Menasha Thilakaratne

Research Interests

Knowledge Representation and Machine Learning Natural Language Processing Pattern Recognition and Data Mining

Dr Menasha Thilakaratne

Lecturer

Optimisation and Stabilisation

Integration Management Office

Eligible to supervise Masters and PhD - email supervisor to discuss availability.

Dr. Menasha Thilakaratne is a Lecturer at the University of Adelaide, Australia, and serves as the Research Lead for the Language Technology for Social Good (LT4SG) group. She is also an active Researcher in the Computer Science Education Research (CSER) group. Her research, which includes natural language processing (NLP), machine learning, information retrieval and extraction, text mining, mental health and education, has received broad recognition and substantial support. This includes prestigious awards such as the Winnovation Awards and funding from significant entities like the Defence Innovative Partnership and the Department of Industry, Science, Energy & Resources.Beyond her research, Dr. Thilakaratne is deeply committed to educational excellence and innovation in teaching. She has led significant curriculum design and development initiatives at the University of Adelaide, enhancing the educational pathways for postgraduate students. Her leadership roles include managing large curriculum development teams and developing advanced educational frameworks, demonstrating her dedication to advancing computer science education and equipping students with critical skills for their professional growth.

Dr. Menasha Thilakaratne specialises in a diverse range of interdisciplinary research areas, including natural language processing (NLP), machine learning, information retrieval and extraction, text mining, with a particular focus on applications in mental health and education.

Dr. Thilakaratne is looking for highly motivated research students with backgrounds and interests in Computer Science. Prospective students are encouraged to review the scholarship webpage for both domestic and international scholarships. For further inquiries, interested candidates are invited to email Dr. Thilakaratne directly.

Date Position Institution name
2021 - ongoing Lecturer University of Adelaide
2017 - 2020 PhD student University of Adelaide, Adelaide

Date Type Title Institution Name Country Amount
2021 Award Dean's Commendation for Doctoral Thesis Excellence The University of Adelaide Australia -
2021 Award Winner of Winnovation Awards in the Maths & Data category Women in Innovation (Sponsored by FIXE - Future Industries eXchange for Entrepreneurship) Australia -
2021 Recognition Finalist of Winnovation Awards in the Emerging Innovator category Women in Innovation (sponsored by Stone & Chalk) Australia -
2020 Scholarship Faculty of Engineering, Computer & Mathematical Sciences Travel Scholarship The University of Adelaide Australia -
2018 Scholarship SRW ACL2018 Travel Grant Roam Analytics Australia -
2018 Achievement Three Minute Thesis (3MT) Engineering, Computer & Mathematical Sciences Faculty Finalist The University of Adelaide Australia -
2017 Scholarship Faculty of Engineering, Computer & Mathematical Sciences Divisional Scholarship and Full Fee Scholarship The University of Adelaide Australia -
2015 Award Professor Mohan Munasinghe Award for Computer Science University of Colombo School of Computing Sri Lanka -
2014 Award David Pieris Group Gold Medal for the Best Performance in Industrial Placement University of Colombo School of Computing Sri Lanka -

Language Competency
English -
Sinhala; Sinhalese -

Date Institution name Country Title
2017 - 2020 University of Adelaide Australia Doctor of Philosophy
2011 - 2016 University of Colombo, Colombo Sri Lanka Bachelor in Computer Science

Date Title Institution name Country
— Machine Learning Professional Certificate IBM -
— Applied Data Science with Python Specialisation University of Michigan -
— Natural Language Processing Specialisation DeepLearning.AI -
— Generative Adversarial Networks (GANs) Specialisation DeepLearning.AI -
— Learning to Teach Online The University of New South Wales -
— University Teaching The University of Hong Kong -
— Blended Language Learning: Design and Practice for Teachers University of Colorado Boulder -
— Inclusive Online Teaching Teach-Out Johns Hopkins University -
— Resilient Teaching Through Times of Crisis and Change University of Michigan -
— Online education: The foundations of online teaching Macquarie University -
— Certification in Chartered Institute of Management Accountants Foundation Level CIMA -

Year Citation
2025 Dehkordi, A. A., Neshat, M., Khosravian, A., Thilakaratne, M., Safaa Sadiq, A., & Mirjalili, S. (2025). Lightweight convolutional neural networks using nonlinear Lévy chaotic moth flame optimisation for brain tumour classification via efficient hyperparameter tuning. Scientific Reports, 15(1), 22586.
DOI Scopus1 WoS1 Europe PMC1
2025 Neshat, M., Thilakaratne, M., El-Abd, M., Mirjalili, S., Gandomi, A. H., & Boland, J. (2025). Smart buildings energy consumption forecasting using adaptive evolutionary bagging extra tree learning models. Energy, 333(137130), 137130.
DOI Scopus1 WoS1
2024 Neshat, M., Ahmed, M., Askari, H., Thilakaratne, M., & Mirjalili, S. (2024). Hybrid Inception Architecture with Residual Connection: Fine-tuned Inception-ResNet Deep Learning Model for Lung Inflammation Diagnosis from Chest Radiographs. Procedia Computer Science, 235, 1841-1850.
DOI Scopus28
2024 Athukoralage, D., Atapattu, T., Thilakaratne, M., & Falkner, K. (2024). LT4SG@SMM4H24: Tweets Classification for Digital Epidemiology of Childhood Health Outcomes Using Pre-Trained Language Models.. CoRR, abs/2406.07759.
2023 Neshat, M., Ahmed, M., Askari, H., Thilakaratne, M., & Mirjalili, S. (2023). Hybrid Inception Architecture with Residual Connection: Fine-tuned Inception-ResNet Deep Learning Model for Lung Inflammation Diagnosis from Chest Radiographs.. CoRR, abs/2310.02591.
2022 Atapattu, T., Herath, M., Elvitigala, C., de Zoysa, P., Gunawardane, K., Thilakaratne, M., . . . Falkner, K. (2022). EmoMent: An Emotion Annotated Mental Health Corpus from two South Asian Countries. Proceedings - International Conference on Computational Linguistics, COLING, 29(1), 6991-7001.
Scopus6
2020 Atapattu, T., Falkner, K., Thilakaratne, M., Sivaneasharajah, L., & Jayashanka, R. (2020). What Do Linguistic Expressions Tell Us about Learners' Confusion? A Domain-independent Analysis in MOOCs. IEEE Transactions on Learning Technologies, 13(4), 878-888.
DOI Scopus18 WoS13
2019 Atapattu, T., Falkner, K., Thilakaratne, M., Sivaneasharajah, L., & Jayashanka, R. (2019). An Identification of Learners' Confusion through Language and Discourse Analysis.. CoRR, abs/1903.03286.
2019 Atapattu, T., Thilakaratne, M., Vivian, R., & Falkner, K. (2019). Detecting cognitive engagement using word embeddings within an online teacher professional development community. Computers and Education, 140, 14 pages.
DOI Scopus54 WoS42
2019 Thilakaratne, M., Falkner, K., & Atapattu Mudiyanselage, T. (2019). A systematic review on literature-based discovery workflow. PEERJ COMPUTER SCIENCE, 5, 40 pages.
DOI Scopus33 WoS30 Europe PMC13
2019 Thilakaratne, M., Falkner, K., & Atapattu Mudiyanselage, T. (2019). A systematic review on literature-based discovery: General overview, methodology, & statistical analysis. ACM Computing Surveys, 52(6), 34 pages.
DOI Scopus45 WoS32

Year Citation
2025 Atapattu, T., Thilakaratne, M., Do, D. N., Herath, M., & Falkner, K. E. (2025). Exploring the Role of Mental Health Conversational Agents in Training Medical Students and Professionals: A Systematic Literature Review.. In W. Che, J. Nabende, E. Shutova, & M. T. Pilehvar (Eds.), ACL (Findings) (pp. 20785-20798). Association for Computational Linguistics.
2025 Thilakaratne, M., Chen, W. T., Brennan, M., Falkner, N., & Szabo, C. (2025). Building a Strong Base: The Impact of Mastery Learning on Foundation of Computer Science Courses. In Proceedings of 25th International Conference on Computing Education Research Koli Calling 2025 (pp. 1-7). ACM.
DOI
2024 Mahdi, M. D., Atapattu, T., & Thilakaratne, M. (2024). Advancing Community Directories: Leveraging LLMs for Automated Extraction in MARC Standard Venue Availability Notes. In ALTA 2024 - Proceedings of the 22nd Annual Workshop of the Australasian Language Technology Association (pp. 118-129). Canberra: Association for Computational Linguistics (ACL).
2022 Atapattu, T., Herath, M., Elvitigala, C., Zoysa, P. D., Gunawardana, K., Thilakaratne, M., . . . Falkner, K. (2022). EmoMent: An Emotion Annotated Mental Health Corpus from Two South Asian Countries.. In N. Calzolari, C. -R. Huang, H. Kim, J. Pustejovsky, L. Wanner, K. -S. Choi, . . . S. -H. Na (Eds.), COLING (pp. 6991-7001). International Committee on Computational Linguistics.
2020 Thilakaratne, M., Falkner, K., & Atapattu Mudiyanselage, T. (2020). Connecting the Dots: Hypotheses Generation by Leveraging Semantic Shifts. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 12085 LNAI (pp. 328-340). Switzerland: Springer.
DOI Scopus1 WoS1
2020 Thilakaratne, K., Falkner, K., & Atapattu Mudiyanselage, T. (2020). Information extraction in digital libraries: First steps towards portability of lbdworkflow. In Proceedings of the 2020 ACM/IEEE Joint Conference on Digital Libraries (JCDL) (pp. 345-348). online: ACM.
DOI Scopus2
2020 Atapattu Mudiyanselage, T., Falkner, K., & Thilakaratne, K. (2020). Garbage in, garbage out? an empirical look at information richness of lbd input types. In Proceedings of the ACM/IEEE Joint Conference on Digital Libraries (JCDL) (pp. 369-372). online: ACM.
DOI
2018 Thilakaratne, M., Falkner, K., & Atapattu, T. (2018). Automatic detection of cross-disciplinary knowledge associations. In ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Student Research Workshop (pp. 45-51). online: Association for Computational Linguistics.
DOI Scopus6
2017 Thilakaratne, M., Weerasinghe, R., & Perera, S. (2017). Knowledge-Driven Approach to Predict Personality Traits by Leveraging Social Media Data. In J. E. Guerrero (Ed.), Proceedings - 2016 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2016 (pp. 288-295). Piscataway, New Jersey, USA: IEEE.
DOI Scopus7
2016 Thilakaratne, K. M., Weerasinghe, R., & Perera, S. (2016). Knowledge Driven Approach to Predict Personality Traits by Leveraging Social Media Data. In Proceedings of 2016 IEEE/WIC/ACM International Conference on Web Intelligence (WI) (pp. 288-295). online: IEEE.
DOI WoS7

Year Citation
2024 Athukoralage, D., Atapattu, T., Thilakaratne, M., & Falkner, K. (2024). LT4SG@SMM4H24: Tweets Classification for Digital Epidemiology of
Childhood Health Outcomes Using Pre-Trained Language Models.

 

Grants & Funding ($209,000.00)

  • Defence Innovation Partnership: AI for Decision Making Initiative by Office of National Intelligence. “Contextually Situated Anomaly Detection”

    Markus Wagner, Chetan Arora, Menasha Thilakaratne, Christoph Treude, Wei Zhang - Chief Investigator 2021-2022

  • Defence Innovation Partnership: AI for Decision Making Initiative by Office of National Intelligence. “Automated glossary generation for effective information extraction from COVID-19 related scientific articles”

    Thushari Atapattu, Menasha Thilakaratne - Chief Investigator 2020-2021

  • Department of Industry, Science, Energy and Resources. "MindSpace – a Fitbit for language" 

    Thushari Atapattu, Menasha Thilakaratne, Kasun Gunawardana, Kasun De Zoysa - Chief Investigator 2021-2022

  • UoA CMS Research Grants - Principal Investigator 2023 - 2023 (UoA)

  • UoA Start-up Grant - Principal Investigator 2023 - 2025 (UoA)

 

Grant and Recognition:

  • "SCANN: Security Classification using Artificial Neural Networks" ($273,960)

     Finalist of the National Intelligence Postdoctoral Grant (NIPG)

 

Course Coordination & Teaching:

  • COMP SCI 7210: Foundations of Computer Science Python A (Semester 2 - 2024)
  • COMP SCI 7211: Foundations of Computer Science Python B (Semester 2 - 2024)
  • COMP 1010: Puzzle Based Learning (Semester 1 - 2024)
  • COMP SCI 7211: Foundations of Computer Science Python B (Semester 1 - 2024)
  • COMP SCI 7210: Foundations of Computer Science Python A (OTP6 - 2023)
  • COMP SCI 7211: Foundations of Computer Science Python B (OTP5 - 2023)
  • COMP SCI 7210: Foundations of Computer Science Python A (OTP4, OTP5 - 2022)
  • COMP SCI 7210: Foundations of Computer Science Python A (Trimester 1, 2, & 3 - 2022)
  • COMP SCI 7211: Foundations of Computer Science Python B  (Trimester 1, 2, & 3 - 2022)
  • COMP SCI 7327: Concepts in Artificial Intelligence and Machine Learning (Trimester 1 - 2022)
  • COMP SCI 7317: Using Machine Learning Tools PG (Trimester 2 - 2022)
  • COMP SCI 7210: Foundations of Computer Science Python A (Semester 2 - 2021)
  • COMP SCI 7211: Foundations of Computer Science Python B (Semester 2 - 2021)

Curriculum Design and Development for the Postgraduate Students Using Mastery Learning Framework:

  • Project Lead: COMP SCI 7210: Foundations of Computer Science Python A (For Trimester and Semester teaching since 2022)
  • Project Lead: COMP SCI 7211: Foundations of Computer Science Python B  (For Trimester and Semester teaching since 2022)

Course Design:

  • COMP SCI 7317: Using Machine Learning Tools PG (For Trimester teaching - 2022)

 

Certifications:

  • Learning to Teach Online by UNSW Sydney (The University of New South Wales)
  • University Teaching by The University of Hong Kong
  • Blended Language Learning: Design and Practice for Teachers by University of Colorado Boulder
  • Inclusive Online Teaching Teach-Out by Johns Hopkins University
  • Resilient Teaching Through Times of Crisis and Change by the University of Michigan
  • Online education: The foundations of online teaching by Macquarie University
  • Instructional Design Foundations and Applications by University of Illinois at Urbana-Champaign (in progress)
  • Foundations of Teaching for Learning: Curriculum by Commonwealth Education Trust (in progress)

Date Role Research Topic Program Degree Type Student Load Student Name
2022 - 2025 Co-Supervisor Developing Language Resources and Advancing AI Techniques for Automatic Detection of Cyberbullying Causes Doctor of Philosophy Doctorate Full Time Isuru Mahagani Arachchige

Date Role Research Topic Location Program Supervision Type Student Load Student Name
2022 - ongoing Principal Supervisor Exploring outlier-detection techniques to detect fake news University of Adelaide - Honours - Jacob Thomas Schwarz
2022 - ongoing Principal Supervisor Classifying Argumentative Structures in Student Writing University of Adelaide - Honours - Olivia Florence Byrnes
2022 - ongoing Co-Supervisor Student Writing Evaluation using Explainable AI University of Adelaide - Doctorate - Abhilash Sridhara
2021 - ongoing Co-Supervisor PRISMA Methodology The University of Adelaide - Other - Dasuni Jayawickrama (Research Assistant)
2021 - ongoing Co-Supervisor Masters of Computing & Innovation (MCI) projects The University of Adelaide - Master - 12 Masters Students
2021 - ongoing Co-Supervisor Emotion-trigger extraction from unstructured text The University of Adelaide - Honours - Dasuni Jayawickrama (Advanced Topics Student)
2021 - ongoing Co-Supervisor Emotion-cause modeling from Natural Language text The University of Adelaide - Honours - Georgia Zhang (Honours in Computer Science Student)
2020 - 2021 Co-Supervisor Systematic literature review on emotion-cause extraction from unstructured text The University of Adelaide - Other - Dasuni Jayawickrama (Research Assistant)

Date Topic Location Name
2022 - ongoing Multi Task Learning University of Adelaide Ankit Yadav
2021 - ongoing Adobe Analytics Challenge 2021 The University of Adelaide Ankit Yadav

Date Role Membership Country
2022 - ongoing Member STEM Women Australia

Date Title Type Institution Country
2022 - ongoing Transactions on Learning Technologies Peer Review IEEE -
2021 - ongoing Scientometrics (SCIM) Peer Review Springer Journals -
2020 - ongoing Bioinformatics Peer Review Oxford Academic -

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