Donglin Zhou

Recommendation Algorithm Engineer · Recommender Systems / LLM Applications · 2733824402@qq.com · GitHub · Google Scholar · LinkedIn

Education

• M.S., College of Computer Science and Software Engineering, Shenzhen University, 2023.09-2026.06. Computer Science and Technology; advised by Prof. Weike Pan; SIGIR 2026, KDD 2025 and FCS recommendation research was conducted during my master's studies; GPA 3.60/4.0.
• B.E. in Computer Science and Technology, Shantou University, 2019.09-2023.06; GPA 4.24/5.0; advised by Prof. Lin Zheng.

Selected Publications

1. LLM-based Semantic and ID Representations for Sequential Recommendation. Donglin Zhou, Weike Pan, Zhong Ming. Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 4403-4408, 2026. DOI · Code.
2. LLM-Aligned Geographic Item Tokenization for Local-Life Recommendation. Hao Jiang, Guoquan Wang, Donglin Zhou, Sheng Yu, Yang Zeng, Wencong Zeng, Kun Gai, Guorui Zhou. Proceedings of the AAAI Conference on Artificial Intelligence, 40(17), pp. 14928-14936, 2026. DOI · Code.
3. TencentLLMEval: A Hierarchical Evaluation of Real-World Capabilities for Human-Aligned LLMs. Shuyi Xie, Wenlin Yao, Yong Dai, Shaobo Wang, Zishan Xu, Fan Lin, Donglin Zhou, et al.. ACM Transactions on Intelligent Systems and Technology, 17(4), pp. 1-22, 2026. DOI.
4. Contrastive Text-enhanced Transformer for Cross-Domain Sequential Recommendation. Donglin Zhou, Xinbei Cai, Weike Pan. Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp. 4110-4119, 2025. DOI · Code.
5. Self-Supervised Representation Learning with ID-Content Modality Alignment for Sequential Recommendation. Donglin Zhou, Weike Pan, Zhong Ming. Frontiers of Computer Science, 20(12), 2025. DOI · Code.
6. Attenuated Sentiment-aware Sequential Recommendation. Donglin Zhou, Zhihong Zhang, Yangxin Zheng, Zhenting Zou, Lin Zheng. International Journal of Data Science and Analytics, 16(2), pp. 271-283, 2023. DOI · Code.

Industry Experience

• Vipshop, Recommendation Algorithm Engineer, 2026.07-Present: recommender systems for e-commerce.
• Kuaishou, Recommendation Algorithm Intern, 2025.04-2025.11: semantic item IDs, POI representations and behavior sequence modeling for local-life ranking; this research later appeared at AAAI 2026; two projects launched.
• Tencent TEG, Data Engineering/Algorithm Intern, 2023.06-2023.08: conducted the TencentLLMEval work in August 2023 on Hunyuan LLM evaluation, automatic evaluation prompts, model deployment and benchmark construction; the paper was published in ACM TIST in August 2026.

Research Areas

LLM-based recommendation, multimodal and cross-domain recommendation, generative recommendation, semantic item tokenization, and LLM evaluation.

Skills

Python, PyTorch, RecBole, sequential recommendation, semantic ID, RQ-VAE, MMoE ranking, contrastive learning, SFT/QLoRA, DPO, GRPO, RLVR, vLLM.