Scholar

Ming Li

Google Scholar ID: Rj4kkjkAAAAJ

IRLab, University of Amsterdam

Recommender SystemsLLMInformation Retrieval

Citations & Impact

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Citations

310

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Publications

Co-authors

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Publications

20 items

Browse publications on Google Scholar (top-right) ↗

Resume (English only)

Academic Achievements

Papers published: 'Domain Generalization in Time Series Forecasting' accepted at ACM Transactions on Knowledge Discovery from Data; 'Measuring Item Fairness in Next Basket Recommendation: A Reproducibility Study' accepted at ECIR’24; 'Repetition and Exploration in Offline Reinforcement Learning-based Recommendations' accepted at CIKM’23 Workshop; 'Masked and Swapped Sequence Modeling for Next Novel Basket Recommendation in Grocery Shopping' accepted at RecSys’23; 'Who Will Purchase this Item Next? Reverse Next Period Recommendation in Grocery Shopping' accepted at ACM Transactions on Recommender Systems; 'Repetition and Exploration in Sequential Recommendation' accepted at SIGIR’23; 'A Next Basket Recommendation Reality Check' accepted at ACM Transactions on Information Systems (TOIS); 'A Personalized Neighborhood-based Model for Within-basket Recommendation in Grocery Shopping' accepted at WSDM’23; 'ReCANet: A Repeat Consumption-Aware Neural Network for Next Basket Recommendation in Grocery Shopping' accepted at SIGIR’22; Patent: One patent w.r.t. distributed deep learning framework got granted.

Research Experience

Currently a Postdoc Researcher at the University of Amsterdam. Was a member of AIRLab in collaboration with Ahold Delhaize. Now working on building up the using&fine-tuning LLM pipeline for Information Retrieval research.

Education

Received bachelor and master degrees in Computer Science from University of Electronic Science and Technology of China (UESTC) in 2016 and 2019, respectively. Obtained a Ph.D. at IRLab, University of Amsterdam (UvA), supervised by Prof. Dr. Maarten de Rijke and Dr. Andrew Yates.

Background

Research Interests: 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.

Miscellany