QUT - Academic profiles - Dr Mythreyi Velmurugan

I am passionate about responsible data science and addressing real-world challenges using data. My research interests lie at the intersection of data analytics and process science, with a focus on leveraging data to drive meaningful impact. I completed my PhD thesis on the use of existing Explainable AI (XAI) techniques for tabular data, contributing to the promotion of transparency in machine learning and AI technologies.

Pronouns: she / her

+61 7 3138 7838

m.velmurugan@qut.edu.au

QUT alumni

Personal details

Positions

Associate Lecturer (TIEA)
Faculty of Science,
School of Information Systems

Research field

Information systems, Data management and data science, Machine learning

Field of Research code, Australian and New Zealand Standard Research Classification (ANZSRC), 2020

Qualifications

PhD (Queensland University of Technology)

Professional memberships and associations

A member of Women in Technology (WiT)
Associate Fellow of the Higher Education Academy (AFHEA)

Publications

Velmurugan, M., Ouyang, C., Moreira, C. & Sindhgatta Rajan, R. (2021). Evaluating Fidelity of Explainable Methods for Predictive Process Analytics. Intelligent Information Systems: CAiSE Forum 2021, Melbourne, VIC, Australia, June 28 – July 2, 2021, Proceedings, 64–72. https://eprints.qut.edu.au/211176
Velmurugan, M., Ouyang, C., Pinto Moreira, C. & Sindhgatta, R. (2021). Evaluating Stability of Post-hoc Explanations for Business Process Predictions. Service-Oriented Computing: 19th International Conference, ICSOC 2021, Virtual Event, November 22-25, 2021, Proceedings, 49–64. https://eprints.qut.edu.au/214090
Velmurugan, M., Watson, J., Obst, T. & Ouyang, C. (2022). Supporting carers in online role-diverse communities: A case study in Australia. Health and Social Care in the Community, 30(6). https://eprints.qut.edu.au/235272
Velmurugan, M., Ouyang, C., Sindhgatta, R. & Pinto Moreira, C. (2023). Through the looking glass: Evaluating post hoc explanations using transparent models. International Journal of Data Science and Analytics. https://eprints.qut.edu.au/243164
Velmurugan, M., Watson, J. & Bruce, C. (2017). Online peer-to-peer sobriety support: a conceptualization of the peer to peer social support mechanisms in an online 'Stop Drinking' community. Proceedings of the 28th Australasian Conference on Information Systems, 1–11. https://eprints.qut.edu.au/128683

QUT ePrints

For more publications by Mythreyi, explore their research in QUT ePrints (our digital repository).

View more publications

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2025

Velmurugan, M., Ouyang, C., Xu, Y., Sindhgatta, R., Wickramanayake, B. & Moreira, C. (2025). Developing guidelines for functionally-grounded evaluation of explainable artificial intelligence using tabular data. Engineering Applications of Artificial Intelligence, Article 109772, 141. https://eprints.qut.edu.au/254859

2023

Velmurugan, M., Ouyang, C., Sindhgatta, R. & Pinto Moreira, C. (2023). Through the looking glass: Evaluating post hoc explanations using transparent models. International Journal of Data Science and Analytics. https://eprints.qut.edu.au/243164

2022

Velmurugan, M., Watson, J., Obst, T. & Ouyang, C. (2022). Supporting carers in online role-diverse communities: A case study in Australia. Health and Social Care in the Community, 30(6), e6030-e6043. https://eprints.qut.edu.au/235272

2021

Moreira, C., Chou, Y., Velmurugan, M., Ouyang, C., Sindhgatta, R. & Bruza, P. (2021). LINDA-BN: An Interpretable Probabilistic Approach for Demystifying Black-box Predictive Models. Decision Support Systems, Article 113561, 150. https://eprints.qut.edu.au/211178
Velmurugan, M., Ouyang, C., Moreira, C. & Sindhgatta Rajan, R. (2021). Evaluating Fidelity of Explainable Methods for Predictive Process Analytics. Intelligent Information Systems, 64–72. Springer. https://eprints.qut.edu.au/211176
Velmurugan, M., Ouyang, C., Pinto Moreira, C. & Sindhgatta, R. (2021). Evaluating Stability of Post-hoc Explanations for Business Process Predictions. Service-Oriented Computing, 49–64. Springer. https://eprints.qut.edu.au/214090
Velmurugan, M. (2021). Design and evaluation of explainable methods for predictive process analytics. Proceedings of the Doctoral Consortium Papers Presented at the 33rd International Conference on Advanced Information Systems Engineering (CAiSE 2021), 49–58. Sun SITE Central Europe (CEUR). https://eprints.qut.edu.au/254335

2020

Bandara, W., Velmurugan, M. & Leemans, S. (2020). Building 'holistic' Business process modelling skills for IS graduates. Proceedings of the 41st International Conference on Information Systems (ICIS 2020), Association for Information Systems. https://eprints.qut.edu.au/205803

2017

Velmurugan, M., Watson, J. & Bruce, C. (2017). Online peer-to-peer sobriety support: a conceptualization of the peer to peer social support mechanisms in an online 'Stop Drinking' community. Proceedings of the 28th Australasian Conference on Information Systems, 1–11. University of Tasmania. https://eprints.qut.edu.au/128683

A complete list of publications is available at: https://www.qut.edu.au/about/our-people/academic-profiles/m.velmurugan

Dr Mythreyi Velmurugan

Biography