About Me
Dr. Yaqing Wang is currently an Associate Professor at the Beijing Institute of Mathematical Sciences and Applications (BIMSA). She received her Ph.D. in Computer Science and Engineering from the Hong Kong University of Science and Technology in 2019, under the supervision of Professor Lionel M. Ni and Prof. James T. Kwok. From 2019 to 2024, she worked as a Staff Researcher at Baidu Research. Dr. Wang has published more than 30 papers in top-tier international conferences and journals, including NeurIPS, ICML, ICLR, KDD, TheWebConf, SIGIR, AAAI, IJCAI, EMNLP, TPAMI, JMLR, and TIP, with more than 5300 citations. Dr. Wang was named to the World’s Top 2% Scientists List in 2024 and 2025. She was selected for the Beijing Nova Program in 2025. She was also selected into the AAAI-26 New Faculty Highlights Program.
Research Interests
Dr. Yaqing Wang’s research focuses on machine learning, artificial intelligence, and data science. She strives to develop refined, data-efficient, and cost-effective scientific solutions to real-world problems.
Her current research interests include:
- Few-shot learning, meta-learning, and in-context learning
- Large language models and agents
- Cold-start recommendation and user modeling
- AI for Science and Mathematics (AI + X)
Recruiting
We are always looking for talented and highly motivated students and postdoctoral researchers to join our team:
- Postdoctoral Positions through the Tsinghua–BIMSA Joint Program
- Ph.D. Positions through the RUC–BIMSA Joint Program
Students from Qiuzhen College, Tsinghua University are especially encouraged to get in touch.
Please check here for more details.
🎉 News
2025.12: Our work on “Multifaceted Curriculum Learning on Heterogeneous Graphs” has been accepted to Neural Networks.
2025.11: I am selected into the AAAI-26 New Faculty Highlights Program (the only invited speaker from Mainland China among the 23 selected worldwide).
2025.11: Our work on “Graph-Based In-Context Example Selection for Multi-Step Reasoning” has been accepted to AAAI 2026.
2025.10: I am invited to be an Action Editor of Neural Networks.
2025.10: I am invited to be an Area Chair of ACL Rolling Review.
2025.09: Our work on “Learning to Learn with Contrastive Meta-Objective” has been accepted to NeurIPS 2025, seleted as an Oral (Top 0.4%).
2025.09: Our work on “Personalized Agent” has been accepted to NeurIPS 2025.
2025.08: Our work on “In-Context Example Selection for Multi-Level Sentiment Analysis” has been accepted to EMNLP 2025.
2025.06: I am selected for the Beijing Nova Program.
2025.05: Our work on “Personalized Multi-Scenario Matching” has been accepted to KDD 2025.
2025.01: Our work on “Understanding in-context learning for few-shot generalization” has been accepted to ICLR 2025.