![Professor Guido Zuccon](/sites/default/files/profiles/22857.jpeg)
Overview
Background
Professor Guido Zuccon is a Professorial Research Fellow at The University of Queensland, Electrical Engineering and Computer Science School, the AI DIrector for the Queensland Digital Health Centre (QDHeC), an Affiliate Professor at the UQ Centre for Health Services Research, Faculty of Medicine, and an Honorary Reader at Strathclyde University (UK). He leads the Information Engineering Lab (ielab), a research team working in Information Retrieval and Health Data Science. He was an ARC DECRA Fellow (2018-2020).
Guido's main research interests are Information Retrieval, Health Search, Formal Models of Search and Search Interaction, and Health Data Science. He has successfully attracted funding from the ARC via an ARC Discovery Early Career Research Award Fellowship and an ARC Discoverty Project. His research has also been funded by Google (Google Research Awards program), Grain Research and Development Corporation (GRDC), Microsoft (Microsoft Azure for Research Award), the CSIRO (research gifts and PhD Students Top-up scholarships), the Australian Academy of Science (FASIC program), the European Science Foundation, and Neusoft Corporation.
Guido has published more than 100 peer-reviewed research articles at conferences and in journals, in information retrieval and health informatics; of these more than 30 are ranked in the top 10% of his filed (field weighted average) and more than 10 are ranked in the top 1%. He has won best papers award at AIRS 2017 (“Automatic Query Generation from Legal Texts for Case Law Retrieval”), CLEF 2016 (“Assessors agreement: A case study across assessor type, payment levels, query variations and relevance dimensions”), ALTA 2015 (“Analysis of Word Embeddings and Sequence Features for Clinical Information Extraction”), and ECIR 2012 (“Top-k retrieval using facility location analysis”). His research on people using search engines to seek health advice on the web has been widely disseminated by the media (190+ national and international newspaper articles, 10+ TV and radio interviews in 2015; see the media page coverage for that project). Guido is the Consumer Health Search task leader for the CLEF eHealth Evaluation Lab, since 2014. He is one of the TREC 2019 Decision Track organisers: this is an international evaluation effort in Information Retrieval that aims to investigate how people use search engines to make decisions (with a focus in 2019 on consumer health search). Guido has provided scientific tutorials to other researchers in his field at ACM SIGIR 2015 and 2018, ACM CIKM 2015, ACM ICTIR 2016, RUSSIR 2018, WSDM 2019.
Guido has reviewed for top journals and conferences in his field, including ACM TOIS, FnTIR, JASIST, IRJ, ACM TIST, ACM TWEB, IP&M, ACM SIGIR,ACM CIKM, ACM ICTIR, ACM WSDM, WWW, ECIR, ACM SIG-PODS. He was awarded the Best Reviewer Award at ECIR 2014. He has served as general chair, program chair, workshop chair and publicity chair for conferences in his research field, including ADCS (either PC Chair or General Chair in 2013, 2014, 2017), AIRS 2015 (General Chair), ECIR 2015 (Workshop Chair) and WSDM 2019 (publicity chair). Dr Zuccon is the Information co-Director for ACM SIGIR and was one of the recognised IR leaders invited to participate to the 3rd Strategic Workshop in Information Retrieval (SWIRL III, 2018).
Before joining the University of Queensland, Guido was a Lecturer (2014-2017) and Senior Lecturer (2017-2018) at the Queensland University of Technology, Australia, and a Post Doctoral Research Fellow at the Australian E-Health Research Centre (AEHRC), CSIRO (2011-2014), Australia. He received a Ph.D. in Computer Science at the University of Glasgow, UK (2012), focusing on Formal Models of Information Retrieval based on Quantum Theory, and a M.Comp.Eng. summa cum laude at the University of Padova, Italy (2007).
Availability
- Professor Guido Zuccon is:
- Available for supervision
Fields of research
Qualifications
- Doctor of Philosophy, University of Glasgow
Research interests
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Formal models of Information Retrieval
Models of search, information seeking and interactions; Semantic models of search; Exploiting word embeddings and deep learning in Information Retrieval; Evaluation of Information Retrieval (including task-based evaluation)
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Medical/Health Information Retrieval and Data Science
Retrieval models and strategies for consumers searching the web for health advise; Retrieval models and strategies for cohort identification for clinical trials from electronic medical records; Retrieval models and strategies for clinical decision support and evidence-based medicine; Models, approaches and strategies for automating systematic reviews, in particular with respect to the search phase health search evaluation; Semantic models for health data science, including automatic and bootstrapped generation and exploitation of health knowledge graph
Works
Search Professor Guido Zuccon’s works on UQ eSpace
2023
Conference Publication
Open-source large language models are strong zero-shot query likelihood models for document ranking
Zhuang, Shengyao, Liu, Bing, Koopman, Bevan and Zuccon, Guido (2023). Open-source large language models are strong zero-shot query likelihood models for document ranking. Conference on Empirical Methods in Natural Language Processing, Singapore, 6-10 December 2023. Stroudsburg, PA, United States: Association for Computational Linguistics. doi: 10.18653/v1/2023.findings-emnlp.590
2023
Journal Article
AgAsk: an agent to help answer farmer’s questions from scientific documents
Koopman, Bevan, Mourad, Ahmed, Li, Hang, van der Vegt, Anton, Zhuang, Shengyao, Gibson, Simon, Dang, Yash, Lawrence, David and Zuccon, Guido (2023). AgAsk: an agent to help answer farmer’s questions from scientific documents. International Journal on Digital Libraries. doi: 10.1007/s00799-023-00369-y
2023
Conference Publication
Dr ChatGPT tell me what I want to hear: how different prompts impact health answer correctness
Koopman, Bevan and Zuccon, Guido (2023). Dr ChatGPT tell me what I want to hear: how different prompts impact health answer correctness. EMNLP 2023 - 2023 Conference on Empirical Methods in Natural Language Processing, Singapore, 6-10 December 2023. Stroudsburg, PA, United States: Association for Computational Linguistics. doi: 10.18653/v1/2023.emnlp-main.928
2023
Conference Publication
Pretrained language models rankers on private data: is online and federated learning the solution?
Zuccon, Guido (2023). Pretrained language models rankers on private data: is online and federated learning the solution?. DESIRES 2022: Design of Experimental Search & Information REtrieval Systems, San Jose, CA, United States, 30-31 August 2022. Aachen, Germany: Rheinisch-Westfaelische Technische Hochschule Aachen Lehrstuhl Informatik.
2023
Conference Publication
Convolutional Persistence as a Remedy to Neural Model Analysis
Khramtsova, Ekaterina, Zuccon, Guido, Wang, Xi and Baktashmotlagh, Mahsa (2023). Convolutional Persistence as a Remedy to Neural Model Analysis. International Conference on Artificial Intelligence and Statistics, Valencia, Spain, 25-27 April 2023. Brookline, MA United States: ML Research Press.
2022
Conference Publication
Robustness of neural rankers to typos: a comparative study
Zhuang, Shengyao, Mao, Xinyu and Zuccon, Guido (2022). Robustness of neural rankers to typos: a comparative study. 26th Australasian Document Computing Symposium, Adelaide, SA, Australia, 15-16 December 2022. New York, NY, United States: ACM. doi: 10.1145/3572960.3572981
2022
Conference Publication
The task: distinguishing tasks and sessions in legal information retrieval
Wiggers, Gineke and Zuccon, Guido (2022). The task: distinguishing tasks and sessions in legal information retrieval. ADCS '22: Australasian Document Computing Symposium, Adelaide, SA, Australia, 15-16 December 2022. New York, United States: Association for Computing Machinery. doi: 10.1145/3572960.3572983
2022
Conference Publication
Neural rankers for effective screening prioritisation in medical systematic review literature search
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
2022
Conference Publication
Pseudo-relevance feedback with dense retrievers in Pyserini
Li, Hang, Zhuang, Shengyao, Ma, Xueguang, Lin, Jimmy and Zuccon, Guido (2022). Pseudo-relevance feedback with dense retrievers in Pyserini. ADCS '22: Australasian Document Computing Symposium, Adelaide, SA, Australia, 15-16 December 2022. New York, United States: Association for Computing Machinery. doi: 10.1145/3572960.3572982
2022
Conference Publication
Guiding Neural Entity Alignment with Compatibility
Liu, Bing, Scells, Harrisen, Hua, Wen, Zuccon, Guido, Zhao, Genghong and Zhang, Xia (2022). Guiding Neural Entity Alignment with Compatibility. 2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022, Abu Dhabi, United Arab Emirates, 7-11 December 2022. Stroudsburg, PA United States: Association for Computational Linguistics. doi: 10.18653/v1/2022.emnlp-main.32
2022
Journal Article
Automated MeSH term suggestion for effective query formulation in systematic reviews literature search
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
2022
Conference Publication
High-quality task division for large-scale entity alignment
Liu, Bing, Hua, Wen, Zuccon, Guido, Zhao, Genghong and Zhang, Xia (2022). High-quality task division for large-scale entity alignment. 31st ACM International Conference on Information and Knowledge Management, Atlanta, GA, United States, 17 - 21 October 2022. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3511808.3557352
2022
Conference Publication
SCC - a test collection for search in chat conversations
Sabei, Ismail, Mourad, Ahmed and Zuccon, Guido (2022). SCC - a test collection for search in chat conversations. 31st ACM International Conference on Information & Knowledge Management, Atlanta, GA USA, 17-21 October 2022. New York, NY, USA: Association for Computing Machinery. doi: 10.1145/3511808.3557692
2022
Conference Publication
The impact of query refinement on systematic review literature search: a query log analysis
Scells, Harrisen, Forbes, Connor, Clark, Justin, Koopman, Bevan and Zuccon, Guido (2022). The impact of query refinement on systematic review literature search: a query log analysis. 2022 ACM SIGIR International Conference on Theory of Information Retrieval, New York, NY USA, 11-12 July 2022. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3539813.3545143
2022
Journal Article
Reinforcement online learning to rank with unbiased reward shaping
Zhuang, Shengyao, Qiao, Zhihao and Zuccon, Guido (2022). Reinforcement online learning to rank with unbiased reward shaping. Information Retrieval Journal, 25 (4), 1-28. doi: 10.1007/s10791-022-09413-y
2022
Conference Publication
Rethinking persistent homology for visual recognition
Khramtsova, Ekaterina, Zuccon, Guido, Wang, Xi and Baktashmotlagh, Mahsa (2022). Rethinking persistent homology for visual recognition. Topological, Algebraic and Geometric Learning Workshops, Online, 25-22 July 2022. Brookline, MA United States: ML Research Press.
2022
Conference Publication
Implicit feedback for dense passage retrieval: a counterfactual approach
Zhuang, Shengyao, Li, Hang and Zuccon, Guido (2022). Implicit feedback for dense passage retrieval: a counterfactual approach. 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), Madrid, Spain, 11 - 15 July 2022. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3477495.3531994
2022
Conference Publication
Is Non-IID Data a Threat in Federated Online Learning to Rank?
Wang, Shuyi and Zuccon, Guido (2022). Is Non-IID Data a Threat in Federated Online Learning to Rank?. SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, 11 - 15 July 2022. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3477495.3531709
2022
Conference Publication
How does feedback signal quality impact effectiveness of pseudo relevance feedback for passage retrieval
Li, Hang, Mourad, Ahmed, Koopman, Bevan and Zuccon, Guido (2022). How does feedback signal quality impact effectiveness of pseudo relevance feedback for passage retrieval. 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, 11 - 15 July 2022. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3477495.3531822
2022
Conference Publication
From little things big things grow: a collection with seed studies for medical systematic review literature search
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
Funding
Current funding
Supervision
Availability
- Professor Guido Zuccon is:
- Available for supervision
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Supervision history
Current supervision
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Doctor Philosophy
AI-driven Effective Query Formulation for Better Systematic Reviews
Principal Advisor
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Doctor Philosophy
AgAsk: A question-answering conversational agent for data-driven growing decisions
Principal Advisor
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Doctor Philosophy
Automated Evaluation of Intelligent Conversational Agents
Principal Advisor
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Doctor Philosophy
Large Language Models for Search
Principal Advisor
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Doctor Philosophy
Data Mining on Many-to-Many Complex Relationships
Principal Advisor
Other advisors: Professor Xue Li
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Doctor Philosophy
Summarisation of Healthcare Information
Principal Advisor
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Doctor Philosophy
Information Retrieval for Precision Medicine
Principal Advisor
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Doctor Philosophy
AI-driven Effective Query Formulation for Better Systematic Reviews
Principal Advisor
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Doctor Philosophy
Exploring Facets of Model Generalizability on Out-of-Distribution Data
Associate Advisor
Other advisors: Dr Mahsa Baktashmotlagh
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Doctor Philosophy
Development of small animal emergency medicine clinical recommender systems to improve veterinary clinical decision-making and care
Associate Advisor
Other advisors: Professor Ricardo Soares Magalhaes
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Doctor Philosophy
Efficient Next-Generation Information Retrieval Systems
Associate Advisor
Other advisors: Associate Professor Gianluca Demartini, Dr Joel Mackenzie
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Doctor Philosophy
Sample sub-group algorithm bias analysis for machine learning evaluation in the clinical domain
Associate Advisor
Other advisors: Professor Clair Sullivan, Dr Andrew Mallett, Mr Anton Van Der Vegt
Completed supervision
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2023
Doctor Philosophy
Teaching Pre-trained Language Models to Rank Effectively, Efficiently, and Robustly
Principal Advisor
Other advisors: Dr Joel Mackenzie
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2023
Doctor Philosophy
Recommending Data Visualizations: Tackling Diversification and Data Quality Challenges
Principal Advisor
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2022
Doctor Philosophy
Electronic Health Record Representation for Similarity Computing
Principal Advisor
Other advisors: Professor Xue Li
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2020
Doctor Philosophy
Search Engines that Help People Make Better Health Decisions
Principal Advisor
Other advisors: Associate Professor Gianluca Demartini
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2020
Doctor Philosophy
Minimal interaction Information Retrieval: A theoretical framework with applications in clinical decision support
Principal Advisor
Other advisors: Professor Xue Li
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2024
Doctor Philosophy
A Study of Active Learning for Named Entity Recognition
Associate Advisor
Other advisors: Associate Professor Gianluca Demartini
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Media
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