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Professor Guido Zuccon
Professor

Guido Zuccon

Email: 
Phone: 
+61 7 336 58319

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

Qualifications

  • Doctor of Philosophy, University of Glasgow

Research interests

  • 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)

  • 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

227 works between 2008 and 2025

1 - 20 of 227 works

Featured

2019

Journal Article

Consumer health search on the web: study of web page understandability and its integration in ranking algorithms

Palotti, Joao, Zuccon, Guido and Hanbury, Allan (2019). Consumer health search on the web: study of web page understandability and its integration in ranking algorithms. Journal of Medical Internet Research, 21 (1) e10986, e10986. doi: 10.2196/10986

Consumer health search on the web: study of web page understandability and its integration in ranking algorithms

Featured

2018

Journal Article

Payoffs and pitfalls in using knowledge-bases for consumer health search

Jimmy, Zuccon, Guido and Koopman, Bevan (2018). Payoffs and pitfalls in using knowledge-bases for consumer health search. Information Retrieval Journal, 22 (3-4), 350-394. doi: 10.1007/s10791-018-9344-z

Payoffs and pitfalls in using knowledge-bases for consumer health search

Featured

2018

Journal Article

Recursive module extraction using louvain and pagerank

Perrin, Dimitri and Zuccon, Guido (2018). Recursive module extraction using louvain and pagerank. F1000Research, 7 (1286) 1286, 1-11. doi: 10.12688/f1000research.15845.1

Recursive module extraction using louvain and pagerank

2025

Conference Publication

RARR Unraveled: Component-Level Insights into Hallucination Detection and Mitigation

Ross, Jonathan J., Khramtsova, Ekaterina, van der Vegt, Anton, Koopman, Bevan and Zuccon, Guido (2025). RARR Unraveled: Component-Level Insights into Hallucination Detection and Mitigation. 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: 10.1145/3726302.3730337

RARR Unraveled: Component-Level Insights into Hallucination Detection and Mitigation

2025

Conference Publication

Reassessing Large Language Model Boolean query generation for systematic reviews

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

Reassessing Large Language Model Boolean query generation for systematic reviews

2025

Conference Publication

Unlearning for Federated Online Learning to Rank: a reproducibility study

Tao, Yiling, Wang, Shuyi, Yang, Jiaxi and Zuccon, Guido (2025). Unlearning for Federated Online Learning to Rank: a reproducibility study. 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: 10.1145/3726302.3730336

Unlearning for Federated Online Learning to Rank: a reproducibility study

2025

Conference Publication

ReviewHQ: An API-based system for reviewer assignment and quality control in research conferences

Zuccon, Guido (2025). ReviewHQ: An API-based system for reviewer assignment and quality control in research conferences. 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: 10.1145/3726302.3730139

ReviewHQ: An API-based system for reviewer assignment and quality control in research conferences

2025

Conference Publication

Pre-training vs. Fine-tuning: A Reproducibility Study on Dense Retrieval Knowledge Acquisition

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

Pre-training vs. Fine-tuning: A Reproducibility Study on Dense Retrieval Knowledge Acquisition

2025

Conference Publication

AiReview: An open platform for accelerating systematic reviews with LLMs

Mao, Xinyu, Leelanupab, Teerapong, Potthast, Martin, Scells, Harrisen and Zuccon, Guido (2025). AiReview: An open platform for accelerating systematic reviews with LLMs. 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: 10.1145/3726302.3730133

AiReview: An open platform for accelerating systematic reviews with LLMs

2025

Conference Publication

Document screenshot retrievers are vulnerable to pixel poisoning attacks

Zhuang, Shengyao, Khramtsova, Ekaterina, Ma, Xueguang, Koopman, Bevan, Lin, Jimmy and Zuccon, Guido (2025). Document screenshot retrievers are vulnerable to pixel poisoning attacks. 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: 10.1145/3726302.3730056

Document screenshot retrievers are vulnerable to pixel poisoning attacks

2025

Conference Publication

2D Matryoshka Training for Information Retrieval

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

2D Matryoshka Training for Information Retrieval

2025

Conference Publication

R 2 LLMs: retrieval and ranking with LLMs

Zuccon, Guido, Zhuang, Shengyao and Ma, Xueguang (2025). R 2 LLMs: retrieval and ranking with LLMs. 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: 10.1145/3726302.3731689

R 2 LLMs: retrieval and ranking with LLMs

2025

Journal Article

The epidemiology of hospitalisations from four key environmentally sensitive zoonotic diseases in Queensland, 2012–2019

Proboste, Tatiana, Lau, Colleen L., Clark, Nicholas, Jagals, Paul, Sly, Peter D., Lambert, Stephen B., Devine, Gregor, Zuccon, Guido and Soares Magalhães, Ricardo J. (2025). The epidemiology of hospitalisations from four key environmentally sensitive zoonotic diseases in Queensland, 2012–2019. Tropical Medicine and International Health, 30 (8), 838-847. doi: 10.1111/tmi.14139

The epidemiology of hospitalisations from four key environmentally sensitive zoonotic diseases in Queensland, 2012–2019

2025

Other Outputs

Pseudo relevance feedback is enough to close the gap between small and large dense retrieval models

Li, Hang, Wang, Xiao, Koopman, Bevan and Zuccon, Guido (2025). Pseudo relevance feedback is enough to close the gap between small and large dense retrieval models. doi: 10.48550/arXiv.2503.14887

Pseudo relevance feedback is enough to close the gap between small and large dense retrieval models

2025

Conference Publication

ReSLLM: large language models are strong resource selectors for federated search

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 USA: Association for Computing Machinery. doi: 10.1145/3701716.3715595

ReSLLM: large language models are strong resource selectors for federated search

2025

Conference Publication

An investigation of prompt variations for zero-shot LLM-based rankers

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

An investigation of prompt variations for zero-shot LLM-based rankers

2025

Conference Publication

Corpus subsampling: estimating the effectiveness of neural retrieval models on large corpora

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

Corpus subsampling: estimating the effectiveness of neural retrieval models on large corpora

2025

Other Outputs

LLM-VPRF: Large language model based vector pseudo relevance feedback

Li, Hang, Zhuang, Shengyao, Koopman, Bevan and Zuccon, Guido (2025). LLM-VPRF: Large language model based vector pseudo relevance feedback. doi: 10.48550/arXiv.2504.01448

LLM-VPRF: Large language model based vector pseudo relevance feedback

2024

Conference Publication

Understanding and Mitigating the Threat of Vec2Text to Dense Retrieval Systems

Zhuang, Shengyao, Koopman, Bevan, Chu, Xiaoran and Zuccon, Guido (2024). Understanding and Mitigating the Threat of Vec2Text to Dense Retrieval Systems. 2024 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region, Tokyo, Japan, 9-12 December 2024. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3673791.3698414

Understanding and Mitigating the Threat of Vec2Text to Dense Retrieval Systems

2024

Conference Publication

Searching in Professional Instant Messaging Applications: User Behaviour, Intent, and Pain-points

Sabei, Ismail, Galal, Mahmoud, Koopman, Bevan and Zuccon, Guido (2024). Searching in Professional Instant Messaging Applications: User Behaviour, Intent, and Pain-points. 2024 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region, Tokyo, Japan, 9-12 December 2024. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3673791.3698417

Searching in Professional Instant Messaging Applications: User Behaviour, Intent, and Pain-points

Funding

Current funding

  • 2024 - 2029
    NASCENT: National infrastructure for real-time clinical AI trials
    MRFF - National Critical Infrastructure Initiative
    Open grant
  • 2022 - 2026
    Digital Infrastructure For improving First Nations Maternal & Child Health
    MRFF Research Data Infrastructure
    Open grant

Past funding

  • 2023 - 2024
    From Search to Synthesis: Automating the Systematic Review Creation Process
    Universities Australia - Germany Joint Research Co-operation Scheme
    Open grant
  • 2022 - 2023
    Federated Online Learning of Neural Rankers
    CCF Baidu Pinecone Fund
    Open grant
  • 2022 - 2023
    SMART Project - Towards Systematic Maturation of Analytics and System Redesign to Transform (SMART) Healthcare and Public Health Research
    Queensland Health
    Open grant
  • 2021 - 2023
    Enhancing the Capability of the Global Policing Database
    Australian Federal Police
    Open grant
  • 2021 - 2023
    Enhancing the Capability of the Global Policing Database
    Australia and New Zealand Society of Evidence Based Policing Inc
    Open grant
  • 2021 - 2025
    AI-driven Effective Query Formulation for Better Systematic Reviews
    ARC Discovery Projects
    Open grant
  • 2021 - 2022
    Tribu: AI-based Ticketing System
    Innovation Connections
    Open grant
  • 2020 - 2025
    Enhanced data extraction and modelling from electronic medical records and phenotyping for clinical care, and research: Case studies in management of medication stewardship
    Digital Health CRC
    Open grant
  • 2020 - 2022
    AgAsk: A machine learning generated question-answering conversational agent for data-driven growing decisions.
    Grains Research & Development Corporation
    Open grant
  • 2019 - 2021
    Development of Explainable AI Techniques for Complex Disease Diagnosis using Genomics Data (SPARC grant led by Symbiosis International)
    Symbiosis International Deemed University
    Open grant
  • 2019 - 2022
    Collaborative Lab of Health Informatics with Neusoft
    Neusoft Research of Intelligent Healthcare Technology, Co Ltd
    Open grant
  • 2018 - 2021
    Searching when the stakes are high: better health decisions from Dr Google
    ARC Discovery Early Career Researcher Award
    Open grant
  • 2018 - 2022
    Searching for Better Health
    Google Inc
    Open grant

Supervision

Availability

Professor Guido Zuccon is:
Available for supervision

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Supervision history

Current supervision

  • Doctor Philosophy

    Methods for the Effective Retrieval of Chat Conversations

    Principal Advisor

  • Doctor Philosophy

    Advanced Query Representation and Feedback Methods for Neural Information Retrieval

    Principal Advisor

  • Doctor Philosophy

    Large Language Models for Search

    Principal Advisor

  • Doctor Philosophy

    Symptom Checkers, Search Engines and Conversational Agents for Online Health Information Seeking

    Principal Advisor

  • Doctor Philosophy

    Data Mining on Many-to-Many Complex Relationships

    Principal Advisor

    Other advisors: Professor Xue Li

  • Doctor Philosophy

    AI-driven Effective Query Formulation for Better Systematic Reviews

    Principal Advisor

  • Doctor Philosophy

    AI-driven Automated Systematic Reviews

    Principal Advisor

  • Doctor Philosophy

    What Generators Want from Search: Aligning Retrieval with the Needs of Generative AI

    Principal Advisor

    Other advisors: Mr Anton Van Der Vegt

  • Doctor Philosophy

    Human-centered verification of language model outputs

    Associate Advisor

    Other advisors: Dr Joel Mackenzie, Professor Tim Miller

  • Doctor Philosophy

    Optimizing Large Language Models for Healthcare Question Answering

    Associate Advisor

    Other advisors: Dr Teerapong Leelanupab

  • 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

Media

Enquiries

For media enquiries about Professor Guido Zuccon's areas of expertise, story ideas and help finding experts, contact our Media team:

communications@uq.edu.au