted.
  • Yudai Pan, Jun Liu, Lingling Zhang, Tianzhe Zhao, Qika Lin, Xin Hu and Qianying Wang. Inductive Relation Prediction with Logical Reasoning Using Contrastive Representations. EMNLP 2022.
  • Jiaxin Wang, Lingling Zhang*, Jun Liu, Liang Xi, Yujie Zhong and Yaqiang Wu. MatchPrompt: Prompt-based Open Relation Extraction with Semantic Consistency Guided Clustering. EMNLP 2022.
  • Lingling Zhang, Xiaojun Chang, Jun Liu, Minnan Luo, Zhihui Li, Lina Yao, and Alex Hauptmann, TN-ZSTAD: Transferable Network for Zero-Shot Temporal Activity Detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022, Accepted.
  • Lingling Zhang, Shaowei Wang, Jun Liu*, Xiaojun Chang, Qika Lin, Yaqiang Wu, and Qinghua Zheng. MuL-GRN: Multi-Level Graph Relation Network for Few-Shot Node Classification,IEEE Transactions on Knowledge and Data Engineering, 2022, Accepted.
  • Fangzhi Xu, Jun Liu, Qika Lin, Yudai Pan and Lingling Zhang. Logiformer: A Two-Branch Graph Transformer Network for Interpretable Logical Reasoning, SIGIR 2022.
  • Qika Lin, Jun Liu, Fangzhi Xu, Yudai Pan, Yifan Zhu, Lingling Zhang and Tianzhe Zhao. Incorporating Context Graph with Logical Reasoning for Inductive Relation Prediction, SIGIR 2022.
  • Shaowei Wang, Linging Zhang*, Xuan Luo, Yi Yang, Xin Hu, Tao Qin*, Jun Liu, Computer Science Diagram Understanding with Topology Parsing, ACM Transactions on Knowledge Discovery from Data (TKDD), 2022.

2021:

  • Qika Lin; Jun Liu, Lingling Zhang*, Yudai Pan, Xin Hu, Fangzhi Xu, Hongwei Zeng, Contrastive Graph Representations for Logical Formulas Embedding, IEEE Transactions on Knowledge and Data Engineering, 2021, Accepted.
  • 张玲玲*,、陈一苇、吴文俊、魏笔凡、罗炫、常晓军、刘均,基于对比约束的可解释小样本学习,计算机研究与发展,2021(已录用).
  • Shaowei Wang, Lingling Zhang*, Yi Yang, Xin Hu, Tao Qin, Bifan Wei, Jun Liu, CSDQA: Diagram Question Answering in Computer Science, China Conference on Knowledge Graph and Semantic Computing. Springer, Singapore, 2021: 274-280. (最佳论文资源奖)
  • Wenjun Wu, Lingling Zhang*, Yiwei Chen, Xuan Luo, Bifan Wei, Jun Liu, Fuzzy c-Means Clustering with Discriminative Projection, ICBK 2021
  • Xin Hu, Lingling Zhang*, Jun Liu, Qinghua Zheng, Jianlong Zhou, Fs-DSM: Few-Shot Diagram-Sentence Matching via Cross-Modal Attention Graph Model, IEEE Transactions on Image Processing, 2021, Accepted.
  • 蔺奇卡、张玲玲*、刘均、赵天哲,基于问句感知图卷积的教育知识库问答方法,计算机科学与探索,2021.
  • 郑庆华、刘均、魏笔凡、张玲玲. 知识森林:理论、方法与实践, 科学出版社, 2021.
  • Jun Liu, Lingling Zhang, Bifan Wei, Qinghua Zheng. Virtual Teaching Assistants: Technologies, Applications and Challenges. In: Fang Chen, Jianlong Zhou (Eds.), Humanity Driven AI: Productivity, Well-being, Sustainability and Partnership, Springer, 2021.
  • Qika Lin, Jun Liu, Yudai Pan, Lingling Zhang, Xin Hu, Jie Ma. Rule-Enhanced Iterative Complementation for Knowledge Graph Reasoning, Information Sciences, 2021, Accepted.
  • Lingling Zhang, Shaowei Wang, Xiaojun Chang, Jun Liu, Zongyuan Ge, and Qinghua Zheng. Auto-FSL: Searching the Attribute Consistent Network for Few-Shot Learning, IEEE Transactions on Circuits and Systems for Video Technology, 2021, Accepted.
  • Jinzhi Liao, Xiang Zhao, Xibyi Li, Lingling Zhang, Jiuyang Tang, Learning Discriminative Neural Representations for Event Detection, SIGIR, 2021.

2020年之前:

  • Ning Wang, Minnan Luo, Kaize Ding, Lingling Zhang, Jundong Li, Qinghua Zheng,  Graph Few-shot Learning with Attribute Matching, CIKM, 2020.
  • Lingling Zhang, Xiaojun Chang, Jun Liu, Sen Wang, Zongyuan Ge, Minnan Luo, Alexander Hauptmann, ZSTAD: Zero-Shot Temporal Activity Detection, CVPR,2020.
  • Xin Hu, Jun Liu, Jie Ma, Yudai Pan, Lingling Zhang, Fine-grained 3D-Attention Prototypes for FewShot Learning, Neural Computation, 2020.
  • Lingling Zhang, Xiaojun Chang, Jiu Liu, Minnan Luo, and Alexander G. Hauptmann, Few-Shot Activity Recognition with Cross-Modal Memory Network, Pattern Recognition, 2020. (CCF B)
  • Lingling Zhang, Minnan Luo, Zhihui Li, Feiping Nie, Huangxiang Zhang, Jun Liu, Qinghua Zheng. Large Scale Robust Semi-supervised Classification, IEEE Transactions on Cybernetics, 2018, 49(3): 907-917. (CCF B)
  • Lingling Zhang, Minnan Luo, Jun Liu, Xiaojun Chang, Yi Yang, and Alexander G. Hauptmann. Deep Top-k Ranking for Image-Sentence Matching, IEEE Transactions on Multimedia, 2019. (CCF B)
  • Lingling Zhang, Jun Liu, Minnan Luo, Xiaojun Chang, Qinghua Zheng, and Alexander G. Hauptmann. Scheduled Sampling for One-Shot Learning via Matching Network, Pattern Recognition, 2019. (CCF B)
  • Lingling Zhang, Jun Liu, Minnan Luo, Xiaojun Chang, Qinghua Zheng. Deep Semi-supervised Zero-shot Learning with Maximum Mean Discrepancy. Neural Computation, 2018, 30(5), 1426-1447. (CCF B)  
  • Lingling Zhang, Minnan Luo, Jun Liu, Zhihui Li, Qinghua Zheng. Diverse fuzzy c-means for image clustering, Pattern Recognition Letter, 2018.
  • Minnan Luo, Lingling Zhang, Feiping Nie, Xiaojun Chang, Buyue Qian, Qinghua Zheng. Adaptive Semi-supervised Learning with Discriminative Least Squares Regression, In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), 2017. (CCF A类会议)
  • Minnan Luo, Lingling Zhang, Jun Liu and Qinghua Zheng, Distributed Extreme Learning Machine with Alternating Direction Method of Multiplier, Neurocomputing, 2017, 261, 164-170. 
  • Lingyun Song, Minnan Luo, Jun Liu, Lingling Zhang, Haifei Li, Qinghua Zheng, Sparse Multi-Modal Topical Coding for Image Annotation, Neurocomputing, 2016, 214, 162-174.