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Associate Professor Gianluca Demartini
Associate Professor

Gianluca Demartini

Email: 
Phone: 
+61 7 336 58325

Overview

Background

Dr. Gianluca Demartini is an Associate Professor in Data Science at the University of Queensland, Australia. His main research interests include Information Retrieval, Semantic Web, and Human Computation. His research is currently funded by the Australian Research Council, the Swiss National Science Foundation, Meta, Google, and the Wikimedia Foundation. He received Best Paper Awards at the ACM SIGIR International Conference on the Theory of Information Retrieval (ICTIR) in 2023, AAAI Conference on Human Computation and Crowdsourcing (HCOMP) in 2018, at the European Conference on Information Retrieval (ECIR) in 2016 and 2020, and the Best Demo award at the International Semantic Web Conference (ISWC) in 2011. He has published more than 200 peer-reviewed scientific publications including papers at major venues such as WWW, ACM SIGIR, VLDBJ, ISWC, and ACM CHI. He is an ACM Senior Member, ACM Distinguished Speaker, and a TEDx speaker.

Before joining the University of Queensland, he was a Lecturer at the University of Sheffield in UK, post-doctoral researcher at the eXascale Infolab at the University of Fribourg in Switzerland, visiting researcher at UC Berkeley, junior researcher at the L3S Research Center in Germany, and intern at Yahoo! Research in Spain. In 2011, he obtained a Ph.D. in Computer Science at the Leibniz University of Hannover in Germany focusing on Semantic Search.

Availability

Associate Professor Gianluca Demartini is:
Available for supervision
Media expert

Research interests

  • Misinformation

    Understanding how people interact with misinformation on social media and using AI to mitigate its spread online.

  • Crowdsourcing and Human Computation

    Improving the efficiency and effectiveness of human-in-the-loop systems.

  • Big Data Analytics

    Designing algorithms and systems that can scale-out to large amounts of data.

  • AI for Public Good

    Using Artificial Intelligence methods for societal and environmental purposes. For example, stopping the spread of misinformation online and identifying chimpanzee in videos for preservation purposes.

Research impacts

The research led by A/Prof. Demartini focuses on improving the efficiency and effectiveness of human-in-the-loop artificial intelligence (AI) systems with application of AI for public good. The application domains of his research include text analytics and the intersection between structured (e.g., knowledge graphs) and unstructured (e.g., text) digital content. During his research career he has collaborated with colleagues from several industry and governmental organizations like for example, Facebook, Google, Microsoft, Yahoo!, IBM, SAP, and The National Archives in the UK.

Works

Search Professor Gianluca Demartini’s works on UQ eSpace

203 works between 2006 and 2024

1 - 20 of 203 works

Featured

2024

Journal Article

Cognitive Biases in Fact-Checking and Their Countermeasures: A Review

Soprano, Michael, Roitero, Kevin, La Barbera, David, Ceolin, Davide, Spina, Damiano, Demartini, Gianluca and Mizzaro, Stefano (2024). Cognitive Biases in Fact-Checking and Their Countermeasures: A Review. Information Processing & Management, 61 (3) 103672, 103672. doi: 10.1016/j.ipm.2024.103672

Cognitive Biases in Fact-Checking and Their Countermeasures: A Review

Featured

2024

Conference Publication

CoLAL: Co-learning active learning for text classification

Le, Linh, Zhao, Genghong, Zhang, Xia, Zuccon, Guido and Demartini, Gianluca (2024). CoLAL: Co-learning active learning for text classification. Thirty-Eighth AAAI Conference on Artificial Intelligence, Vancouver, BC Canada, 20–27 February 2024. Washington, DC United States: Association for the Advancement of Artificial Intelligence. doi: 10.1609/aaai.v38i12.29235

CoLAL: Co-learning active learning for text classification

Featured

2024

Journal Article

Who Determines What Is Relevant? Humans or AI? Why Not Both? : A spectrum of human–AI collaboration in assessing relevance

Faggioli, Guglielmo, Dietz, Laura, Clarke, Charles, Demartini, Gianluca, Hagen, Matthias, Hauff, Claudia, Kando, Noriko, Kanoulas, Evangelos, Potthast, Martin, Stein, Benno and Wachsmuth, Henning (2024). Who Determines What Is Relevant? Humans or AI? Why Not Both? : A spectrum of human–AI collaboration in assessing relevance. Communications of the ACM, 67 (4), 31-34. doi: 10.1145/3624730

Who Determines What Is Relevant? Humans or AI? Why Not Both? : A spectrum of human–AI collaboration in assessing relevance

Featured

2023

Journal Article

Data bias management

Demartini, Gianluca, Roitero, Kevin and Mizzaro, Stefano (2023). Data bias management. Communications of the ACM, 67 (1), 28-32. doi: 10.1145/3611641

Data bias management

Featured

2023

Journal Article

Human-AI cooperation to tackle misinformation and polarization

Spina, Damiano, Sanderson, Mark, Angus, Daniel, Demartini, Gianluca, Mckay, Dana, Saling, Lauren L. and White, Ryen W. (2023). Human-AI cooperation to tackle misinformation and polarization. Communications of the ACM, 66 (7), 40-45. doi: 10.1145/3588431

Human-AI cooperation to tackle misinformation and polarization

Featured

2022

Conference Publication

Preferences on a budget: prioritizing document pairs when crowdsourcing relevance judgments

Roitero, Kevin, Checco, Alessandro, Mizzaro, Stefano and Demartini, Gianluca (2022). Preferences on a budget: prioritizing document pairs when crowdsourcing relevance judgments. ACM Web Conference, Virtual/Lyon, France, 25-29 April 2022. New York, United States: Association for Computing Machinery. doi: 10.1145/3485447.3511960

Preferences on a budget: prioritizing document pairs when crowdsourcing relevance judgments

Featured

2020

Journal Article

CrowdCO-OP: sharing risks and rewards in crowdsourcing

Fan, Shaoyang, Gadiraju, Ujwal, Checco, Alessandro and Demartini, Gianluca (2020). CrowdCO-OP: sharing risks and rewards in crowdsourcing. Proceedings of the ACM on Human-Computer Interaction, 4 (CSCW2) 132, 1-24. doi: 10.1145/3415203

CrowdCO-OP: sharing risks and rewards in crowdsourcing

Featured

2020

Conference Publication

Can the crowd identify misinformation objectively?: The effects of judgment scale and assessor's background

Roitero, Kevin, Soprano, Michael, Fan, Shaoyang, Spina, Damiano, Mizzaro, Stefano and Demartini, Gianluca (2020). Can the crowd identify misinformation objectively?: The effects of judgment scale and assessor's background. International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event, China, 25-30 July 2020. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3397271.3401112

Can the crowd identify misinformation objectively?: The effects of judgment scale and assessor's background

Featured

2020

Conference Publication

On understanding data worker interaction behaviors

Han, Lei, Chen, Tianwa, Demartini, Gianluca, Indulska, Marta and Sadiq, Shazia (2020). On understanding data worker interaction behaviors. SIGIR '20: The 43rd International ACM SIGIR conference on research and development in Information Retrieval, Virtual Event China, July 2020. New York, United States: Association for Computing Machinery. doi: 10.1145/3397271.3401059

On understanding data worker interaction behaviors

Featured

2020

Journal Article

Adversarial attacks on crowdsourcing quality control

Checco, Alessandro, Bates, Jo and Demartini, Gianluca (2020). Adversarial attacks on crowdsourcing quality control. Journal of Artificial Intelligence Research, 67, 375-408. doi: 10.1613/jair.1.11332

Adversarial attacks on crowdsourcing quality control

Featured

2019

Conference Publication

Scalpel-CD: leveraging crowdsourcing and deep probabilistic modeling for debugging noisy training data

Yang, Jie, Demartini, Gianluca, Smirnova, Alisa, Lu, Yuan, Yang, Dingqi and Cudré-Mauroux, Philippe (2019). Scalpel-CD: leveraging crowdsourcing and deep probabilistic modeling for debugging noisy training data. World Wide Web Conference (WWW), San Francisco, CA, United States, 13-17 May 2019. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3308558.3313599

Scalpel-CD: leveraging crowdsourcing and deep probabilistic modeling for debugging noisy training data

Featured

2015

Conference Publication

The dynamics of micro-task crowdsourcing: the case of amazon MTurk

Difallah, Djellel Eddine, Catasta, Michele, Demartini, Gianluca, Ipeirotis, Panagiotis G. and Cudré-Mauroux, Philippe (2015). The dynamics of micro-task crowdsourcing: the case of amazon MTurk. 24th International Conference on World Wide Web, WWW 2015, Florence, Italy, 18 - 22 May 2015. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/2736277.2741685

The dynamics of micro-task crowdsourcing: the case of amazon MTurk

Featured

2015

Conference Publication

Understanding malicious behavior in crowdsourcing platforms: the case of online surveys

Gadiraju, Ujwal, Kawase, Ricardo, Dietze, Stefan and Demartini, Gianluca (2015). Understanding malicious behavior in crowdsourcing platforms: the case of online surveys. 33rd Annual CHI Conference on Human Factors in Computing Systems - CHI'15, Seoul, South Korea, 18 - 23 April 2015. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/2702123.2702443

Understanding malicious behavior in crowdsourcing platforms: the case of online surveys

2024

Other Outputs

Multimodal Entity Linking Evaluation Dataset for Art (Version 3.0)

Demartini, Gianluca, Le, Thai Linh, Krestel, Ralf and Sierra, Alejandro (2024). Multimodal Entity Linking Evaluation Dataset for Art (Version 3.0). The University of Queensland. (Dataset) doi: 10.48610/8a1ccdf

Multimodal Entity Linking Evaluation Dataset for Art (Version 3.0)

2024

Journal Article

Crowdsourced Fact-checking: Does It Actually Work?

Barbera, David La, Maddalena, Eddy, Soprano, Michael, Roitero, Kevin, Demartini, Gianluca, Ceolin, Davide, Spina, Damiano and Mizzaro, Stefano (2024). Crowdsourced Fact-checking: Does It Actually Work?. Information Processing & Management, 61 (5) 103792, 103792. doi: 10.1016/j.ipm.2024.103792

Crowdsourced Fact-checking: Does It Actually Work?

2024

Conference Publication

Hate speech detection with generalizable target-aware fairness

Chen, Tong, Wang, Danny, Liang, Xurong, Risius, Marten, Demartini, Gianluca and Yin, Hongzhi (2024). Hate speech detection with generalizable target-aware fairness. KDD '24: 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Barcelona, Spain, 25-29 August 2024. New York, NY, United States: ACM. doi: 10.1145/3637528.3671821

Hate speech detection with generalizable target-aware fairness

2024

Journal Article

Longitudinal Loyalty: Understanding The Barriers To Running Longitudinal Studies On Crowdsourcing Platforms

Soprano, Michael, Roitero, Kevin, Gadiraju, Ujwal, Maddalena, Eddy and Demartini, Gianluca (2024). Longitudinal Loyalty: Understanding The Barriers To Running Longitudinal Studies On Crowdsourcing Platforms. ACM Transactions on Social Computing, 7 (1-4), 1-49. doi: 10.1145/3674884

Longitudinal Loyalty: Understanding The Barriers To Running Longitudinal Studies On Crowdsourcing Platforms

2024

Journal Article

Human-AI cooperation to tackle misinformation and polarization

Spina, Damiano, Sanderson, Mark, Angus, Daniel, Demartini, Gianluca, McKay, Dana, Saling, Lauren L. and White, Ryen W. (2024). Human-AI cooperation to tackle misinformation and polarization. Communications of the ACM, 67 (7), 40-45. doi: 10.1145/3588431

Human-AI cooperation to tackle misinformation and polarization

2024

Conference Publication

Fairness without sensitive attributes via knowledge sharing

Ni, Hongliang, Han, Lei, Chen, Tong, Sadiq, Shazia and Demartini, Gianluca (2024). Fairness without sensitive attributes via knowledge sharing. 2024 ACM Conference on Fairness, Accountability, and Transparency, Rio de Janeiro, Brazil, 3-6 June 2024. New York, NY, United States: ACM. doi: 10.1145/3630106.3659014

Fairness without sensitive attributes via knowledge sharing

2024

Conference Publication

How good are LLMs in generating personalized advertisements?

Meguellati, Elyas, Han, Lei, Bernstein, Abraham, Sadiq, Shazia and Demartini, Gianluca (2024). How good are LLMs in generating personalized advertisements?. WWW '24: The ACM Web Conference 2024, Singapore, 13-17 May 2024. New York, United States: Association for Computing Machinery. doi: 10.1145/3589335.3651520

How good are LLMs in generating personalized advertisements?

Funding

Current funding

  • 2025 - 2028
    PBIAS: A Principled Approach to Data Bias Management in Data Pipelines
    ARC Future Fellowships
    Open grant
  • 2025 - 2028
    PBIAS: A Principled Approach to Data Bias Management in Data Pipelines
    ARC Future Fellowships
    Open grant
  • 2022 - 2025
    Large-Scale Political Participation: Issue Identification, Deliberation, and Co-creation (Swiss National Science Foundation grant administered by Universität Zürich)
    University of Zurich
    Open grant
  • 2021 - 2026
    ARC Training Centre for Information Resilience
    ARC Industrial Transformation Training Centres
    Open grant
  • 2019 - 2024
    Crowdsourcing an Online Safety Benchmark for Fake News Identification
    Facebook Online Safety Benchmark Research Award
    Open grant

Past funding

  • 2023 - 2024
    Measuring the Gender Gap: Attribute-based Class Completeness Estimation
    Wikimedia Foundation (US)
    Open grant
  • 2022 - 2024
    Human-in-the-loop Natural Language Processing in GLAM
    Universities Australia - Germany Joint Research Co-operation Scheme
    Open grant
  • 2022 - 2023
    Monitoring and Modeling Human Annotator Behaviors in Mephisto
    Meta AI Mephisto Dataset Collection Tool
    Open grant
  • 2021 - 2023
    Human-in-the-loop Chimpanzee Identification
    Google AI for Social Good
    Open grant
  • 2019 - 2022
    DESCANT : DEtecting Stereotypes in human ComputAtioN Tasks
    CYENS Centre of Excellence
    Open grant
  • 2019 - 2024
    Building crowd sourced data curation processes
    ARC Discovery Projects
    Open grant
  • 2019
    Artificial Intelligence with Humans in the Loop
    UQ Early Career Researcher
    Open grant
  • 2019 - 2022
    Collaborative Lab of Health Informatics with Neusoft
    Neusoft Research of Intelligent Healthcare Technology, Co Ltd
    Open grant

Supervision

Availability

Associate Professor Gianluca Demartini is:
Available for supervision

Before you email them, read our advice on how to contact a supervisor.

Supervision history

Current supervision

  • Doctor Philosophy

    Human-centered Artificial Intelligence for Democracy

    Principal Advisor

  • Master Philosophy

    Online discussion summarisation and interaction

    Principal Advisor

  • Doctor Philosophy

    Human in the Loop Decision Systems for Online Safety

    Principal Advisor

    Other advisors: Professor Tim Miller

  • Doctor Philosophy

    Bias Mitigation in Human in the Loop Decision Systems

    Principal Advisor

    Other advisors: Professor Shazia Sadiq

  • Doctor Philosophy

    Human-Centred Artificial Intelligence for Democracy

    Principal Advisor

  • Doctor Philosophy

    Customer Data Stories

    Principal Advisor

    Other advisors: Professor Shazia Sadiq

  • Doctor Philosophy

    Retrieval Augmented Generation: A Paradigm Shift in Natural Language Processing

    Principal Advisor

  • Doctor Philosophy

    Integrating Human and Machine Intelligence Towards the Development of an Adaptive Learning System

    Associate Advisor

    Other advisors: Dr Hassan Khosravi

  • Doctor Philosophy

    Synergising Learning Sciences, Learning Analytics, and Educational Technologies

    Associate Advisor

    Other advisors: Dr Hassan Khosravi

  • Doctor Philosophy

    Critical Success Factors in Data Driven Value Creation

    Associate Advisor

    Other advisors: Professor Marta Indulska, Professor Shazia Sadiq

  • Doctor Philosophy

    Extreme Analytics

    Associate Advisor

    Other advisors: Associate Professor Stephen Viller, Dr Maxime Cordeil

  • Doctor Philosophy

    Sensemaking in Multi-artefact Information Tasks

    Associate Advisor

    Other advisors: Professor Marta Indulska, Professor Shazia Sadiq

  • Doctor Philosophy

    Crowd Sourced Data Curation

    Associate Advisor

    Other advisors: Professor Marta Indulska, Professor Shazia Sadiq

Completed supervision

Media

Enquiries

Contact Associate Professor Gianluca Demartini directly for media enquiries about:

  • AI
  • AI for Good
  • Artificial Intelligence
  • Bias
  • Big data
  • Crowdsourcing
  • Data Analytics
  • Data Science
  • Disinformation
  • Fairness
  • Fake News
  • Human Computation
  • Knowledge Graphs
  • Misinformation
  • Text Analytics

Need help?

For help with finding experts, story ideas and media enquiries, contact our Media team:

communications@uq.edu.au