Damiano Spina

Damiano Spina

Senior Lecturer and DECRA Fellow

School of Computing Technologies, RMIT University

About Me

Womin djeka! This is my personal—not an official RMIT—website. I’m a Senior Lecturer and DECRA Fellow at RMIT University (School of Computing Technologies), deputy director of the Research Centre for Information Discovery and Data Analytics (CIDDA), an Associate Investigator at the ARC Centre of Excellence for Automated Decision-Making and Society, and a research collaborator of RMIT FactLab.

My main research interests are Information Retrieval (IR), Text Analytics, and Data Science. I currently work on evaluation of information access systems and interactive information retrieval.

In my free time, I teach Capoeira at the Associação de Capoeira Descendente do Pantera (ACDP) –where I am also known as Contramestre Camaleão– and play samba with Wombatuque.

I acknowledge the people of the Woi wurrung and Boon wurrung language groups of the eastern Kulin Nation on whose unceded lands I live, work, teach, and learn. I respectfully acknowledge their Ancestors and Elders, past and present. I also acknowledge the Traditional Custodians and their Ancestors of the lands and waters across Australia.
  • Information Retrieval
  • Text Analytics
  • Data Science
  • PhD in Computer Science, 2014

    UNED (Madrid, Spain)


RMIT University

Senior Lecturer and DECRA Fellow, School of Computing Technologies


Deputy Director, Centre for Information Discovery and Data Analytics


Associate Investigator, Centre of Excellence for Automated Decision-Making and Society


Scholarship Opportunities

BITS-RMIT (India-Australia) PhD Research Partnership

Transform your future with a transnational joint PhD from two leading universities. Attractive scholarships available including funded travel to Melbourne, Australian stipend and overseas health cover.

Title. Enhancing computing education for the visually impaired using machine-generated code summaries (BITSRMIT100090)

Project Description. Visually impaired (VI) persons use screen readers that verbalise the text on a computer screen line-by-line. While a sighted developer can comprehend program code by glancing at pieces of code quickly, it is difficult for a VI developer to comprehend code by going line by line. Thus, the aim is to develop an AI-based assistive system helping to improve (Python) code comprehension for the VI developer. Sub-tasks: 1) develop a pseudocode generator providing a natural language description of the source code, 2) develop an AI-based code summarizer generating a compact summary improving the code comprehension, and finally 3) design and develop a Visual Studio code plug-in implementing the above-mentioned models. Experiments: For source code summary generation, we aim to use a multi-modal approach consisting of source code analysis, pseudocode analysis, and feedback quantification. We will employ a forest of abstract syntax trees to generate summaries. The pseudocode will be used to extract long-distance semantics, while feedback will extract lexical features from the text. We will validate our approach against human evaluation and statistical analysis. We will deploy the designed plug-in for real-world Python teaching-learning setups for the VI students. We will compare the code comprehension and programming abilities of VI students using our tool (treatment) and without using our tool (control group).

BITS Supervisors. Dr. Swati Agarwal, Dr. Swaroop Joshi

RMIT Supervisors. Dr Damiano Spina, Dr. Johanne R. Trippas

PhD Scholarship in Automated Decision-Making and Information Retrieval

Opportunity to join the Centre of Excellence on Automated Decision-Making and Society (ADM+S) work on developing new approaches to fairness, actionable explainability or socially considerate evaluation of Automated Decision-Making in search, conversational, recommender, or other information access systems.

More info: https://www.rmit.edu.au/students/careers-opportunities/scholarships/research/phd-automated-decision-making-information-retrieval

Current PhD Students

Former PhD Students

Former Master and Honours Students

  • Reham Abdullah Altalhi, Search Results Fairness based on Analytical Hierarchy Process, RMIT University, 2022.
  • Binh Chon Nut Le, Investigating Algorithmic Bias via Crowdsourcing, RMIT University, 2020. [Paper]
  • Xinhuan Duan, Two-Step Classification for Profiling Fake News Spreaders on Twitter, RMIT University, 2020. [Paper]
  • Shubhdeep Singh, Spoken DialogWOZ : A Tool to PerformWizard of Oz Experiments in Speech-Only Question Answering Scenarios, RMIT University, 2020.
  • Assunta Cerone, Watch ’n’ Check: Towards a Social Media Monitoring Tool to Assist Fact-Checking Experts, Politecnico di Torino, 2020. [Paper]
  • Mazhar Morshed, Missing Attribute Imputation through Clustering in New Item Cold Start Job Recommendation, RMIT University, 2017.
  • Phanomsinh Homsombath, Applying Phonetic Matching to Spoken Document Retrieval, RMIT University, 2015.


The RMIT Research Awards and Prizes focus on research excellence and research impact. It is through these research contributions that RMIT continues to bridge the gap between research and impact, benefitting those beyond the academic community. The research awards and prizes acknowledge the accomplishments of individual researchers, research teams, research leaders, supervisors, and HDR candidates.
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Fair and Transparent Information Access in Spoken Conversational Assistants. This project aims to investigate how rich information needed to answer complex questions can be delivered via a speech-only communication channel. Using laboratory user studies, where users can interact with a smart speaker to ask for information about controversial or multi-perspective topics, the project expects to advance knowledge on how to expose pertinent information without creating or reinforcing biases. Expected outcomes include novel presentation strategies to access rich information via audio in a fair manner. This should significantly benefit the visually impaired and low-literacy communities by enhancing their access to topics with multiple point of views, which would impact decision making such as who to vote for in elections.
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La Barbera D., Roitero K., Demartini G., Mizzaro S., Spina D. (2020) Crowdsourcing Truthfulness: The Impact of Judgment Scale and Assessor Bias. In: Jose J. et al. (eds) Advances in Information Retrieval. ECIR 2020. Lecture Notes in Computer Science, vol 12036. Springer, Cham. https://doi.org/10.1007/978-3-030-45442-5_26
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Albahem A., Spina D., Scholer F., Cavedon L. (2019) Meta-evaluation of Dynamic Search: How Do Metrics Capture Topical Relevance, Diversity and User Effort?. In: Azzopardi L., Stein B., Fuhr N., Mayr P., Hauff C., Hiemstra D. (eds) Advances in Information Retrieval. ECIR 2019. Lecture Notes in Computer Science, vol 11437. Springer, Cham. https://doi.org/10.1007/978-3-030-15712-8_39
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Information Processing & Management
Top Reviewer Award
In recognition of the review made for the Elsevier’s international journal Information Processing & Management (IP&M), based on number of reviews, quality of reviews, and timeliness of responses.
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