Gianluca Demartini
building Data Scientists since 2014

Prospective PhD Students

Here you can find some information on how to apply for a PhD position indicating me as your supervisor.

I am currently based at the University of Queensland, Australia. You can find the formal application process for PhD students here.

My research work focuses on Crowdsourcing and Human Computation. I build hybrid human-machine information systems that can scale over large amounts of data and selectively crowdsource some data items for which machine-based algorithms do not have high confidence.
A survey of such systems I wrote is:
- Gianluca Demartini. Hybrid Human-Machine Information Systems: Challenges and Opportunities. In: Computer Networks, Volume 90, page 5-13 (2015), Elsevier.

Good introductory reading material on the area are:
- Edith Law and Luis von Ahn. Human Computation. Synthesis Lectures on Artificial Intelligence and Machine Learning. June 2011
- Adam Marcus and Aditya Parameswaran. Crowdsourced data management industry and academic perspectives. Foundations and Trends in Databases, 2015

Possible research projects in the crowdsourcing and human computation area include the analysis of data (i.e., logs) about how people work in crowdsourcing platforms with the goal of understanding human behaviours and of build software tools (e.g., search, recommendation, social networks, etc.) to support crowd workers and next-generation crowdsourcing platforms.

I am also interested in projects that look at the boundaries between structured (i.e., databases, linked open data, etc.) and unstructured (i.e., web pages, news articles, etc.) Big Data. Thus, my research areas are Information Retrieval and Semantic Web mainly but also include Natural Language Processing and Machine Learning.

Other topics one could be working on with me are to look at entities on the Web: e.g., build novel ways for users to access and search the Web by means of entities (i.e., persons, locations, organisations) using Natural Language Processing techniques.

Feel free to discuss your research plan with me before your submission.

Dr. Gianluca Demartini,
School of Electrical Engineering and Computer Science,
University of Queensland

GP South Building, Staff House Road
St Lucia
QLD 4072 Australia

Office: +61 7 336 58325
demartini@acm.org

Photo of Gianluca Demartini

Gianluca Demartini is a Professor in Data Science and an ARC Future Fellow at the School of Electrical Engineering and Computer Science at the University of Queensland, Australia. He is also a Dieter Schwarz Fellow at the Technical University of Munich, Germany. His main research interests in Data Science include Information Retrieval and Responsible Artificial Intelligence. His research is currently funded by the Australian Research Council, the Swiss National Science Foundation, Meta, Google, and the Wikimedia Foundation. He received multiple Best Paper awards at Artificial Intelligence and Information Retrieval conferences. He has published more than 200 scientific papers at major computer science venues such as the ACM Web Conference, ACM SIGIR, VLDB Journal, ISWC, and ACM CHI. He is an ACM Senior Member, ACM Distinguished Speaker, and TEDx speaker.
His recent research has looked at the application of AI for public good. This includes, for example, applications of AI to online misinformation detection, harmful content detection, and gender and political bias in AI. This has led him to work on fundamental research challenges including data bias management, fairness in AI, and human-artificial intelligence collaboration.
He serves as associate editor for the Transactions on Graph Data and Knowledge (TGDK) Journal and for the ACM Journal of Data and Information Quality (JDIQ). He is a steering committee member for the AAAI HCOMP conference. He was PC Chair for the AAAI HCOMP conference in 2024, the International Semantic Web Conference in 2024, and for the ACM Conference on Research and Development in Information Retrieval (SIGIR) in 2022. He was General co-Chair for the ACM International Conference on Information and Knowledge Management (CIKM) 2021. He was Crowdsourcing and Human Computation Track co-Chair at WWW 2018 and co-chair for the Human Computation and Crowdsourcing Track at ESWC 2015.
Before joining the University of Queensland, he was 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 focusing on Semantic Search.

Prospective PhD Students

Here you can find some information on how to apply for a PhD position indicating me as your supervisor.

I am currently based at the University of Queensland, Australia. You can find the formal application process for PhD students here.

My research work focuses on Crowdsourcing and Human Computation. I build hybrid human-machine information systems that can scale over large amounts of data and selectively crowdsource some data items for which machine-based algorithms do not have high confidence.
A survey of such systems I wrote is:
- Gianluca Demartini. Hybrid Human-Machine Information Systems: Challenges and Opportunities. In: Computer Networks, Volume 90, page 5-13 (2015), Elsevier.

Good introductory reading material on the area are:
- Edith Law and Luis von Ahn. Human Computation. Synthesis Lectures on Artificial Intelligence and Machine Learning. June 2011
- Adam Marcus and Aditya Parameswaran. Crowdsourced data management industry and academic perspectives. Foundations and Trends in Databases, 2015

Possible research projects in the crowdsourcing and human computation area include the analysis of data (i.e., logs) about how people work in crowdsourcing platforms with the goal of understanding human behaviours and of build software tools (e.g., search, recommendation, social networks, etc.) to support crowd workers and next-generation crowdsourcing platforms.

I am also interested in projects that look at the boundaries between structured (i.e., databases, linked open data, etc.) and unstructured (i.e., web pages, news articles, etc.) Big Data. Thus, my research areas are Information Retrieval and Semantic Web mainly but also include Natural Language Processing and Machine Learning.

Other topics one could be working on with me are to look at entities on the Web: e.g., build novel ways for users to access and search the Web by means of entities (i.e., persons, locations, organisations) using Natural Language Processing techniques.

Feel free to discuss your research plan with me before your submission.