Asara Senaratne

Lecturer (Teaching and Research)

College of Science and Engineering

place Tonsley Building
GPO Box 2100, ADELAIDE, SA, 5001

Dr. Asara Senaratne is a Lecturer in Computer Science at Flinders University’s College of Science and Engineering, working at the intersection of AI, data, and real-world impact. Her work focuses on making complex data more trustworthy, interpretable, and actionable, especially in high-stakes domains like healthcare.

Her research spans anomaly detection, data visualisation, and knowledge representation, with a strong emphasis on how AI and machine learning can improve data quality and support better decision-making. She is particularly interested in uncovering hidden patterns in complex, graph-based data and translating those insights into practical applications.

Asara’s current work explores next-generation digital health solutions, including the development of Biological Digital Twins for elite athletes. This research integrates wearable data, physiological modelling, and AI to create personalised, real-time representations of athletes, supporting performance optimisation, injury prevention, and recovery. Alongside this, she is actively investigating digital interventions in healthcare, focusing on how data-driven systems can enhance patient outcomes while remaining ethical, secure, and user-centred.

A key thread across her research is data privacy and responsible AI. She is passionate about designing systems that not only generate insight but also respect data governance, interoperability, and trust ensuring that innovation in AI aligns with societal and regulatory expectations.

Prior to joining Flinders University, Asara was a Research Fellow at the Industrial AI Research Centre at the University of South Australia, where she contributed to the FEnEx CRC initiative; developing open, interoperable analytics frameworks to accelerate Industry 4.0 transformation.

She completed her PhD in Computer Science at the Australian National University, where her research on anomaly detection in graph data received wide recognition, including People’s Choice awards at both the Visualise Your Thesis and Three Minute Thesis competitions in 2022. Asara also holds an MBA from Cardiff Metropolitan University and a First-Class Honours degree in Information Technology and Management from the University of Moratuwa, where she graduated as valedictorian and gold medallist. She is a Fellow of the Higher Education Academy and a professional member of the British Computer Society.

Qualifications

Educational Qualifications

  • Doctor of Philosophy, Computer Science and Engineering, Australian National University (2024)
  • BSc. (Hons) Information Technology and Management (IT Faculty Batch Top in 2018), University of Moratuwa (2018)
  • Master of Business Administration, Cardiff Metropolitan University (2016)
  • Higher Education Qualification, British Computer Society (2013)

Professional Qualifications

  • Fellow of the Higher Education Academy (FHEA)
  • Professional Member of the British Computer Society (MBCS)
Honours, awards and grants

Grants

  • Cyber Resilience for Industry 4.0 Manufacturing: Janjua N., Williams T., Senaratne A., Mahmud A., Erp T V.,Flinders Factory of the Future SIRP Grant 2025. $82,000: 2025-2026.
  • Smart Energy Management using AI-Supported Digital Twin Simulations: Stephenson M., Erp T V., Brinkworth R., Pereira B., Senaratne A., Zanj A.,Mahmoudi A.,Bayat A.,Mahmud A.,Flinders Factory of the Future SIRP 2025: $85,551 2025-2026.
  • Digital CRC Project:  Improving Patient Care and Flow Management Using an Integrated Digital Platform – an Independent Benefit Analysis: Janjua  N., Ben-Tovim D., Senaratne A., Qin S., Bajger M., McGill A.: $461,702 2025-2028.

Awards

  • People’s Choice Award for the best e-poster titled Anomaly Detection for Prolongation of Health at Digital Health Week 2025.
  • 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).
  • Doctoral Award recipient at the Doctoral Consortium of AUSDM 2022 held in Sydney, Australia.
  • PhD Scholarship (International) full-time and Higher degree research merit scholarship offered by the ANU in 2019.
  • 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.
  • Gold medal for the student with the highest overall GPA (best overall academic performance) in the Faculty of IT in 2018 (Valedictorian speech)
  • Best lecturer award received at the BCS graduation in 2017.
Key responsibilities
  • Topic Coordination (Data Engineering)
  • HDR Supervision
  • Teaching and Research
Teaching interests

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.

Topic coordinator
COMP2031 Data Engineering
COMP8031 Data Engineering
Topic lecturer
COMP1711 Database Modelling and Information Management
COMP8711 Database Modelling and Information Management
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