• 山东大学计算机科学与技术学院教授、博士生导师，教育部“青年长江学者”。其于2010年和2015年分别从华东师范大学和新加坡国立大学获得学士和博士学位，后任新加坡科技研究局资讯通信研究院(Institute for Infocomm Research, A*STAR)研究科学家(2014–2016)。担任CSIG多媒体专委会副秘书长，IJCAI 2023资深程序委员、ACMMM 2023领域主席、ICIMCS2019和ACMMM Asia 2020出版主席。主持国家自然科学青年基金项目、面上项目、科技创新2030-“新一代人工智能”重大项目子课题等国家    级、省部级课题。在多个相关领域的国际顶级学术期刊及会议如 CVPR、ACM MM、ACL、AAAI、IEEE TIP、IEEE TMM等上发表多篇论文，获得2021年山东省科技进步一等奖、2023年山东省技术发明一等奖。

博士/硕士招生说明：

- 欢迎有一定数学基础、编程能力优异，致力于在多媒体信息处理、计算机视觉及机器学习领域开展深入研究的同学报考！

- 2026年招收多媒体信息处理、计算机视觉和机器学习方向的硕士研究生（3+）、博士研究生（1+） （更新时间：2025-07-23）

- 欢迎山东大学强基计划同学联系加入！

- 有进组意愿的同学可以将个人简历发送至gantian@sdu.edu.cn 并抄送科研助理zhangwenchao@sdu.edu.cn，邮件主题备注：申请类别+姓名+学校。

研究方向：

- 社交媒体计算：多模态社交媒体争议检测 ，基于多智能体的民主争议调解， 基于大模型的社区传播预测等；

- 跨模态计算：短视频标签自动生成， 基于自然语言描述的智能视频检索， 智能音频生成等；

- 计算机视觉：无偏场景图生成，恶劣条件下的视觉感知等；

- 多模态大模型：多模态视频预训练，大模型高效部署与优化等。

代表性成果如下：（所有成果详见论文成果）

- 会议论文：

• Harry Cheng, Yangyang Guo, Qingpei Guo, Ming Yang, Tian Gan, Liqiang Nie, ''Social Debiasing for Fair Multi-modal LLMs'', ICCV (CCF-A), 2025

• Tianjiao Xu, Keyi Kong, Jinfei Gao, Jianhua Yin*, Tian Gan*, Liqiang Nie, ''Generative Agents for Multimodal Controversy Detection'', IJCAI (CCF-A), 2025

• Jinfei Gao, Xiao Wang, Tian Gan*, Jianhua Yin, Chuanchen Luo, Liqiang Nie, ''Social Context-Aware Community-Level Propagation Prediction'', SIGIR (CCF-A), 2025

• Tianjiao Xu, Hao Fu, Suiyang Zhang, Jianhua Yin, Tian Gan*, Liqiang Nie, ''Enhancing Democratic Mediation through Norm-Awareness in Generative Agent Societies'', ACM MM (CCF-A), 2025

• Tianjiao Xu, Aoxuan Chen, Yuxi Zhao, Jinfei Gao, Tian Gan*, ''A Chinese Multimodal Social Video Dataset for Controversy Detection'', ACM MM (CCF-A), 2024

• Yutao Chen, Xingning Dong, Tian Gan*, Chunluan Zhou, Ming Yang, Qingpei Guo, ''EVE: Efficient zero-shot text-based Video Editing with Depth Map Guidance and Temporal Consistency Constraints'', IJCAI (CCF-A), 2024

• Tian Gan, Xiao Wang, Yan Sun, Jianlong Wu, Qingpei Guo, Liqiang Nie, ''Temporal Sentence Grounding in Streaming Videos'', ACM MM (CCF-A), 2023

• Xiao Wang, Yaoyu Li, Tian Gan*, Zheng Zhang, Jingjing Lv, Liqiang Nie, ''RTQ: Rethinking Video-language Understanding Based on Image-text Model'', ACM MM (CCF-A), 2023

• Tian Gan^#, Qing Wang^#, Xingning Dong, Xiangyuan Ren, Liqiang Nie, Qingpei Guo, ''CNVid-3.5 M: Build, Filter, and Pre-Train the Large-Scale Public Chinese Video-Text Dataset'', CVPR (CCF-A), 2023

• Jianlong Wu, Haozhe Yang, Tian Gan*, Ning Ding, Feijun Jiang, Liqiang Nie*, ''CHMATCH: Contrastive Hierarchical Matching and Robust Adaptive Threshold Boosted Semi-Supervised Learning'', CVPR (CCF-A), 2023

• Haozhe Yang, Xianqiang Gao, Jianlong Wu, Tian Gan, Ning Ding, Feijun Jiang, Liqiang Nie, ''Self-Adaptive Context and Modal-Interaction Modeling for Multimodal Emotion Recognition'', ACL (CCF-A), 2023

• Xiao Wang, Tian Gan*, Yinwei Wei, Jianlong Wu, Dai Meng, Liqiang Nie, ''Micro-video Tagging via Jointly Modeling Social Influence and Tag Relation'', ACM MM (CCF-A), 2022

• Xingning Dong, Tian Gan*, Xuemeng Song, Jianlong Wu, Yuan Cheng*, Liqiang Nie, ''Stacked Hybrid-Attention and Group Collaborative Learning for Unbiased Scene Graph Generation'', CVPR (CCF-A), 2022

- 期刊论文：

• Xuzheng Yu, Chen Jiang, Xingning Dong, Tian Gan, Ming Yang, Qingpei Guo, ''SHE-Net: Syntax-Hierarchy-Enhanced Text-Video Retrieval'', TCSVT (CCF-B), 2025

• Muhe Ding, Jianlong Wu,  Xue Dong, Xiaojie Li, Pengda Qin, Tian Gan, Liqiang Nie, ''Preview-Based Category Contrastive Learning for Knowledge Distillation'', TCSVT (CCF-B), 2025

• Tianjiao Xu, Xuebo Liu, Derek F. Wong, Yue Zhang, Lidia S. Chao, Min Zhang, Tian Gan, ''Exploiting Multimodal Knowledge Graph for Multimodal Machine Translation'', TMM (CCF-B), 2025

• Xingning Dong, Qingpei Guo, Tian Gan*, Qing Wang, Jianlong Wu, Xiangyuan Ren, Yuan Cheng, Wei Chu, ''SNP-S³: Shared Network Pre-Training and Significant Semantic Strengthening for Various Video-Text Tasks'', TCSVT (CCF-B), 2024

• Jianlong Wu, Wei Sun, Tian Gan*, Ning Ding, Feijun Jiang, Jialie Shen, Liqiang Nie, ''Neighbor-guided consistent and contrastive learning for semi-supervised action recognition'', TIP (CCF-A), 2023

• Shaokun Wang, Tian Gan*, Yuan Liu, Li Zhang, Jianlong Wu, Liqiang Nie, ''Micro-Influencer Recommendation by Multi-Perspective Account Representation Learning'', TMM (CCF-B), 2022

• Yaxin Liu, Jianlong Wu, Leigang Qu, Tian Gan, Jianhua Yin, Liqiang Nie, ''Self-Supervised Correlation Learning for Cross-Modal Retrieval'', TMM (CCF-B), 2022

• Xianjing Han, Xingning Dong, Xuemeng Song, Tian Gan, Yibing Zhan, Yan Yan, Liqiang Nie, ''Divide-and-Conquer Predictor for Unbiased Scene Graph Generation'', TCSVT (CCF-B), 2022

• Shaokun Wang, Tian Gan, Yuan Liu, Zhiyong Cheng, Jianlong Wu, Liqiang Nie, ''Discover Micro-Influencers for Brands via Better Understanding'', TMM (CCF-B), 2021

• Weili Guan, Xuemeng Song, Tian Gan*, Junyu Lin, Xiaojun Chang, Liqiang Nie, ''Cooperation Learning From Multiple Social Networks: Consistent and Complementary Perspectives'', TCYB (CCF-B), 2021

培养学生情况：

• 截至2025年7月，在读博士生3人，在读硕士生7人，已毕业硕士生22人。

• 主要毕业去向：读博深造（如新加坡国立大学、哈工大深圳)、国有企业/央企（电网）、高科技企业（华为、百度、阿里）等。