Hello! This is Yizhou Dang (党翌洲 in Chinese). I am currently a third-year Ph.D. student at Software College of Northeastern University, Shenyang, China. I am fortunate to be advised by Prof. Guibing Guo. Before that, I earned my B.E. degree in 2023 at the same institute. I am honored to work closely with Dr. Enneng Yang and Dr. Yuting Liu.

My research interests focus on AI for science (enzyme design) and recommender systems (sequential recommendation and LLM-based recommendation). I am particularly interested in data-centric methods, such as data augmentation and data synthesis.

Please feel free to contact me by email if you have any questions or are seeking collaborations.

🔥 Our team is seeking self-motivated students (including remote internships, undergraduates, graduate students, and other candidates) to join research on recommender systems, LLMs, and AI for science, with the goal of publishing high-quality academic papers. If interested, please email me your resume.

👏 News

📝 Publications

$^{\dagger}$ indicates corresponding author. $^{\star}$ indicates equal contribution.

Surveys

• Data Augmentation for Sequential Recommendation: A Survey
  Yizhou Dang, Enneng Yang, Yuting Liu, Guibing Guo$^{\dagger}$, Linying Jiang, Xingwei Wang$^{\dagger}$, Jianzhe Zhao
  IEEE Transactions on Knowledge and Data Engineering (TKDE), 2026 · Code
  The code repository collects research on data augmentation and contrastive learning for recommendation (700+ papers).

Research Papers

2026

• Exploring and Tailoring the Test-Time Augmentation for Sequential Recommendation
  Yizhou Dang, Enneng Yang, Yuting Liu, Jianzhe Zhao, Xingwei Wang$^{\dagger}$, Guibing Guo$^{\dagger}$
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2026 · Code

• Enhancing Protein Representation Learning via Manifold Restore Mixing
  Yizhou Dang, Chuang Zhao, Lianbo Ma, Guibing Guo, Xingwei Wang, Zhu Sun
  ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2026, In Press · Code

• Pay Attention to Sequence Split: Uncovering the Impacts of Sub-Sequence Splitting on Sequential Recommendation Models
  Yizhou Dang, Yifan Wu, Minhan Huang, Chuang Zhao, Lianbo Ma, Guibing Guo$^{\dagger}$, Xingwei Wang$^{\dagger}$, Zhu Sun
  International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2026 · Code

• Tail-Aware Data Augmentation for Long-Tail Sequential Recommendation
  Yizhou Dang, Zhifu Wei, Minhan Huang, Lianbo Ma, Jianzhe Zhao, Guibing Guo$^{\dagger}$, Xingwei Wang$^{\dagger}$
  The Web Conference (WWW), 2026 · Code

• Repairing and Enriching Heuristic Data Augmentation for Sequential Recommendation
  Yizhou Dang, Chu Zhao, Linying Jiang, Lianbo Ma, Guibing Guo$^{\dagger}$
  Journal of Software (JOS, Chinese journal), 2026, In Press

• Smoothed Intent Learning for Sequential Recommendation
  Yifeng Su$^{\star}$, Yizhou Dang$^{\star}$, Xiaodong Cai$^{\dagger}$, Guibing Guo$^{\dagger}$
  ACM Transactions on Information Systems (TOIS), 2026, In Press

• Fusion and Alignment Enhancement with Large Language Models for Tail-item Sequential Recommendation
  Zhifu Wei, Yizhou Dang, Guibing Guo$^{\dagger}$, Chuang Zhao, Zhu Sun$^{\dagger}$
  International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2026 · Code

• DeCO: A Training-Free Framework for In-Context Knowledge Editing via Incremental Reasoning
  Haoyu Xu, Yuliang Liang, Yizhou Dang, Guibing Guo$^{\dagger}$, Jianzhe Zhao, Linying Jiang, Xingwei Wang
  Knowledge-Based Systems (KBS), 2026, In Press

2025

• Data Augmentation as Free Lunch: Exploring the Test-Time Augmentation for Sequential Recommendation
  Yizhou Dang, Yuting Liu, Enneng Yang, Minhan Huang, Guibing Guo$^{\dagger}$, Jianzhe Zhao$^{\dagger}$, Xingwei Wang
  International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR, Oral), 2025 · Code

• Augmenting Sequential Recommendation with Balanced Relevance and Diversity
  Yizhou Dang, Jiahui Zhang, Yuting Liu, Enneng Yang, Yuliang Liang, Guibing Guo$^{\dagger}$, Jianzhe Zhao$^{\dagger}$, Xingwei Wang
  AAAI Conference on Artificial Intelligence (AAAI, Oral), 2025 · Code

• Beyond Single Sequence: User Correlation Guided Cross-Sequence Mixing for Sequential Recommendation
  Jiahui Zhang$^{\star}$, Yizhou Dang$^{\star}$, Enneng Yang, Jianzhe Zhao, Linying Jiang, Guibing Guo$^{\dagger}$, Xingwei Wang
  Machine Intelligence Research (MIR), 2025 · Code

• Denoising Multi-Interest-Aware Logical Reasoning for Long-Sequence Recommendation
  Fei Li, Qingyun Gao, Yizhou Dang, Enneng Yang, Guibing Guo$^{\dagger}$, Jianzhe Zhao, Xingwei Wang$^{\dagger}$
  International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR, Oral), 2025 · Code

• CoRA: Collaborative Information Perception by Large Language Model’s Weights for Recommendation
  Yuting Liu, Jinghao Zhang, Yizhou Dang, Yuliang Liang, Qiang Liu$^{\dagger}$, Guibing Guo$^{\dagger}$, Jianzhe Zhao, Xingwei Wang
  AAAI Conference on Artificial Intelligence (AAAI, Oral), 2025 · Code

• Multiple Purchase Chains with Negative Transfer Elimination for Multi-Behavior Recommendation
  Shuwei Gong, Yuting Liu, Yizhou Dang, Guibing Guo$^{\dagger}$, Jianzhe Zhao$^{\dagger}$, Xingwei Wang
  AAAI Conference on Artificial Intelligence (AAAI), 2025 · Code

• Towards Unified Modeling for Positive and Negative Preferences in Sign-aware Recommendation
  Yuting Liu, Yizhou Dang, Yuliang Liang, Qiang Liu, Guibing Guo$^{\dagger}$, Jianzhe Zhao, Xingwei Wang
  Database Systems for Advanced Applications (DASFAA, Oral), 2025 · Code

• Self-supervised Hierarchical Representation for Medication Recommendation
  Yuliang Liang, Yuting Liu, Yizhou Dang, Enneng Yang, Guibing Guo$^{\dagger}$, Wei Cai, Jianzhe Zhao, Xingwei Wang
  Database Systems for Advanced Applications (DASFAA, Oral), 2025 · Code

• Harnessing Content and Structure in ID For Multimodal Recommendation
  Yuting Liu$^{\star}$, Enneng Yang$^{\star}$, Yizhou Dang, Guibing Guo$^{\dagger}$, Qiang Liu, Yuliang Liang, Linying Jiang, Xingwei Wang
  IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2025 · Code

2024

• Efficient and Adaptive Recommendation Unlearning: A Guided Filtering Framework to Erase Outdated Preferences
  Yizhou Dang$^{\dagger}$, Yuting Liu, Enneng Yang, Guibing Guo, Linying Jiang, Jianzhe Zhao, Xingwei Wang
  ACM Transactions on Information Systems (TOIS), 2024 · Code

• Repeated Padding for Sequential Recommendation
  Yizhou Dang, Yuting Liu, Enneng Yang, Guibing Guo, Linying Jiang, Xingwei Wang$^{\dagger}$, Jianzhe Zhao$^{\dagger}$
  ACM Conference on Recommender Systems (RecSys, Oral), 2024 · Code

2023

• TiCoSeRec: Augmenting Data to Uniform Sequences by Time Intervals for Effective Recommendation
  Yizhou Dang, Enneng Yang, Guibing Guo$^{\dagger}$, Linying Jiang, Xingwei Wang$^{\dagger}$, Xiaoxiao Xu, Qinghui Sun, Hong Liu
  IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023 · Code

• Uniform Sequence Better: Time Interval Aware Data Augmentation for Sequential Recommendation
  Yizhou Dang, Enneng Yang, Guibing Guo$^{\dagger}$, Linying Jiang, Xingwei Wang$^{\dagger}$, Xiaoxiao Xu, Qinghui Sun, Hong Liu
  AAAI Conference on Artificial Intelligence (AAAI, Oral), 2023 · Code · Video · 中文解读

📖 Educations

• 2023.09 - 2028.06 (Expected), Ph.D. in Software Engineering, Northeastern University, Shenyang, China.
• 2019.09 - 2023.06, Bachelor in Software Engineering, Northeastern University, Shenyang, China.

🏆 Honors and Awards

• 2026  SIGIR Student Travel Grant
• 2025  Young Talent Support Program for Doctoral Students, CAST (中国科协青年科技人才培育工程博士生专项计划)
• 2023  National Scholarship for Graduate Student (Top 1%)
• 2022,2023  First-Class Scholarship from NEU
• 2022  AAAI Student Scholarship
• 2022  Baidu App User Experience Analysis Competition, First Prize
• 2022  Ministry of Education - Huawei Intelligent Foundation Future Stars
• 2021,2022  Huawei Intelligent Foundation Scholarship
• 2020  Outstanding Student of NEU

💻 Service

• Conference Reviewers:
  • SIGIR 2026
  • AAAI 2026
  • IJCAI 2025, 2026
  • KDD 2024, 2026
• Journal Reviewers:
  • IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
  • IEEE Transactions on Knowledge and Data Engineering (TKDE)
  • ACM Transactions on Information Systems (TOIS)
  • ACM Transactions on Recommender Systems (TORS)

👨‍🎓 Mentorships

• Minhan Huang (2024.09-)  B.E. from NEU; now M.S. at NEU
• Yifeng Su (2024.11-)  M.S. from GUET; incoming Ph.D. at JLU
• Zhifu Wei (2024.12-2026.02)  B.E. from NEU
• Yifan Wu (2025.02-2026.02)  B.E. from NEU
• Yiming Zheng (2025.11-)  B.E. from NEU