Andy Dong

Andy Dong

Applied Scientist

About Me

I am a Senior Applied Scientist at Amazon. I lead the research and development of LLM-native recommendation architectures, driving advances in generative retrieval via Semantic IDs and foundation model alignment to support next-generation personalization paradigms. My broader research interests center on reasoning and personalization for generative recommendation, retrieval-augmented generation (RAG), and agentic systems, specifically exploring memory context management and computer-use capabilities.

Experience

News

Publications

  1. Graph Collaborative Signals Denoising and Augmentation for Recommendation
    SIGIR
    Ziwei Fan, Ke Xu, Zhang Dong, Hao Peng, Jiawei Zhang, Philip S Yu
    Proceedings of the 46nd International ACM SIGIR Conference (SIGIR), 2023.
  2. Exploring information retrieval for personalized teaching support
    HCII
    Nanjie Rao, Sharon Lynn Chu, Zeyuan Jing, Huan Kuang, Yunjie Tang, Zhang Dong
    International Conference on Human-Computer Interaction (HCII), 2022.
  3. Cross-Document Contextual Coreference Resolution in Knowledge Graphs
    Preprint
    Zhang Dong, Mingbang Wang, Le Dai, Jiyuan Li, Xingzu Liu, Ruilin Nong
    Preprint
  4. End-to-End Dialog Neural Coreference Resolution: Balancing Efficiency and Accuracy in Large-Scale Systems
    Preprint
    Zhang Dong, Songhang deng, Mingbang Wang, Le Dai, Jiyuan Li, Xingzu Liu, Ruilin Nong
    Preprint
  5. Enhancing Coreference Resolution with Pretrained Language Models: Bridging the Gap Between Syntax and Semantics
    Preprint
    Xingzu Liu, Mingbang Wang, Zhang Dong, Le Dai, Jiyuan Li, Ruilin Nong
    Preprint

Services

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