Researcher and Lecturer
School of Computer Science
Faculty of Engineering, Computer and Mathematical Sciences
I am a member of the Computer Science Education Research (CSER) group and the Language Technology for Social Good (LT4SG) group in the School of Computer Science at the University of Adelaide. My main research expertise is in the areas of data mining, natural language processing, machine learning, deep learning, and semantic web. So far, I have applied my knowledge in these research areas into diverse problem domains, including scientific literature mining, medicine, social sciences, education and psychology.
Date Position Institution name 2021 Researcher & Lecturer University of Adelaide 2017 - 2020 PhD student University of Adelaide, Adelaide
Awards and Achievements
Date Type Title Institution Name Country Amount 2021 Award Dean's Commendation for Doctoral Thesis Excellence The University of Adelaide 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 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.
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 Scopus9 WoS4
2019 Thilakaratne, M., Falkner, K., & Atapattu Mudiyanselage, T. (2019). A systematic review on literature-based discovery workflow. PEERJ COMPUTER SCIENCE, 5, 40 pages.
DOI WoS7 Europe PMC1
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 Scopus11 WoS3
Year Citation 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.
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.
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.
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.
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.
- "Contextually Situated Anomaly Detection"
funded by Defence Innovation Partnership
in collaboration with the Deakin University, Australia
- "MindSpace – a Fitbit for language"
funded by the Department of Industry, Science, Energy and Resources
in collabotation with the University of Colombo, Sri Lanka
- "Automated glossary generation for effective information extraction from COVID-19 related scientific articles"
funded by Defence Innovation Partnership
- "SCANN: Security Classification using Artificial Neural Networks"
Finalist of the National Intelligence Postdoctoral Grant (NIPG)
- Foundations of Computer Science Python A (COMP SCI 7210) and Python B (COMP SCI 7211) courses at the University of Adelaide
The main philosophy that underpins my teaching is based on student-centred methods. This helps students engage through immersive, realistic and project-based learning activities, enabling them to participate in an applied and motivating learning context. This helps students delve deeply and explore course topics, while also obtaining an in-depth understanding and long-term retention of the course content.
I am a huge fan of the flipped classroom approach, using online modules to deliver pre-classroom information-based content such as short video clips, notes, embedded quizzes, and other interactive content. This enables the students to pre-engage and think about the topics and to attend classes equipped with some sufficient understanding of information. In this way, we provide them with the opportunity to meaningfully interact and engage during face-to-face times such as workshops. This also allows them to develop extended concepts during the workshops, while further deepening their understanding of the course content. Throughout this process, I also ensure that every interaction that happens in the classroom supports a positive and inclusive learning environment.
Due to my background in Computer Science, and being part of the Computer Science Education Research (CSER) group, I love to use technology/tools to enhance and support the learning experiences of students. The use of technology is not only limited to my pre-class online materials, but also indicates new tools that I would like to integrate into my learning environments.
- 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 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)
Other Supervision Activities
Date Role Research Topic Location Program Supervision Type Student Load Student Name 2021 - ongoing Co-Supervisor Emotion-trigger extraction from unstructured text The University of Adelaide — Honours — Dasuni Jayawickrama (Advanced Topics Student) 2021 - ongoing Co-Supervisor Masters of Computing & Innovation (MCI) projects The University of Adelaide — Master — 12 Masters Students 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)
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