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
2023
Conference Publication
Leveraging Semantic Type Dependencies for Clinical Named Entity Recognition
Le, Linh, Zuccon, Guido, Demartini, Gianluca, Zhao, Genghong and Zhang, Xia (2023). Leveraging Semantic Type Dependencies for Clinical Named Entity Recognition. AMIA 2022 Annual Symposium, Washington, DC United States, 5-9 November 2022. Bethesda, MD United States: American Medical Informatics Association.
2023
Journal Article
On the role of human and machine metadata in relevance judgment tasks
Xu, Jiechen, Han, Lei, Sadiq, Shazia and Demartini, Gianluca (2023). On the role of human and machine metadata in relevance judgment tasks. Information Processing and Management, 60 (2) 103177, 1-14. doi: 10.1016/j.ipm.2022.103177
2023
Other Outputs
UQ Single Column Format Inconsistency Datasets
Demartini, Gianluca, Chen, Tianwa, Sadiq, Shazia, Fan, Shaoyang, Xu, Jiechen, Han, Lei and Yu, Shaochen (2023). UQ Single Column Format Inconsistency Datasets. The University of Queensland. (Dataset) doi: 10.48610/0ab54e7
2023
Other Outputs
MELArt: Multimodal Entity Linking Evaluation Dataset for Art (Version 1.0)
Demartini, Gianluca, Le, Linh, Krestel, Ralf and Sierra, Alejandro (2023). MELArt: Multimodal Entity Linking Evaluation Dataset for Art (Version 1.0). The University of Queensland. (Dataset) doi: 10.48610/2a8ef30
2022
Journal Article
Combining human and machine confidence in truthfulness assessment
Qu, Yunke, Barbera, David La, Roitero, Kevin, Mizzaro, Stefano, Spina, Damiano and Demartini, Gianluca (2022). Combining human and machine confidence in truthfulness assessment. Journal of Data and Information Quality, 15 (1) 5, 1-17. doi: 10.1145/3546916
2022
Journal Article
Task design in complex crowdsourcing experiments: Item assignment optimization
Ceschia, Sara, Roitero, Kevin, Demartini, Gianluca, Mizzaro, Stefano, Di Gaspero, Luca and Schaerf, Andrea (2022). Task design in complex crowdsourcing experiments: Item assignment optimization. Computers and Operations Research, 148 105995, 1-13. doi: 10.1016/j.cor.2022.105995
2022
Journal Article
Report on the 1st Workshop on Human-in-the-Loop Data Curation (HIL-DC 2022) at CIKM 2022
Demartini, Gianluca, Yang, Jie and Sadiq, Shazia (2022). Report on the 1st Workshop on Human-in-the-Loop Data Curation (HIL-DC 2022) at CIKM 2022. ACM SIGIR Forum, 56 (2), 1-8. doi: 10.1145/3582900.3582921
2022
Conference Publication
Automatic identification of 5C vaccine behaviour on social media
Sampath Kumar, Ajay Hemanth, Shausan, Aminath, Demartini, Gianluca and Rahimi, Afshin (2022). Automatic identification of 5C vaccine behaviour on social media. Eighth Workshop on Noisy User-generated Text (W-NUT 2022), Gyeongju, Republic of Korea, 12-17 October 2022. Gyeongju, Republic of Korea: International Conference on Computational Linguistics.
2022
Conference Publication
Workshop on human-in-the-loop data curation
Demartini, Gianluca, Yang, Jie and Sadiq, Shazia (2022). Workshop on human-in-the-loop data curation. 31st ACM International Conference on Information and Knowledge Management, Atlanta, GA, United States, 17-21 October 2022. New York, NY, United States: ACM. doi: 10.1145/3511808.3557498
2022
Conference Publication
How does the crowd impact the model? A tool for raising awareness of social bias in crowdsourced training data
Perikleous, Periklis, Kafkalias, Andreas, Theodosiou, Zenonas, Barlas, Pinar, Christoforou, Evgenia, Otterbacher, Jahna, Demartini, Gianluca and Lanitis, Andreas (2022). How does the crowd impact the model? A tool for raising awareness of social bias in crowdsourced training data. 31st ACM International Conference on Information & Knowledge Management, Atlanta, GA, United States, 17-22 October 2022. New York, NY, United States: ACM. doi: 10.1145/3511808.3557178
2022
Conference Publication
Crowdsourced fact-checking at Twitter : how does the crowd compare with experts?
Saeed, Mohammed, Traub, Nicolas, Nicolas, Maelle, Demartini, Gianluca and Papotti, Paolo (2022). Crowdsourced fact-checking at Twitter : how does the crowd compare with experts?. 31st ACM International Conference on Information & Knowledge, Atlanta, GA USA, 17-21 October 2022. New York, NY, USA: ACM. doi: 10.1145/3511808.3557279
2022
Journal Article
Analytics of learning tactics and strategies in an online learnersourcing environment
Lahza, Hatim, Khosravi, Hassan and Demartini, Gianluca (2022). Analytics of learning tactics and strategies in an online learnersourcing environment. Journal of Computer Assisted Learning, 39 (1), 94-112. doi: 10.1111/jcal.12729
2022
Conference Publication
Incorporating AI and Analytics to Derive Insights from E-exam Logs
Lahza, Hatim Fareed, Khosravi, Hassan and Demartini, Gianluca (2022). Incorporating AI and Analytics to Derive Insights from E-exam Logs. 23rd International Conference of Artificial Intelligence in Education AIED 2022, Durham, United Kingdom, 27–31 July 2022. Heidelberg, Germany: Springer. doi: 10.1007/978-3-031-11644-5_78
2022
Journal Article
A neural model to jointly predict and explain truthfulness of statements
Brand, Erik, Roitero, Kevin, Soprano, Michael, Rahimi, Afshin and Demartini, Gianluca (2022). A neural model to jointly predict and explain truthfulness of statements. Journal of Data and Information Quality, 15 (1) 4, 1-19. doi: 10.1145/3546917
2022
Conference Publication
Socio-economic diversity in human annotations
Fan, Shaoyang, Barlas, Pinar, Christoforou, Evgenia, Otterbacher, Jahna, Sadiq, Shazia and Demartini, Gianluca (2022). Socio-economic diversity in human annotations. WebSci '22: 14th ACM Web Science Conference 2022, Barcelona, Spain, 26-29 June 2022. New York, United States: Association for Computing Machinery. doi: 10.1145/3501247.3531588
2022
Conference Publication
Exploring data literacy levels in the crowd – the case of COVID-19
Fan, Shaoyang, Han, Lei, Demartini, Gianluca and Sadiq, Shazia (2022). Exploring data literacy levels in the crowd – the case of COVID-19. The 16th International AAAI Conference on Web and Social Media, Atlanta, GA United States, 6-9 June 2022. Palo Alto, CA United States: AAAI Press.
2022
Conference Publication
Exploring data literacy levels in the crowd – the case of COVID-19
Fan, Shaoyang, Han, Lei, Demartini, Gianluca and Sadiq, Shazia (2022). Exploring data literacy levels in the crowd – the case of COVID-19. Sixteenth International AAAI Conference on Web and Social Media, Atlanta, GA United States, 6–9 June 2022. Palo Alto, CA United States: Association for the Advancement of Artificial Intelligence (AAAI). doi: 10.1609/icwsm.v16i1.19395
2022
Conference Publication
Understanding reactions to swine flu, Ebola, and the Zika virus using Twitter data: an outlook for future infectious disease outbreaks
Ahmed, Wasim, Bath, Peter A., Sbaffi, Laura and Demartini, Gianluca (2022). Understanding reactions to swine flu, Ebola, and the Zika virus using Twitter data: an outlook for future infectious disease outbreaks. 18th International Symposium on Health Information Management Research, Kalmar, Sweden, 17-18 October 2020. Växjö, Sweden: Linnaeus University Press. doi: 10.15626/ishimr.2020.04
2022
Book Chapter
Artificial intelligence needs human intervention to combat online hate
Demartini, Gianluca and Wilson-Barnao, Caroline (2022). Artificial intelligence needs human intervention to combat online hate. Conflict in My Outlook. (pp. 1-30) edited by Anna Briers, Nicholas Carah and Holly Arden. Melbourne, VIC Australia: Perimiter.
2022
Conference Publication
Does evidence from peers help crowd workers in assessing truthfulness?
Xu, Jiechen, Han, Lei, Fan, Shaoyang, Sadiq, Shazia and Demartini, Gianluca (2022). Does evidence from peers help crowd workers in assessing truthfulness?. WWW '22: The ACM Web Conference 2022, Online, 25 - 29 April, 2022. New York, NY, United States: ACM. doi: 10.1145/3487553.3524236
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
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-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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Master Philosophy
Online discussion summarisation and interaction
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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Doctor Philosophy
Synergising Learning Sciences, Learning Analytics, and Educational Technologies
Associate Advisor
Other advisors: Dr Hassan Khosravi
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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
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
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
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
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
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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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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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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