The mission of LDS is to conduct cutting-edge research that can better “understand and analyze actual phenomena” from data. We work closely on the research fields of information retrieval (SIGIR, WWW, CIKM), data mining (KDD, WSDM), natural language processing (ACL, EMNLP), machine learning (NeurIPS, ICML, ICLR), multimedia (ACM MM, CVPR, ICCV), and more generally, artificial intelligence (AAAI, IJCAI). Current research interests are primarily on deep learning, graph learning, meta learning, and causal inference, with particular applications on recommender systems, dialog systems, knowledge graphs, and financial technologies (Fintech).
Congratulations to Zihao Zhao, Wentao Shi, Tianhao Shi, Yiyan Xu, Yuyue Zhao, Jiayi Liao, Jiaju Chen and all the collaborators for their papers at SIGIR'24 on generative recsys, fairness, causal rec, ood generalization, gnn explanation, etc.
Congratulations to Shuxian Bi, Wentao Shi, Meng Jiang, Junfeng Fang, Yongduo Sui, Yuan Gao, Xinyuan Zhu and all the collaborators for their papers at WWW'24 on LLM-based recommendation, graph condensation, and proactive recommendation.
Congratulations to Sihang Li, Haoxuan Li and all the collaborators for their papers at AAAI'24 on LLM for molecule and recommendation debiasing.
Congratulations to Xingyu Zhu, Jiayi Liao and all the collaborators for their papers at AAAI'24 on few-shot learning and text-to-image generation.