Ming Li

University of Amsterdam

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I am Ming Li (李明), now a Postdoc Researcher at University of Amsterdam (UvA). I got my Ph.D. at IRLab, University of Amsterdam (UvA), supervised by Prof. Dr. Maarten de Rijke and Dr. Andrew Yates. I was a member in AIRLab in collaboration with Ahold Delhaize. I received my bachelor and master degree in Computer Science from University of Electronic Science and Technology of China, UESTC in 2016 and 2019, respectively.

Research Interest: Recommender Systems, Information Retrieval, Retrieval augmented machine learning, LLM.

Ph.D. Research Summary: Collaborated with Europe’s largest retail company (Ahold Delhaize) on recommendation research within the smart retail scenario, resulting in several publications in top-tier conferences/journals (RecSys, SIGIR, TOIS, TORS, etc); some related research findings have been applied to real-world applications.

Current Project: Now, I am currently working on building up the using\&fine-tuning LLM pipeline for Information Retrieval research.

I am on job market now!!! Feel free to contact me!

news

Jan 17, 2024 :tada: Our paper “Domain Generalization in Time Series Forecasting” got accepted at ACM Transactions on Knowledge Discovery from Data!!
Dec 17, 2023 :tada: Our paper “Measuring Item Fairness in Next Basket Recommendation: A Reproducibility Study” got accepted at ECIR’24!!
Sep 27, 2023 :tada: Our paper “Repetition and Exploration in Offline Reinforcement Learning-based Recommendations” got accepted at CIKM’23 Workshop!
Jul 1, 2023 :tada: Our paper “Masked and Swapped Sequence Modeling for Next Novel Basket Recommendation in Grocery Shopping” got accepted at RecSys’23!!
Apr 17, 2023 :tada: Our tutorial proposal “Complex Item Set Recommendation” got accepted at SIGIR’23!!
Apr 17, 2023 :tada: Our paper “Who Will Purchase this Item Next? Reverse Next Period Recommendation in Grocery Shopping” got accepted at ACM Transactions on Recommender Systems!!
Apr 1, 2023 :tada: Our paper “Repetition and Exploration in Sequential Recommendation” got accepted at SIGIR’23!!
Feb 27, 2023 :tada: Our paper “A Next Basket Recommendation Reality Check” got accepted at ACM Transactions on Information Systems (TOIS)!!
Oct 27, 2022 :tada: Our paper “A Personalized Neighborhood-based Model for Within-basket Recommendation in Grocery Shopping” got accepted at WSDM’23!
May 3, 2022 :fire: One patent w.r.t. distributed deep learning framework got granted, check it here.
Apr 1, 2022 :tada: Our paper “ReCANet: A Repeat Consumption-Aware Neural Network for Next Basket Recommendation in Grocery Shopping” got accepted at SIGIR’22!
Nov 17, 2021 :fire: We participanted the TREC 2021 fair ranking track, check our solutions here.
Jul 1, 2021 :fire: I joined AIRLab (inside IRLab) which is a joint UvA-Ahold Delhaize industry lab!
Nov 1, 2020 :fire: I joined IRLab (UvA) as a Ph.D. student working on recommender system, excited to explore this new domain!!

selected publications

  1. Are We Really Achieving Better Beyond-Accuracy Performance in Next Basket Recommendation?
    Ming Li, Yuanna Liu, Sami Jullien, Mozhdeh Ariannezhad, Andrew Yates, and 2 more authors
    In SIGIR 2024: 47th international ACM SIGIR Conference on Research and Development in Information Retrieval, Jul 2024
  2. thesis.png
    Repetition and Exploration in Recommendation
    Ming Li
    In Ph.D. Thesis, Jul 2024
  3. rl4rec.png
    Repetition and Exploration in Offline Reinforcement Learning-based Recommendations
    Ming Li, Jin Huang, and Maarten Rijke
    In CIKM 2023 Workshop on Deep Reinforcement Learning for Information Retrieval, May 2023
  4. fairnbr.png
    Measuring Item Fairness in Next Basket Recommendation: A Reproducibility Study
    Yuanna Liu, Ming Li, Mozhdeh Ariannezhad, Masoud Mansoury, Mohammad Aliannejadi, and 1 more author
    In ECIR 2024: 46th European Conference on Information Retrieval, Mar 2024
  5. timeseries.png
    Domain Generalization in Time Series Forecasting
    Songgaojun Deng, Olivier Sprangers, Ming Li, Sebastian Schelter, and Maarten Rijke
    ACM Transactions on Knowledge Discovery from Data, Mar 2024
  6. nnbr.png
    Masked and Swapped Sequence Modeling for Next Novel Basket Recommendation in Grocery Shopping
    Ming Li, Mozhdeh Ariannezhad, Andrew Yates, and Maarten Rijke
    In RecSys 2023: 17th ACM Conference on Recommender Systems, Sep 2023
  7. resr.png
    Repetition and Exploration in Sequential Recommendation
    Ming Li, Ali Vardasbi, Andrew Yates, and Maarten Rijke
    In SIGIR 2023: 46th international ACM SIGIR Conference on Research and Development in Information Retrieval, Jul 2023
  8. Complex Item Set Recommendation
    Mozhdeh Ariannezhad, Ming Li, Sami Jullien, and Maarten Rijke
    In SIGIR 2023: 46th international ACM SIGIR Conference on Research and Development in Information Retrieval, Jul 2023
  9. rnpr.png
    Who Will Purchase this Item Next? Reverse Next Period Recommendation in Grocery Shopping
    Ming Li, Mozhdeh Ariannezhad, Andrew Yates, and Maarten Rijke
    ACM Transactions on Recommender Systems, Sep 2023
  10. tois-repro.png
    A Next Basket Recommendation Reality Check
    Ming Li, Sami Jullien, Mozhdeh Ariannezhad, and Maarten Rijke
    ACM Transactions on Information Systems, Sep 2023
  11. wsdm-within.png
    A Personalized Neighborhood-based Model for Within-basket Recommendation in Grocery Shopping
    Mozhdeh Ariannezhad, Ming Li, Sebastian Schelter, and Maarten Rijke
    In WSDM 2023: The Sixteenth International Conference on Web Search and Data Mining, Feb 2023
  12. racnet.png
    ReCANet: A Repeat Consumption-Aware Neural Network for Next Basket Recommendation in Grocery Shopping
    Mozhdeh Ariannezhad, Sami Jullien, Ming Li, Min Fang, Sebastian Schelter, and 1 more author
    In SIGIR 2022: 45th international ACM SIGIR Conference on Research and Development in Information Retrieval, Jul 2022
  13. dpplee3.png
    A distributed deep learning framework and method based on Pytorch&Spark
    Ming Li, Mengshu hou, and  al.
    In CN Patent, CN109,032,671 B, Jul 2022