Gianluca Demartini, Ph.D.
School of Information Technology and Electrical Engineering,
University of Queensland
St Lucia
QLD 4072 Australia
Office: +61 7 336 58325
demartini@acm.org
Dr. Gianluca Demartini is an Associate Professor in Data Science at the University of Queensland, School of Electrical Engineering and Computer Science. His main research interests are Information Retrieval, Semantic Web, and Human Computation. His research has been supported by the Australian Research Council (ARC), the Swiss National Science Foundation (SNSF), the EU H2020 framework program, the UK Engineering and Physical Sciences Research Council (EPSRC), Facebook, 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 and at the European Conference on Information Retrieval (ECIR) in 2016, the Best Short Paper Award at ECIR in 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 has given several invited talks, tutorials, and keynotes at a number of academic conferences (e.g., ISWC, ICWSM, WebScience, and the RuSSIR Summer School), companies (e.g., Facebook), and Dagstuhl seminars. He is a senior member of the ACM since 2020, an ACM Distinguished Speaker since 2015, and has been a TEDx speaker in 2019. He serves as associate editor for the Transactions on Graph Data and Knowledge (TGDK) Journal and as an editorial board member for the Information Retrieval journal. He is a steering committee member for the AAAI HCOMP conference. He was PC Chair 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. He has been Senior Program Committee member for, among others, the ACM Conference on Research and Development in Information Retrieval (SIGIR), the ACM Web Search and Data Mining (WSDM) Conference, the International Joint Conference on Artificial Intelligence (IJCAI), the AAAI Conference on Human Computation and Crowdsourcing (HCOMP), and the International Conference on Web Engineering (ICWE). He co-organized several workshops and tutorials at international conferences as well as the Entity Ranking Track at the Initiative for the Evaluation of XML Retrieval in 2008 and 2009. 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 Hanover 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.
