Hi, my name is Yuhao Wang. I obtained my PhD degree from School of Data Science at City University of Hong Kong on June 2026. It’s my honor to be supervised by Prof. Xiangyu Zhao and worked with fellows in Applied Machine Learning Lab.

Research

I have a broad interest in data science and artificial intelligence. My current research mainly focuses on Recommender System, especially Generative Recommendation, Large Language Model for recommendation, multi-modal recommendation, and multi-scenario modeling. I also worked on Large Reasoning Models, diffusion LLM, and reward model. I also worked as reviewer and PC member in NeurIPS, KDD, SIGIR, ACM MM, TOIS, ICDM, RecSys, CIKM, TKDD, etc.

Award

08/2025: I am offered the Outstanding Academic Performance Award (OAPA) from CityU.

09/2024: I am offered the Outstanding Academic Performance Award (OAPA) from CityU.

08/2024: I am offered an ACM SIGIR Student Travel Awards in CIKM 2024.

08/2023: I am offered the Research Tuition Scholarship from CityU.

06/2023: I am offered a IJCAI 2023 Travel Grant.

05/2023: I am offered a SIGIR 2023 Student Travel Grant.

News

09/2026: Our paper Multi-Task Deep Recommender Systems: A Survey is accepted to ACM Computing Surveys (CSUR).

07/2026: Our paper ‘Empowering Cross-Domain Sequential Recommendation with Hybrid Tokenization and Serial-Parallel Decoding’ is accepted to RecSys 2026 Main Track.

05/2026: Our paper TeaRAG: A Token-Efficient Agentic Retrieval-Augmented Generation Framework is accepted to TOIS.

03/2026: Our paper DeepResearch-9K: A Challenging Benchmark Dataset of Deep-Research Agent is accepted to SIGIR 2026 Resource Track.

11/2025: Our paper Efficient Reasoning via Reward Model is online.

08/2025: Our paper Empowering Large Language Model for Sequential Recommendation via Multimodal Embeddings and Semantic IDs is accepted to CIKM 2025 as Full Research Paper.

08/2025: Our paper Empowering Denoising Sequential Recommendation with Large Language Model Embeddings is accepted to CIKM 2025 as Full Research Paper.

07/2025: I attend SIGIR 2025 on-site in Padova, Italy.

04/2025: Our paper Pre-train, Align, and Disentangle: Empowering Sequential Recommendation with Large Language Models is accepted to SIGIR 2025 full paper track.

10/2024: I attend CIKM 2024 on-site in Boise, Idaho, USA.

09/2024: Our work ‘Multi-Level Graph Knowledge Contrastive Learning’ is accepted to TKDE 2024.

07/2024: Our work ‘Multi-Granularity Modeling in Recommendation: from the Multi-Scenario Perspective’ is accepted to CIKM 2024 PhD Symposium track.

07/2024: Our work HierRec: Scenario-Aware Hierarchical Modeling for Multi-scenario Recommendations is accepted to CIKM 2024.

07/2024: Our work LLM4MSR: An LLM-Enhanced Paradigm for Multi-Scenario Recommendation is accepted to CIKM 2024.

10/2023: Our work Diff-MSR: A Diffusion Model Enhanced Paradigm for Cold-Start Multi-Scenario Recommendation is accepted to WSDM 2024.

08/2023: We hold a tutorial: Joint Modeling in Recommendations: Foundations and Frontiers in IJCAI 2023 in Macau.

04/2023: Our work PLATE: A Prompt-Enhanced Paradigm for Multi-Scenario Recommendations is accepted to SIGIR 2023 full paper track.

04/2023: Our work AutoDPQ: Automated Differentiable Product Quantization Embedding Compression Framework is accepted to SIGIR 2023 short paper track.

02/2023: Our survey Multi-Task Deep Recommender Systems: A Survey is online.

01/2023: Our work Exploration and Regularization of the Latent Action Space in Recommendation with Kuaishou is accepted to WWW 2023.