Dr Shuai Wang
Research Fellow
School of Electrical Engineering and Computer Science
Researcher biography
Shuai Wang is a Research Fellow at ielab, The University of Queensland, working on AI-powered search. He builds systems that find information and answer questions, using large language models and retrieval-augmented generation (RAG), and he focuses on making those systems faster and cheaper to run. His broader research contributions span federated search optimization and improving model efficiency in IR and retrieval-augmented generation (RAG) applications. His work has been published at premier venues including SIGIR, ECIR, WSDM, and EMNLP. He has served on program committees for SIGIR, ECIR, ICTIR, and TOIS. A lot of his work comes back to one practical question: how do we get good search and reliable answers without depending on expensive, closed commercial AI?
Shuai has published 25+ papers at venues such as SIGIR, WSDM, ECIR, and EMNLP. He coordinates and teaches INFS7410 (Information Retrieval and Web Search) at UQ.
Shuai completed his PhD on automating medical systematic reviews using neural retrieval systems and generative models (thesis: AI-driven Automated Systematic Reviews). His doctoral work encompassed automatic MeSH term suggestion, screening prioritization, seed-driven retrieval methods, and automatic Boolean query formulation.
Education
- PhD, The University of Queensland (2021–2025)
- Master's degree, The University of Queensland (2020–2021)
- Bachelor's degree, The University of Western Australia (2017–2019)
Book Chapter
Zhuang, Shengyao, Wang, Shuai, Zheng, Fabio, Koopman, Bevan and Zuccon, Guido (2026). A simple sketch of a disposable coffee cup with a lid. The cup features a green circle in the center, possibly representing a logo or design element. The drawing is outlined in black with minimal detail. Starbucks: Improved Training for 2D Matryoshka Embeddings. Lecture Notes in Computer Science. (pp. 67-82) Cham: Springer Nature Switzerland. doi: 10.1007/978-3-032-21289-4_5
Journal Articles
MacAvaney, Sean, Roegiest, Adam, Lipani, Aldo, Parry, Andrew, Engelmann, Björn Engelmann, Kreutz, Christin Katharina, Meng, Chuan, Frayling, Erlend, Yang, Eugene, Schlatt, Ferdinand, Faggioli, Guglielmo, Scells, Harrisen, Atanassova, Iana, Friese, Jana, Bevendorff, Janek, Sanz-Cruzado, Javier, Trippas, Johanne, Pathak, Kanaad, Dhole, Kaustubh, Azzopardi, Leif, Fröbe, Maik, Bertin, Marc, Prasad, Nishchal, Zerhoudi, Saber, Wang, Shuai, Chatterjee, Shubham, Jaenich, Thomas, Kruschwitz, Udo, Wang, Xi and Long, Zijun (2024). Report on the Collab-a-Thon at ECIR 2024. ACM SIGIR Forum, 58 (1), 1-11. doi: 10.1145/3687273.3687287
Wang, Shuai, Scells, Harrisen, Koopman, Bevan and Zuccon, Guido (2022). Automated MeSH term suggestion for effective query formulation in systematic reviews literature search. Intelligent Systems with Applications, 16 200141, 1-14. doi: 10.1016/j.iswa.2022.200141
Conference Papers
Wang, Shuai, Scells, Harrisen, Koopman, Bevan and Zuccon, Guido (2026). AutoBool: Reinforcement-Learned LLM for Effective Automatic Systematic Reviews Boolean Query Generation. Stroudsburg, PA, USA: Association for Computational Linguistics. doi: 10.18653/v1/2026.eacl-long.68
Koopman, Bevan, Li, Hang, Wang, Shuai and Zuccon, Guido (2026). EvalugatorA stylized green crocodile with a yellow grid pattern on its back, resembling a calculator. The design combines elements of a crocodile and a calculator, symbolizing a playful or creative concept.—Rapid, Agile Development and Evaluation of Retrieval Augmented Generation Systems Without Labels. Springer Science and Business Media Deutschland GmbH. doi: 10.1007/978-3-032-21321-1_8
Wang, Shuai, Scells, Harrisen, Koopman, Bevan and Zuccon, Guido (2025). Reassessing Large Language Model Boolean query generation for systematic reviews. 48th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR 2025), Padua, Italy, 13-18 July 2025. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3726302.3730329
Wang, Shuai, Zhuang, Shengyao, Koopman, Bevan and Zuccon, Guido (2025). 2D Matryoshka Training for Information Retrieval. 48th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR 2025), Padua, Italy, 13-18 July 2025. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3726302.3730330
Yao, Zheng, Wang, Shuai and Zuccon, Guido (2025). Pre-training vs. Fine-tuning: A Reproducibility Study on Dense Retrieval Knowledge Acquisition. 48th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR 2025), Padua, Italy, 13-18 July 2025. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3726302.3730332
Wang, Shuai, Zhuang, Shengyao, Koopman, Bevan and Zuccon, Guido (2025). ReSLLM: large language models are strong resource selectors for federated search. The ACM Web Conference 2025, Sydney, NSW Australia, 28 April-2 May 2025. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3701716.3715595
Sun, Shuoqi, Zhuang, Shengyao, Wang, Shuai and Zuccon, Guido (2025). An investigation of prompt variations for zero-shot LLM-based rankers. 47th European Conference on Information Retrieval, Lucca, Italy, 6-10 April 2025. Cham, Switzerland: Springer Cham. doi: 10.1007/978-3-031-88711-6_12
Fröbe, Maik, Parry, Andrew, Scells, Harrisen, Wang, Shuai, Zhuang, Shengyao, Zuccon, Guido, Potthast, Martin and Hagen, Matthias (2025). Corpus subsampling: estimating the effectiveness of neural retrieval models on large corpora. 47th European Conference on Information Retrieval, Lucca, Italy, 6-10 April 2025. Cham, Switzerland: Springer Cham. doi: 10.1007/978-3-031-88708-6_29
Rau, David, Wang, Shuai, Déjean, Hervé, Clinchant, Stéphane and Kamps, Jaap (2025). Context embeddings for efficient answer generation in retrieval-augmented generation. 18th International Conference on Web Search and Data Mining-WSDM, Hannover, Germany, 10-14 March 2025. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3701551.3703527
Gienapp, Lukas, Scells, Harrisen, Deckers, Niklas, Bevendorff, Janek, Wang, Shuai, Kiesel, Johannes, Syed, Shahbaz, Fröbe, Maik, Zuccon, Guido, Stein, Benno, Hagen, Matthias and Potthast, Martin (2024). Evaluating generative ad hoc information retrieval. SIGIR '24: 47th International ACM SIGIR Conference on Research and Development in Information Retrieva, Washington, DC, United States, 14-18 July 2024. New York, NY, United States: ACM. doi: 10.1145/3626772.3657849
Wang, Shuai, Khramtsova, Ekaterina, Zhuang, Shengyao and Zuccon, Guido (2024). FeB4RAG: evaluating federated search in the context of retrieval augmented generation. SIGIR '24: 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, Washington, DC, United States, 14-18 July 2024. New York, NY, United States: ACM. doi: 10.1145/3626772.3657853
Wang, Shuai, Zhuang, Shengyao and Zuccon, Guido (2024). Large language models based stemming for information retrieval: promises, pitfalls and failures. SIGIR '24: 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, Washington, DC, United States, 14-18 July 2024. New York, NY, United States: ACM. doi: 10.1145/3626772.3657949
Wang, Shuai, Scells, Harrisen, Zhuang, Shengyao, Potthast, Martin, Koopman, Bevan and Zuccon, Guido (2024). Zero-shot generative large language models for systematic review screening automation. 46th European Conference on Information Retrieval, ECIR 2024, Glasgow, United Kingdom, 24-28 March 2024. Cham, Switzerland: Springer Nature Switzerland. doi: 10.1007/978-3-031-56027-9_25
Rau, David, Déjean, Hervé, Chirkova, Nadezhda, Formal, Thibault, Wang, Shuai, Clinchant, Stéphane and Nikoulina, Vassilina (2024). BERGEN: a benchmarking library for retrieval-augmented generation. 2024 Conference on Empirical Methods in Natural Language Processing, Miami, FL, United States, 12 - 16 November 2024. Stroudsburg, PA, United States: Association for Computational Linguistics. doi: 10.18653/v1/2024.findings-emnlp.449
Wang, Shuai, Scells, Harrisen, Koopman, Bevan, Potthast, Martin and Zuccon, Guido (2023). Generating natural language queries for more effective systematic review screening prioritisation. SIGIR-AP 2023 - Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region, Beijing, China, 26 - 28 November 2023. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3624918.3625322
Wang, Shuai, Scells, Harrisen, Koopman, Bevan and Zuccon, Guido (2023). Can ChatGPT write a good Boolean query for systematic review literature search?. 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, Taipei, Taiwan, 23 - 27 July 2023. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3539618.3591703
Wang, Shuai and Zuccon, Guido (2023). Balanced topic aware sampling for effective dense retriever: a reproducibility study. 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, Taipei, Taiwan, 23 - 27 July 2023. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3539618.3591915
Wang, Shuai, Li, Hang and Zuccon, Guido (2023). MeSH suggester: a library and system for MeSH term suggestion for systematic review Boolean query construction. Sixteenth ACM International Conference on Web Search and Data Mining, Singapore, Singapore, 27 February - 3 March 2023. New York, NY, United States: ACM. doi: 10.1145/3539597.3573025
Wang, Shuai, Scells, Harrisen, Koopman, Bevan and Zuccon, Guido (2022). Neural rankers for effective screening prioritisation in medical systematic review literature search. 26th Australasian Document Computing Symposium, Adelaide, SA, Australia, 15-16 December 2022. New York, NY, United States: ACM. doi: 10.1145/3572960.3572980
Li, Hang, Wang, Shuai, Zhuang, Shengyao, Mourad, Ahmed, Ma, Xueguang, Lin, Jimmy and Zuccon, Guido (2022). To Interpolate or not to Interpolate: PRF, dense and sparse retrievers. SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, 11-15 July 2022. New York, United States: Association for Computing Machinery. doi: 10.1145/3477495.3531884
Wang, Shuai, Scells, Harrisen, Clark, Justin, Koopman, Bevan and Zuccon, Guido (2022). From little things big things grow: a collection with seed studies for medical systematic review literature search. SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, 11-15 July 2022. New York, United States: Association for Computing Machinery. doi: 10.1145/3477495.3531748
Wang, Shuai, Scells, Harrisen, Mourad, Ahmed and Zuccon, Guido (2022). Seed-driven document ranking for systematic reviews: a reproducibility study. 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, 10–14 April 2022. Cham, Switzerland: Springer. doi: 10.1007/978-3-030-99736-6_46
Wang, Shuai, Li, Hang, Scells, Harrisen, Locke, Daniel and Zuccon, Guido (2021). MeSH Term Suggestion for Systematic Review Literature Search. Australasian Document Computing Symposium, Melbourne, VIC, Australia, 9 December 2021. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3503516.3503530
Wang, Shuai, Zhuang, Shengyao and Zuccon, Guido (2021). BERT-based Dense Retrievers Require Interpolation with BM25 for Effective Passage Retrieval. The ACM SIGIR International Conference on the Theory of Information Retrieval (ICTIR), Canada, 11 July 2021. New York, NY, USA: Association for Computing Machinery, Inc. doi: 10.1145/3471158.3472233