苏宏祖，博士， 西南交通大学计算机与人工智能学院助理教授。2025年6月毕业于电子科技大学计算机科学与技术专业，主要从事推荐系统、迁移学习领域的科研工作，研究方向涉及跨领域数据迁移技术、多模态/跨模态处理技术、生成式推荐系统等。已发表学术论文14篇，其中以第一作者身份在CVPR、SIGIR、AAAI等国际旗舰会议及TOIS、TCSVT等国际旗舰期刊发表论文8篇（含6篇CCF-A类、1篇中科院一区）。发表成果中，相关研究获“2021 CCF-腾讯犀牛鸟优秀项目”认可。担任中科院一区/CCF-A类期刊TKDE、TNNLS、TCSVT及CCF-A/B类会议SIGIR、CVPR、ICCV、AAAI、ACM MM、CIKM等的审稿人。谷歌学术主页：https://scholar.google.com/citations?user=9lABrqUAAAAJ

近期代表性科研成果：

 1. Su H, Meng L, Zhu L, et al. DDPO: Direct Dual Propensity Optimization for Post-Click Conversion Rate Estimation[C]//ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR). 2024. CCF-A.

2. Su H, Li J, Du Z, et al. Cross-domain Recommendation via Dual Adversarial Adaptation[J]. ACM Transactions on Information Systems (TOIS). 2024. CCF-A.

3. Su H, Li J, Chen Z, et al. Distinguishing unseen from seen for generalized zero-shot learning[C]//IEEE/CVF conference on computer vision and pattern recognition (CVPR). 2022. CCF-A.

4. Su H, Du Z, Li J, et al. Cross-domain adaptative learning for online advertisement customer lifetime value prediction[C]//AAAI Conference on Artificial Intelligence (AAAI). 2023. CCF-A.

5.Su H, Li J, Li F, et al. SOIL: Contrastive Second-Order Interest Learning for Multimodal Recommendation[C]// ACM International Conference on Multimedia (MM). 2024. CCF-A.

6. Su H, Li J, Li F, et al. Task-Adversarial Adaptation for Multi-modal Recommendation[C]//ACM International Conference on Multimedia (MM). 2023. CCF-A.

7. Su H, Li J, Lu K, et al. Dual-aligned feature confusion alleviation for generalized zero-shot learning[J]. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2023. 中科院一区. 

8. Su H, Zhang Y, et al. Cross-domain recommendation via adversarial adaptation[C]//ACM international conference on information & knowledge management (CIKM). 2022. CCF-B.