Asara Senaratne
Lecturer (Teaching and Research)
College of Science and Engineering
Dr. Asara Senaratne is a Lecturer with the College of Science and Engineering at Flinders University, where she specializes in anomaly detection, data visualization, and knowledge representation within the realm of Computer Science.
Her research interests predominantly focus on applying Artificial Intelligence (AI), Machine Learning (ML), and Data Science techniques to enhance data quality and knowledge discovery. This includes exploring innovative methods for anomaly detection in graphs, advancing industrial automation, and improving human-computer interactions. Currently, her research focuses on developing robust models for anomaly detection in diverse domains, including health, the semantic web, cyberspace, and industry 4.0, thereby generating valuable insights for decision-making.
Previously, Asara worked as a Research Fellow at the Industrial AI Research Centre, University of South Australia, where she contributed to the FEnEx CRC project that aimed to develop open specifications for interoperable analytics, facilitating the digital transformation of industries, supporting Industry 4.0.
Asara completed her PhD in Computer Science at the Australian National University (ANU), where her thesis titled "Anomaly Detection in Graphs for Knowledge Discovery and Data Quality Enhancement" garnered her the People’s Choice award at both the Visualize Your Thesis 2022 and 3 Minute Thesis 2022 competitions. Her doctoral research involved pioneering methods for detecting anomalies in graph data to improve data integrity and uncover hidden patterns.
Her academic journey also includes a Master of Business Administration from Cardiff Metropolitan University and a B.Sc.(Hons) in Information Technology and Management from the University of Moratuwa, Sri Lanka. She was the valedictorian and received the gold medal for the highest overall GPA in her graduating class. Her professional memberships include being a Fellow of the Higher Education Academy and a professional member of the British Computer Society.
Doctor of Philosophy, Computer Science and Engineering, Australian National University (2019 → 2023)
BSc. (Hons) Information Technology and Management (IT Faculty Batch Top in 2018), University of Moratuwa (2014 → 2018)
Master of Business Administration, Cardiff Metropolitan University (2014 → 2016)
Higher Education Qualification, British Computer Society (2011 → 2013)
- Finalist, Falling Walls Lab Australia 2024.
- Winner, Falling Walls Lab Adelaide 2024.
- Winner of the People’s Choice award at the Visualize Your Thesis 2022 competition (video) organized by the ANU.
- Winner of the People’s Choice award at the 3 Minute Thesis 2022 competition organized by the College of Engineering, Computing and Cybernetics, Australian National University (view).
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One of the Doctoral Award recipients at the Doctoral Consortium of AUSDM 2022 held in Sydney, Australia.
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Higher degree research merit scholarship offered by the ANU in 2019.
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PhD Scholarship (International) full-time offered by the ANU in 2019.
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Scholarship to attend an International Study Visit to the UK in 2019 as a member of the Active Citizens program organized by the British Council, UK.
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Best overall academic performance in the Faculty of IT in 2018 (batch top out of 260 students).
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Gold medal for the student with the highest overall GPA (with a GPA of 4.08/4.2) in the Faculty of IT in 2018 (Valedictorian speech)
- Best lecturer award received at the BCS graduation in 2017.
Topic Coordination
Student Supervision
Research
As a passionate educator, my teaching interests lie in the areas of Databases, Data Engineering, Data Wrangling, Data Mining, Software Engineering, and AI and Machine Learning. I am dedicated to delivering an engaging learning experience, equipping students with both theoretical knowledge and practical skills. In Databases, I focus on efficient data storage and retrieval mechanisms, helping students build robust systems. Data Engineering and Data Wrangling courses explore data integration, quality assessment, and processing techniques, essential for transforming raw data into actionable insights. My expertise in Data Mining allows students to uncover patterns and valuable knowledge from large datasets, while Software Engineering fosters the development of scalable, maintainable systems. In AI and Machine Learning, I emphasize cutting-edge techniques and their real-world applications, preparing students to tackle complex challenges in an evolving technological landscape.
Professional Qualifications
- Fellow of the Higher Education Academy (FHEA)
- Professional Member of the British Computer Society (MBCS)
- Associate Member of the Australian Computer Society.
Engagements
- Reviewer for the journals Computers & Security, IEEE Network Magazine, and Data Science and Engineering.
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Publicity chair and a member of the organizing committee of the 22nd Australasian Data Science and Machine Learning (AusDM’24) conference, which will be held in Melbourne, Australia in November 2024.
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Doctoral symposium chair and a member of the organizing committee of the 21st Australasian Data Science and Machine Learning (AusDM’23) conference, held in Auckland, New Zealand in December 2023.
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South Australia 5042
South Australia | Northern Territory
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