Overview
Background
Dr. Gianluca Demartini is a Professor in Data Science and an ARC Future Fellow 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
- Professor Gianluca Demartini is:
- Available for supervision
- Media expert
Fields of research
Research interests
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Misinformation
Understanding how people interact with misinformation on social media and using AI to mitigate its spread online.
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Crowdsourcing and Human Computation
Improving the efficiency and effectiveness of human-in-the-loop systems.
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Big Data Analytics
Designing algorithms and systems that can scale-out to large amounts of data.
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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 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
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
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
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
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
2024
Journal Article
Editorial: Special Issue on Human in the Loop Data Curation
Demartini, Gianluca, Sadiq, Shazia and Yang, Jie (2024). Editorial: Special Issue on Human in the Loop Data Curation. Journal of Data and Information Quality, 16 (1) 3, 1-2. doi: 10.1145/3650209
2024
Journal Article
On the impact of showing evidence from peers in crowdsourced truthfulness assessments
Xu, Jiechen, Han, Lei, Sadiq, Shazia and Demartini, Gianluca (2024). On the impact of showing evidence from peers in crowdsourced truthfulness assessments. ACM Transactions on Information Systems, 42 (3) 87, 1-26. doi: 10.1145/3637872
2024
Conference Publication
Estimating gender completeness in Wikipedia
Patel, Hrishi, Chen, Tianwa, Bongiovanni, Ivano and Demartini, Gianluca (2024). Estimating gender completeness in Wikipedia. The Australasian Conference on Information Systems (ACIS 2024), Canberra, ACT, Australia, 4-6 December 2024. Canberra, ACT, Australia: Australasian Conference on Information Systems.
2024
Other Outputs
Multimodal Entity Linking Evaluation Dataset for Art (Version 2.0)
Demartini, Gianluca, Le, Thai Linh, Krestel, Ralf and Sierra, Alejandro (2024). Multimodal Entity Linking Evaluation Dataset for Art (Version 2.0). The University of Queensland. (Dataset) doi: 10.48610/76f58a5
2024
Journal Article
How many crowd workers do I need? On statistical power when crowdsourcing relevance judgments
Roitero, Kevin, Barbera, David La, Soprano, Michael, Demartini, Gianluca, Mizzaro, Stefano and Sakai, Tetsuya (2024). How many crowd workers do I need? On statistical power when crowdsourcing relevance judgments. ACM Transactions on Information Systems, 42 (1) 21, 1-26. doi: 10.1145/3597201
2024
Conference Publication
Which legal requirements are relevant to a business process? Comparing AI-driven methods as expert aid
Sai, Catherine, Sadiq, Shazia, Han, Lei, Demartini, Gianluca and Rinderle-Ma, Stefanie (2024). Which legal requirements are relevant to a business process? Comparing AI-driven methods as expert aid. 18th International Conference, RCIS 2024, Guimarães, Portugal, 14-17 May 2024. Cham, Switzerland: Springer Nature Switzerland. doi: 10.1007/978-3-031-59465-6_11
2024
Conference Publication
Stochastic Featurization for Active Learning
Le, Linh, Nguyen, Minh-Tien, Tran, Khai Phan, Zhao, Genghong, Xia, Zhang, Zuccon, Guido and Demartini, Gianluca (2024). Stochastic Featurization for Active Learning. Second International Workshop, TAI4H 2024, Jeju, South Korea, 4 August 2024. Cham, Switzerland: Springer Nature Switzerland. doi: 10.1007/978-3-031-67751-9_5
2023
Conference Publication
Exploring data workers’ behaviours in data quality discovery
Chen, Tianwa, Demartini, Gianluca, Indulska, Marta and Sadiq, Shazia (2023). Exploring data workers’ behaviours in data quality discovery. Australasian Conferences on Information Systems 2023, Wellington, New Zealand, 5-8 December 2023. Atlanta, GA USA: Association for Information Systems.
2023
Journal Article
Active learning with feature matching for clinical named entity recognition
Le, Linh, Demartini, Gianluca, Zuccon, Guido, Zhao, Genghong and Zhang, Xia (2023). Active learning with feature matching for clinical named entity recognition. Natural Language Processing Journal, 4 100015, 1-11. doi: 10.1016/j.nlp.2023.100015
2023
Conference Publication
Perspectives on large language models for relevance judgment
Faggioli, Guglielmo, Dietz, Laura, Clarke, Charles L. A., Demartini, Gianluca, Hagen, Matthias, Hauff, Claudia, Kando, Noriko, Kanoulas, Evangelos, Potthast, Martin, Stein, Benno and Wachsmuth, Henning (2023). Perspectives on large language models for relevance judgment. 13th ACM SIGIR International Conference on the Theory of Information Retrieval (ICTIR), Taipei, Taiwan, 23 July 2023. New York, United States: Association for Computing Machinery. doi: 10.1145/3578337.3605136
2023
Conference Publication
On the impact of data quality on image classification fairness
Barry, Aki, Han, Lei and Demartini, Gianluca (2023). On the impact of data quality on image classification fairness. SIGIR '23: The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, Taipei, Taiwan, 23 - 27 July 2023. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3539618.3592031
2023
Journal Article
A data-driven analysis of behaviors in data curation processes
Han, Lei, Chen, Tianwa, Demartini, Gianluca, Indulska, Marta and Sadiq, Shazia (2023). A data-driven analysis of behaviors in data curation processes. ACM Transactions on Information Systems, 41 (3) 72, 1-35. doi: 10.1145/3567419
2023
Conference Publication
Firearms on Twitter: A novel object detection pipeline
Harvey, Ryan, Lebret, Rémi, Massonnet, Stéphane, Aberer, Karl and Demartini, Gianluca (2023). Firearms on Twitter: A novel object detection pipeline. Seventeenth International AAAI Conference on Web and Social Media, Limassol, Cyprus, 5–8 June 2023. Palo Alto, CA United States: Association for the Advancement of Artificial Intelligence. doi: 10.1609/icwsm.v17i1.22221
2023
Journal Article
DataOps-4G: on supporting generalists in data quality discovery
Yu, Shaochen, Chen, Tianwa, Han, Lei, Demartini, Gianluca and Sadiq, Shazia (2023). DataOps-4G: on supporting generalists in data quality discovery. IEEE Transactions on Knowledge and Data Engineering, 35 (5), 4668-4681. doi: 10.1109/tkde.2022.3151605
2023
Conference Publication
Human-in-the-loop regular expression extraction for single column format inconsistency
Yu, Shaochen, Han, Lei, Indulska, Marta, Sadiq, Shazia and Demartini, Gianluca (2023). Human-in-the-loop regular expression extraction for single column format inconsistency. WWW '23: ACM Web Conference 2023, Austin, TX, United States, 30 April - 4 May 2023. New York, United States: Association for Computing Machinery. doi: 10.1145/3543507.3583515
2023
Conference Publication
The community notes observatory: can crowdsourced fact-checking be trusted in practice?
Righes, Luca, Saeed, Mohammed, Demartini, Gianluca and Papotti, Paolo (2023). The community notes observatory: can crowdsourced fact-checking be trusted in practice?. WW '23 Companion: ACM Web Conference 2023, Austin, TX, United States, 30 April - 4 May 2023. New York, NY, United States: ACM. doi: 10.1145/3543873.3587340
Funding
Current funding
Supervision
Availability
- Professor Gianluca Demartini is:
- Available for supervision
Before you email them, read our advice on how to contact a supervisor.
Supervision history
Current supervision
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Doctor Philosophy
Human-centered Artificial Intelligence for Democracy
Principal Advisor
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Doctor Philosophy
Bias in Data Pipelines and AI Systems
Principal Advisor
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Doctor Philosophy
Human-Centred Artificial Intelligence for Democracy
Principal Advisor
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Doctor Philosophy
Bias Mitigation in Human in the Loop Decision Systems
Principal Advisor
Other advisors: Professor Shazia Sadiq
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Doctor Philosophy
Retrieval Augmented Generation: A Paradigm Shift in Natural Language Processing
Principal Advisor
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Doctor Philosophy
Human in the Loop Decision Systems for Online Safety
Principal Advisor
Other advisors: Professor Tim Miller
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Master Philosophy
Online discussion summarisation and interaction
Principal Advisor
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Doctor Philosophy
Critical Success Factors in Data Driven Value Creation
Associate Advisor
Other advisors: Professor Marta Indulska, Professor Shazia Sadiq
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Doctor Philosophy
Crowd Sourced Data Curation
Associate Advisor
Other advisors: Professor Marta Indulska, Professor Shazia Sadiq
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Doctor Philosophy
Critical Success Factors in Data Driven Value Creation
Associate Advisor
Other advisors: Professor Marta Indulska, Professor Shazia Sadiq
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Doctor Philosophy
Sensemaking in Multi-artefact Information Tasks
Associate Advisor
Other advisors: Professor Marta Indulska, Professor Shazia Sadiq
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Doctor Philosophy
Extreme Analytics
Associate Advisor
Other advisors: Associate Professor Stephen Viller, Dr Jarrod Knibbe, Dr Maxime Cordeil
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Doctor Philosophy
Critical Success Factors in Data Driven Value Creation
Associate Advisor
Other advisors: Professor Marta Indulska, Professor Shazia Sadiq
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Doctor Philosophy
Integrating Human and Machine Intelligence Towards the Development of an Adaptive Learning System
Associate Advisor
Other advisors: Dr Hassan Khosravi
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Doctor Philosophy
Synergising Learning Sciences, Learning Analytics, and Educational Technologies
Associate Advisor
Other advisors: Dr Hassan Khosravi
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Doctor Philosophy
Sensemaking in Multi-artefact Information Tasks
Associate Advisor
Other advisors: Professor Marta Indulska, Professor Shazia Sadiq
Completed supervision
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2024
Doctor Philosophy
A Study of Active Learning for Named Entity Recognition
Principal Advisor
Other advisors: Professor Guido Zuccon
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2024
Doctor Philosophy
On the Role of Human and Machine Metadata in Crowdsourced Data Annotation
Principal Advisor
Other advisors: Professor Shazia Sadiq, Professor Marta Indulska
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2024
Doctor Philosophy
Automating Expertise in Identifying Structured Data Quality Issues: From Experts, Through Novices, to Machines
Principal Advisor
Other advisors: Professor Shazia Sadiq, Professor Marta Indulska
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2023
Doctor Philosophy
Improving the Work Environment and Data Quality in Micro-Task Crowdsourcing
Principal Advisor
Other advisors: Professor Shazia Sadiq
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2021
Doctor Philosophy
Intelligence Behind Annotations: A Study of Understanding Interaction Behavior when the Human is in the Loop
Principal Advisor
Other advisors: Professor Shazia Sadiq
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2024
Doctor Philosophy
Synergising Learning Sciences, Learning Analytics, and Educational Technologies
Associate Advisor
Other advisors: Dr Hassan Khosravi
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2020
Doctor Philosophy
Search Engines that Help People Make Better Health Decisions
Associate Advisor
Other advisors: Professor Guido Zuccon
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Media
Enquiries
Contact 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
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