
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
2010
Conference Publication
Estimating interference in the QPRP for subtopic retrieval
Zuccon, Guido, Azzopardi, Leif, Hauff, Claudia and van Rijsbergen, C.J. Keith (2010). Estimating interference in the QPRP for subtopic retrieval. 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval - SIGIR '10, Geneva, Switzerland, 19-23 July 2010. New York, NY, United States: ACM Press. doi: 10.1145/1835449.1835593
2010
Conference Publication
Using the quantum probability ranking principle to rank interdependent documents
Zuccon, Guido and Azzopardi, Leif (2010). Using the quantum probability ranking principle to rank interdependent documents. 32nd European Conference on IR Research, ECIR 2010, Milton Keynes, United Kingdom, 28-31 March 2010. Berlin, Heidelberg: Springer Berlin Heidelberg. doi: 10.1007/978-3-642-12275-0_32
2010
Book Chapter
University of Glasgow at ImageCLEFPhoto 2009: Optimising Similarity and Diversity in Image Retrieval
Leelanupab, Teerapong, Zuccon, Guido, Goyal, Anuj, Halvey, Martin, Punitha, P. and Jose, Joemon M. (2010). University of Glasgow at ImageCLEFPhoto 2009: Optimising Similarity and Diversity in Image Retrieval. Lecture Notes in Computer Science. (pp. 133-141) Berlin, Heidelberg: Springer. doi: 10.1007/978-3-642-15751-6_14
2010
Conference Publication
When Two Is Better Than One: A Study of Ranking Paradigms and Their Integrations for Subtopic Retrieval
Leelanupab, Teerapong, Zuccon, Guido and Jose, Joemon M. (2010). When Two Is Better Than One: A Study of Ranking Paradigms and Their Integrations for Subtopic Retrieval. 6th Asia Information Retrieval Societies Conference (AIRS 2010), Taipei, Taiwan, 1-3 December 2010. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-17187-1_15
2009
Conference Publication
Revisiting logical imaging for information retrieval
Zuccon, Guido, Azzopardi, Leif and van Rijsbergen, Cornelis J. (2009). Revisiting logical imaging for information retrieval. 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Boston, MA, United States, 19-23 July 2009 . New York, NY, United States: ACM Press. doi: 10.1145/1571941.1572118
2009
Conference Publication
The quantum Probability Ranking Principle for information retrieval
Zuccon, Guido, Azzopardi, Leif A. and van Rijsbergen, Keith (2009). The quantum Probability Ranking Principle for information retrieval. Second International Conference on the Theory of Information Retrieval, ICTIR 2009, Cambridge, United Kingdom, September 2009. Berlin, Germany: Springer. doi: 10.1007/978-3-642-04417-5_21
2008
Conference Publication
A formalization of logical imaging for information retrieval using quantum theory
Zuccon, G., Azzopardi, L. A. and Rijsbergen, C. J. van (2008). A formalization of logical imaging for information retrieval using quantum theory. 19th International Workshop on Database and Expert Systems Applications, Turin, Italy, 1-5 September 2008. Piscataway, NJ, United States: IEEE. doi: 10.1109/dexa.2008.69
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
Data Mining on Many-to-Many Complex Relationships
Principal Advisor
Other advisors: Professor Xue Li
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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
Evidence-based Large Language Models as Health Information Mediators
Principal Advisor
Other advisors: Mr Anton Van Der Vegt
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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
Large Language Models for Search
Principal Advisor
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Doctor Philosophy
Summarisation of Healthcare Information
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
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
AI-driven Effective Query Formulation for Better Systematic Reviews
Principal Advisor
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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, Professor Emma McBryde
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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
Human-centered verification of language model outputs
Associate Advisor
Other advisors: Dr Joel Mackenzie, Professor Tim Miller
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Doctor Philosophy
Exploring Facets of Model Generalizability on Out-of-Distribution Data
Associate Advisor
Other advisors: Associate Professor Mahsa Baktashmotlagh
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: 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
Exploring Facets of Model Generalizability on Out-of-Distribution Data
Associate Advisor
Other advisors: Associate Professor Mahsa Baktashmotlagh
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2024
Doctor Philosophy
A Study of Active Learning for Named Entity Recognition
Associate Advisor
Other advisors: Professor Gianluca Demartini
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Media
Enquiries
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