I am conducting research in the field of recommender systems, specifically focusing on generative recommendation models and sequential recommendation tasks. If you are interested in any of my current or previous research and would like to collaborate or discuss further, please feel free to contact me at qu@cmu.iit.tsukuba.ac.jp. You can find an overview of my work below.
I am currently a third-year Ph.D. student in the Doctoral Program in Intelligent and Mechanical Interaction Systems at the Graduate School of Science and Technology, University of Tsukuba (筑波大学知能機能システム学位プログラム), under the supervision of Prof. Hajime Nobuhara (延原 肇). I also obtained my Master’s degree in the same program at the University of Tsukuba, where I began my research on recommender systems and deep learning. Before coming to Japan, I completed my undergraduate studies at Jilin University, earning a bachelor’s degree in Computer Science from the College of Computer Science and Technology. Now, I am a member of the Computational Intelligence and Multimedia Laboratory (計算知能・マルチメディア研究室). You can find more information on our lab homepage: nobuharaken.com.
My research interests include recommender systems, explainable recommendations with NLG, and generative approaches for sequential recommendation.
🔥I am actively looking for positions as a Machine Learning Engineer, Research Scientist, or Data Scientist, where I can apply my expertise in recommender systems and machine learning!!!🔥
📢 News
- 2025.04: 🎉 A research paper has been accepted to SIGIR 2025 (Full Paper Track).
- 2024.12: 🎉 A research paper has been accepted to ICONIP 2024 (Oral).
- 2024.04: 🎉 A journal paper has been accepted to IEEE Access.
- 2023.04: I was selected to participate in the JST SPRING (Next Generation Research Fellowship) program.
📝 Publications
Intent-aware Diffusion with Contrastive Learning for Sequential Recommendation |
Yuanpeng QU, Hajime NOBUHARA
- Proposed InDiRec, a contrastive learning framework that combines intent clustering and conditional diffusion to generate semantically aligned augmented views for sequence representation learning.
Intent Representation Learning for Sequential Recommendation via Latent Guided Diffusion
Yuanpeng QU, Hajime NOBUHARA
- Proposed LGD4Rec, a generative framework that combines VAE-based latent space encoding and diffusion modeling, enabling efficient and controllable item sequence generation.
Generating Explanations for Explanable Recommendations Using Filter-Enhanced Time-Series Information |
Yuanpeng QU, Hajime NOBUHARA
- Proposed TSIER, a Transformer-based model with an FFT-based filter layer to denoise user histories and generate interpretable explanations for sequential recommendations.
Explanation Generated for Sequential Recommendation based on Transformer model
Yuanpeng QU, Hajime NOBUHARA
- Proposed EG4SRec, a Transformer-based model with a modified attention layer to catch the representation of user histories and generate explanations for sequential recommendations.
🎖 Honors and Awards
- 2023.04 Selected for the JST SPRING Program (Next-Gen Research Fellowship).
- 2022.11 Won the Best Student Presentation Award at the international conference SCIS&ISIS 2022.
- 2020.07 Selected as an Outstanding Graduate.
- 2020.01 Awarded First-Class Scholarship for three consecutive years, 2017– 2020.
- 2020.01 Received the Outstanding Student Award for three consecutive years, 2017– 2020.
- 2019.07 Received the Excellence Award in the Magang Cup National Undergraduate Logistics Competition.
📖 Educations
- 2023.04 - 2026.03 (Expected), Doctoral Program in Intelligent and Mechanical Interaction Systems, Graduate School of Science and Technology, University of Tsukuba.「筑波大学大学院 システム情報工学研究群 知能機能システム学位プログラム 博士後期課程」
- 2021.04 - 2023.03, Intelligent and Mechanical Interaction Systems, Graduate School of Science and Technology, University of Tsukuba. (Master of Engineering)「筑波大学大学院 システム情報工学研究群 知能機能システム学位プログラム 博士前期課程」
- 2016.09 - 2020.07, Computer Science and Technology, College of Computer Science and Technology, Jilin University. (Bachelor of Engineering)「吉林大学 计算机科学与技术学院 计算机科学与技术」
💻 Projects
- 2023.01 - 2023.08, Matrix Factorization-based Job Recommendation System. (R&D)
- 2022.06 - 2023.03, Smart Plant Pot R&D. (TOA Industry Co.,Ltd. R&D)
- 2019.06 - 2020.10, Full-Stack Development for Web-Based Systems. (Contest, Independent Project)