Dr Thushari Atapattu

Dr Thushari Atapattu
 Position Grant-Funded Researcher (A)
 Org Unit Computer Science
 Email thushari.atapattu@adelaide.edu.au
 Telephone +61 8 8313 9077
 Location Floor/Room 4 ,  Ingkarni Wardli ,   North Terrace

  • Biography/ Background

    2018- : Lead and founder, Language Technology for Social Good (LT4SG) Research Group, University of Adelaide

    2015- : Postdoctoral Research Fellow, Computer Science Education Research Group, University of Adelaide

    2011-2014: PhD in Computer Science, University of Adelaide

    2010-2011: Software Engineer

    2008-2009: Research Assistant, University of Colombo School of Computing

    2004-2008: Bachelor of Computer Science (Hons), University of Colombo

  • Awards & Achievements

    2021: Finalist for Women in AI Australia & New Zealand

    2019: Australian Federation of University Women SA Postdoctoral Grant

    2017: Adelaide Women's Research Excellence Award

    2015: Dean's Commendation for Doctoral Thesis Excellence

    2013: Finalist for Google Anita Borg scholarship (PhD category in Asia-Pacific Region)

    2012: Google PhD Travel Award

    2011: University of Adelaide PhD Scholarship

  • Teaching Interests

    I am the tech lead, co-designer and developer of following Teacher Professional Development MOOCs;

    Cyber Security and Awareness (Primary Years)

    Cyber Security and Awareness (Secondary Years)

    Teaching AI in the Primary Classrooms

    Teaching AI in the Secondary Classrooms

    Years 7 & 8 Digital Technologies - Next Steps

    Teaching AR, VR and MR in K-12 classrooms

     

    I will be teaching following courses at the University of Adelaide;

    2020 (Semester 2): COMP SCI 1106 - Introduction to Software Engineering

    2019 (Semester 2): COMP SCI 1106 - Introduction to Software Engineering

    2017 (Semester 1): COMP SCI 7098 - Master of Computing & Innovation Project

    2017 (Semester 2): COMP SCI 1106 - Introduction to Software Engineering

     

    Guest lectures:

    Grand challenges in Computer Science - Semester 2 2021

  • Research Interests

    My research focuses on better understanding the latent discourse aspects in large corpora of natural language text, and using this understanding to build computational models that can improve human communication process. My research interests lie in the areas of discourse processing, social NLP, learning analytics and software engineering.

    Read more about my research work at LT4SG

    Some of my recent research projects explores;

    • Using linguistic fingerprints to combat cyberbullying (Lead)
    • Automated glossary generation for effective information extraction from COVID-19 related scientific articles (AI for decision making initiative by Department of Defence) (Lead)
    • Advancing the detection of cyberbullying through role modeling (Lead)
    • Modeling emotion-cause relation in mental health language data (Lead)
    • Modeling language-related to mental health using social media data (Lead)
    • Multi-class emotion modeling from social media data (Lead)
    • Assessing Software Documentation quality (Collaborator)
    • Impact of teachers’ academic discourse in lecture videos for students’ video engagement in MOOCs (Lead)
    • Modeling coginitive engagement and measuring new knowledge construction in online teacher PD MOOCs (Lead)
    • Detecting 'confusion' state of discussion forums in MOOCs (Lead)
    • Understanding and classifying contents in GitHub README files (Collaborator)
    • Topic modeling and visualisation in MOOC discussion forums (Lead)
    Regardless of the discipline, I am passionate about everything in TEXT, DISCOURSE, LANGUAGE, COGNITIVE PSYCHOLOGY & MIND :)

     For potential students (Honours, Masters and PhD):

    If you have a passion for any of the above areas and would like to pursue higher studies in the University of Adelaide, feel free to email me with your current CV, publications record, transcripts of all degrees and a statement about your research interest.

    Some information about Postgraduate scholarship (domestic and international) can be found here

     

    Current HDR/Research students

    PhD students

    Isuru Dharmadasa (PhD) with Nick Falkner and Menasha Thilakaratne - Detecting cyberbullying triggers from text (2022-2024)

    Hamzah Arishi (PhD) with Nick Falkner and Christoph Treude - Sentimental and Emotional analysis from MOOC discussions (2020 - 2023)

    Abhilash Sridara (MPhil) with Katrina Falkner, Nick Falkner - Evaluation of essay type answers in MOOCs using NLP techniques (2020 - 2021)

    Completed PhD students

    Dr Lavendini Sivaneasharajah with Katrina Falkner, Rebecca Vivian - User roles in online learning context through linguistic expressions, 2018-2022

    Dr Menasha Thilakaratne with Katrina Falkner - Literature-based knowledge discovery using Natural Language Processing techniques, 2017-2020

    Masters/Honours/Undergraduates

    Mostafa Mahdi (Masters of AI and Machine Learning) with Menasha Thilakaratne, Leveraging LLMs to transform unstructed venue hire information of SA communities to MARC21 standard (2024)

    Georgia Zhang (Honors in Computer Science) with Menasha Thilakaratne, Emotion-cause pair extraction from Natural Language Text, 2021

    Dasuni Jayawickrama (Advanced Topics in Computer Science) with Menasha Thilakaratne, Automatically detecting triggers of emotions in text, 2021

    Sabby Saha (Masters of Data Science) with Rebecca Vivian & Katrina Falkner, Multi-emotion modeling from Reddit data using NLP, 2020-2021

    Georgia Zhang (Advanced Topics in Computer Science), Automatic identification of roles associated with cyberbullying posts, 2020

    Dasuni Jayawickrama (Summer Research student) with Sebastian Baltes & Christoph Treude, Discourse analysis of stack overflow threads, 2020

    Dung Anh Hoang (Summer Research student) with Katrina Falkner & Christoph Treude, Advancing the detection of Cyberbullying in Social Media, 2020

    Georgia Zhang (Topics in Computer Science), Detection of Cyberbullying aginst minorities, 2019

    Dung Anh Hoang (Topics in Computer Science), Automated identification of mental health issues in Social media, 2019

    Alexa Ng (Topics in Computer Science), Impact of semantic relatedness of course content for video learning, 2018

    Roland Croft (Topics in Computer Science) with Christoph Treude, Identifying the topics of Stack Overflow discussions, 2017

     

    Research Staff

    Dr Menasha Thilakaratne (Dec 2020 to present)- Natural Language Processing

    Mr Ankit Yadav (2022) - Muti-task learning modeling

    Dasuni Jayawickrama (Dec 2020 to Feb 2022) - "Systematic Literature review on automated extraction of emotion-cause from language data"

    Mahen Herath (Aug 2019 to present) - "Using linguistic fingerprints to combat cyberbullying"

    Gathika Ratnayaka (Feb 2020 to Sep 2020) - "Advancing the detection of cyberbullying through role modeling"

    Hamid Tarmazdi (2016) - "Topic visualisation dashboard of MOOC discussions"

  • Research Funding

    Wagner, M., Thilakaratne, M., Zhang, W., Treude, C., Arora, C., Atapattu, T. Contextually situated anomaly detection, Defence Innovation Partnership, $100,000 (2021-2022)

    T. Atapattu, M. Thilakaratne, De Zoysa, K., Gunawardena, K., Zoysa, P. Mental wellbeing and emotion awareness tool, Australian Academy of Science, $10,000 (2021)

    T. Atapattu, M. Thilakaratne. Automated glossary generation for effective and efficient information extraction from COVID-19 scientific articles, Defence Innovation Partnership, $20,000 (2020-2021)

    Falkner, K., Vivian, R., Atapattu, T. Cyber security education in K-12, AustCyber (with industry partners Google Aus & NZ and CSIRO), $313,387 (2020-2021)

    T. Atapattu, Automated dection of cyberbullying against minorities, Australian Federation of University Women SA Inc., $5,000 (2020).

    K. Falkner, R. Vivian, and T. Atapattu, Artificial Intelligence resources to support the Artificial Intelligence in schools initiative, Department of Education & Training, $585,000 (2019-2022)

    K. Falkner, R. Vivian and T. Atapattu, AI Professional Development program for K-12 teachers in support of the Digital Technologies Curriculum in Australia, Google Australia & New Zealand, $83,749 (2019).

    K. Falkner, R. Vivian and T. Atapattu, Understanding the relationship between social community formation and progression within MOOC environments, Research Contract, Google Australia, $37,687 (2017).

  • Publications

    Sridhara, A., Falkner, N., Atapattu, T., Leveraging Inference: A Regression-based Learner Performace System for Knowledge Tracing, Accepted for IEEE Access, 2023

    Atapattu, T., Herath, M., Elvitigala, C., de Zoysa, P., et al., EmoMent: An Emotion Annotated Mental Health Corpus from two South Asian Countries, 29th International Conference on Computational Linguistics (COLING) 2023

    Atapattu, T., Herath, M., Zhang, G., Falkner, K. Automatic Detection of Cyberbullying against Women and Immigrants and Cross-domain Adaptability, Australasian Language Technology Association 2020

    Ratnayaka, G., Atapattu, T., Herath, M., Zhang, G., Falkner, K. Enhancing the Identification of Cyberbullying through Participant Roles, Proccedings of the Workshop on Online Abuse and Harm at EMNLP 2020.

    Atapattu, T., Falkner, K., Thilakaratne, M., Sivaneasharajah, L., Jayashanka, R. What Do Linguistic Expressions Tell Us About Learners' Confusion? A Domain-independent Analysis in MOOCs, IEEE Transactions on Learning Technologies, Sep 2020.

    Treude, C., Middleton, J. Atapattu, T. Beyond Accuracy: Assessing Software Documentation Quality. The ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, Nov 2020.

    Herath M., Atapattu, T., Dung, H., Treude, C., Falkner, K. AdelaideCyC at SemEval-2020 Task 12: Ensemble of Classifiers for Offensive Language Detection in Social Media. International Workshop on Semantic Evaluation at COLING, Dec 2020

    Sivaneasharajah, L., Atapattu, T., Falkner, K. Linguistic Changes across Different User Roles in MOOCs: What do they tell us? 13th International Conference on Educational Data Mining (EDM), July 2020

    Thilakaratne, M., Falkner, K., Atapattu, T. Garbage in-garbage out? an empirical look at information richness of LBD input types. ACM/IEEE Joint conference on Digital Libraries, Aug 2020

    Thilakaratne, M., Falkner, K., Atapattu, T. Information extraction in digital libraries: first step towards portability of LBD workflow. ACM/IEEE Joint conference on Digital Libraries, Aug 2020

    Thilakaratne, M., Falkner, K., Atapattu, T. Connecting the dots: Hypothesis generation by leveraging semantic shifts, PAKDD 2020, Singapore.

     

    Thilakaratne, M., Falkner, K., Atapattu, T. A systematic review on literature-based discovery: General overview, methodology & statistical analysis, ACM Computing Surveys (CSUR), 129,  Dec 2019

    Thilakaratne, M., Falkner, K., Atapattu, T. A systematic review on literature-based discovery workflow, PeerJ Computer Science 5:e235, Nov 2019.

    Atapattu, T., Thilakaratne, M., Vivian, R., Falkner, K. Detecting Cognitive Engagement using Word Embeddings within an Online Teacher Professional Development Community, Computers and Education, Oct 2019.

    Sivaneasharajah, L., Atapattu, T., Falkner, K. Understanding student learning from discussion forums, Australian Learning Analytics Summer Institute, Nov 2019.

     

    Prana, G. A., Treude, C., Thung, F. Atapattu, T., Lo, D. Categorising the content of Github README files. Emprirical Software Engineering, September 2018

    Atapattu, T. & Falkner, K. Impact of Lecturer’s Discourse for Students’ Video Interactions: Video Learning Analytics Case Study of MOOCs, Journal of Learning Analytics, May 2018

    Thilakaratne, M., Falkner, K., Atapattu, T. Automatic Detection of Cross-Disciplinary Knowledge Associations. Student Research Workshop of 56th Annual Meeting of the Association for Computational Linguistics, Melbourne, Australia, July 2018

     

    Atapattu, T., Falkner, K. and Falkner, N. A Comprehensive text analysis of Lecture Slides to Generate Concept Maps. Computers & Education, 115, pp. 96-113, December 2017

    Atapattu, T., Falkner, K. Discourse analysis to improve the effective engagement of MOOC videos. Accepted for the 7th International Learning Analytics and Knowledge conference (LAK), Vancouver, BC, Canada, March 2017

     

    Atapattu, T., Falkner, K. and Tarmazdi, H. Topic-wise classification of MOOC discussions: A visual analytics approach. Proceedings of the 9th International conference on Educational Data Mining (EDM), Raleigh, NC, USA, June 2016

    Atapattu, T., Falkner, K. A Framework for Topic Generation and Labeling from MOOC Discussions. Proceedings of the Third Annual ACM Conference on Learning at Scale (L@S), Edinburgh, Scotland, April 2016

     

    Atapattu, T., Falkner, K. and Falkner, N. Educational Question Answering Motivated by Question-specific Concept Maps. Proceedings of the 17th International Conference on Artificial Intelligence in Education (AIED), Madrid, Spain, June 2015 (Nominated for Best Paper Award)

    Atapattu, T., Falkner, K. and Falkner, N. Task-adapted Concept Map Scaffolding to Support Quizzes in an Online Environment. Proceedings of the 20th Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE), Vilnius, Lithuania, July 2015

    Atapattu, T., Falkner, K. and Falkner, N. An Evaluation Methodology for Concept Maps Mined from Lecture Notes: An Educational Perspective. Communications in Computer and Information Science (CCIS), 510, pp, 68-83, Springer International Publishing, 2015 (Book Chapter)

     

    Atapattu, T., Falkner, K. and Falkner, N. Acquisition of Triples of Knowledge from Lecture Notes: A Natural Language Processing approach. Proceedings of the 7th International conference on Educational Data Mining (EDM), London, July 2014

    Atapattu, T., Falkner, K. and Falkner, N. Evaluation of Concept Importance in Concept Maps Mined from Lecture Notes: Computer vs Human. Proceedings of the 6th International Conference on Computer Supported Education, Barcelona, Spain, April 2014 (Nominated for Best Student Paper Award)

     

    Atapattu, T. Automated Generation of Practice Questions from Semi-Structured Lecture Notes. ICER' 12, Auckland, New Zealand, Sep 2012 (Doctoral abstract)

    Atapattu, T., Falkner, K. and Falkner, N. Automated Extraction of Semantic Concepts From Semi-Structured Data: Supporting Computer-based Education through the Analysis of Lecture Notes. Dexa 2012, Vienna, Austria, Sep 2012

     

    Atapattu, T., De Zoysa, K. Accessing an Interactive learning tool using telephone communications. In the proceedings of the ICT2010, Singapore, June 2010

     

    Atapattu, T., De Zoysa, K. V-Learning: Using voice for Distant Learning in Emerging Regions. In the proceedings of the International conference on Computer Supported Education, Lisboa, Portugal, March 2009

     

    Unpublished works

    Atapattu, T., Falkner, K., Falkner, N. and Palmer, E. 2015. A computational model for task-adapted knowledge organisation: improving learning through concept maps extracted from lecture slides, University of Adelaide, Australia (PhD thesis)

     

  • Professional Associations

    Association for Computer Linguistics (ACL)

    Mind & Life Institute

    International Artificial Intelligence in Education Society (IAIED)

    Society for Learning Analytics Research (SOLAR)

    International Educational Data Mining Society (IEDM)

     

  • Community Engagement

    Conference organisation

    Student volunteer co-chair in the 35th IEEE/ACM International Conference on Automated Software Engineering

    Co-organiser and PC member of the First International Workshop on Literature-based Discovery

    Journal review board

    Review board member of IEEE Transactions on Learning Technologies

    Review board member of Computers & Education

    Review board member of British Journal of Education Technology

    Conference PC member

    ACL Rolling Review (ARR) member since December 2023

    Learning Analytics and Knowledge Conference since 2022

    Koli Calling 

    IEEE TALE

    Other community engagement

    Committee member of Higher Education Research Group of Adelaide (HERGA)

    Member of Google Anita Borg Alumni community

    Member of Learning Analytics Community of Practice - University of Adelaide

    Committee member of Learning Analytics Operations Group (LAOG) - University of Adelaide

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Entry last updated: Friday, 23 Feb 2024

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