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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

207 works between 2008 and 2024

61 - 80 of 207 works

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

Is Non-IID Data a Threat in Federated Online Learning to Rank?

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

How does feedback signal quality impact effectiveness of pseudo relevance feedback for passage retrieval

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

From little things big things grow: a collection with seed studies for medical systematic review literature search

2022

Conference Publication

Asyncval: a toolkit for asynchronously validating dense retriever checkpoints during training

Zhuang, Shengyao and Zuccon, Guido (2022). Asyncval: a toolkit for asynchronously validating dense retriever checkpoints during training. 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: 10.1145/3477495.3531658

Asyncval: a toolkit for asynchronously validating dense retriever checkpoints during training

2022

Conference Publication

Seed-driven document ranking for systematic reviews: a reproducibility study

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

Seed-driven document ranking for systematic reviews: a reproducibility study

2022

Other Outputs

CharacterBERT and self-teaching for improving the robustness of dense retrievers on queries with typos

Zhuang, Shengyao and Zuccon, Guido (2022). CharacterBERT and self-teaching for improving the robustness of dense retrievers on queries with typos.

CharacterBERT and self-teaching for improving the robustness of dense retrievers on queries with typos

2022

Other Outputs

Agvaluate

Li, Hang, Zuccon, Guido, Koopman, Bevan and Mourad, Ahmed (2022). Agvaluate. The University of Queensland. (Dataset) doi: 10.48610/0160dc7

Agvaluate

2022

Conference Publication

Improving query representations for dense retrieval with pseudo relevance feedback: a reproducibility study

Li, Hang, Zhuang, Shengyao, Mourad, Ahmed, Ma, Xueguang, Lin, Jimmy and Zuccon, Guido (2022). Improving query representations for dense retrieval with pseudo relevance feedback: a reproducibility study. 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, 10-14 April 2022. Cham, Switzerland: Springer International Publishing. doi: 10.1007/978-3-030-99736-6_40

Improving query representations for dense retrieval with pseudo relevance feedback: a reproducibility study

2022

Conference Publication

Causality discovery based on combined causes and multiple causes in drug-drug interaction

Subpaiboonkit, Sitthichoke, Li, Xue, Zhao, Xin and Zuccon, Guido (2022). Causality discovery based on combined causes and multiple causes in drug-drug interaction. 18th International Conference, ADMA 2022, Brisbane, QLD, Australia, 28-30 November 2022. Cham, Switzerland: Springer Nature Switzerland. doi: 10.1007/978-3-031-22064-7_5

Causality discovery based on combined causes and multiple causes in drug-drug interaction

2021

Conference Publication

Cohort-based clinical trial retrieval

Koopman, Bevan and Zuccon, Guido (2021). Cohort-based clinical trial retrieval. Australasian Document Computing Symposium, Virtual, 9 December 2021. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3503516.3503529

Cohort-based clinical trial retrieval

2021

Conference Publication

MeSH Term Suggestion for Systematic Review Literature Search

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

MeSH Term Suggestion for Systematic Review Literature Search

2021

Conference Publication

ActiveEA: Active learning for neural entity alignment

Liu, Bing, Scells, Harrisen, Zuccon, Guido, Hua, Wen and Zhao, Genghong (2021). ActiveEA: Active learning for neural entity alignment. 2021 Conference on Empirical Methods in Natural Language Processing, Punta Cana, Dominican Republic, November 2021. Stroudsburg, PA, United States: Association for Computational Linguistics. doi: 10.18653/v1/2021.emnlp-main.270

ActiveEA: Active learning for neural entity alignment

2021

Conference Publication

Dealing with typos for BERT-based passage retrieval and ranking

Zhuang, Shengyao and Zuccon, Guido (2021). Dealing with typos for BERT-based passage retrieval and ranking. Conference on Empirical Methods in Natural Language Processing, Online and Punta Cana, Dominican Republic, 7 – 11 November 2021. Stroudsburg, PA, United States: Association for Computational Linguistics. doi: 10.18653/v1/2021.emnlp-main.225

Dealing with typos for BERT-based passage retrieval and ranking

2021

Conference Publication

Loss-based active learning for named entity recognition

Linh, Le Thai, Nguyen, Minh-Tien, Zuccon, Guido and Demartini, Gianluca (2021). Loss-based active learning for named entity recognition. 2021 International Joint Conference on Neural Networks (IJCNN), Shenzhen, China, 18-22 July, 2021. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ijcnn52387.2021.9533675

Loss-based active learning for named entity recognition

2021

Conference Publication

PECAN: a platform for searching chat conversations

Qin, Kunpeng, Scells, Harrisen and Zuccon, Guido (2021). PECAN: a platform for searching chat conversations. SIGIR '21: 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual, 11 - 15 July, 2021. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3404835.3462791

PECAN: a platform for searching chat conversations

2021

Conference Publication

Effective and privacy-preserving federated online learning to rank

Wang, Shuyi, Liu, Bing, Zhuang, Shengyao and Zuccon, Guido (2021). Effective and privacy-preserving federated online learning to rank. ACM SIGIR International Conference on the Theory of Information Retrieval, Online, 11 July 2021. New York, NY, USA: Association for Computing Machinery, Inc. doi: 10.1145/3471158.3472236

Effective and privacy-preserving federated online learning to rank

2021

Conference Publication

Big brother: a drop-in website interaction logging service

Scells, Harrisen, Jimmy, and Zuccon, Guido (2021). Big brother: a drop-in website interaction logging service. SIGIR '21: 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual, 11 - 15 July, 2021. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3404835.3462781

Big brother: a drop-in website interaction logging service

2021

Conference Publication

BERT-based Dense Retrievers Require Interpolation with BM25 for Effective Passage Retrieval

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

BERT-based Dense Retrievers Require Interpolation with BM25 for Effective Passage Retrieval

2021

Conference Publication

Precision medicine search for paediatric oncology

Koopman, Bevan, Wright, Tracey, Omer, Natacha, McCabe, Veronica and Zuccon, Guido (2021). Precision medicine search for paediatric oncology. 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual, 11 - 15 July, 2021. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3404835.3462792

Precision medicine search for paediatric oncology

2021

Conference Publication

Search engines vs. symptom checkers: a comparison of their effectiveness for online health advice

Cross, Sebastian, Mourad, Ahmed, Zuccon, Guido and Koopman, Bevan (2021). Search engines vs. symptom checkers: a comparison of their effectiveness for online health advice. World Wide Web Conference, Ljubljana, Slovenia, 19-23 April 2021. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3442381.3450140

Search engines vs. symptom checkers: a comparison of their effectiveness for online health advice

Funding

Current funding

  • 2024 - 2029
    NASCENT: Translating AI research to clinical practice; National infrastructure for real-time clinical AI trials.
    MRFF - National Critical Infrastructure Initiative
    Open grant
  • 2023 - 2024
    From Search to Synthesis: Automating the Systematic Review Creation Process
    Universities Australia - Germany Joint Research Co-operation Scheme
    Open grant
  • 2022 - 2026
    Digital Infrastructure For improving First Nations Maternal & Child Health
    MRFF Research Data Infrastructure
    Open grant
  • 2021 - 2024
    AI-driven Effective Query Formulation for Better Systematic Reviews
    ARC Discovery Projects
    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

Past funding

  • 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 - 2022
    Tribu: AI-based Ticketing System
    Innovation Connections
    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

    AgAsk: A question-answering conversational agent for data-driven growing decisions

    Principal Advisor

  • Doctor Philosophy

    Automated Evaluation of Intelligent Conversational Agents

    Principal Advisor

  • Doctor Philosophy

    Large Language Models for Search

    Principal Advisor

  • Doctor Philosophy

    Summarisation of Healthcare Information

    Principal Advisor

  • Doctor Philosophy

    Information Retrieval for Precision Medicine

    Principal Advisor

  • Doctor Philosophy

    AI-driven Effective Query Formulation for Better Systematic Reviews

    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

    Exploring Facets of Model Generalizability on Out-of-Distribution Data

    Associate Advisor

    Other advisors: Dr Mahsa Baktashmotlagh

  • 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

  • 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

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