Dr Sareh Sadeghianasl
Faculty of Science,
School of Information Systems
Biography
Sareh Sadeghianasl is a Research Fellow in Process Science in the School of Information Systems at QUT. As part of her PhD studies at QUT, she has developed open-source gamified techniques to detect and remedy data quality issues in event data for process mining. She also has experience working with Australian datasets from the insurance and health domains. She is currently involved in the quality assessment and root cause identification of data quality problems in electronic medical records of patients presenting at the Emergency Department of a Queensland hospital.Personal details
Positions
- Lecturer in Information Systems
Faculty of Science,
School of Information Systems
Keywords
Process mining, Data quality, Activity labels, Gamification
Research field
Information Systems
Field of Research code, Australian and New Zealand Standard Research Classification (ANZSRC), 2008
Qualifications
- Doctor of Philosophy (Queensland University of Technology)
Professional memberships and associations
QUT Centre for Data Science
IEEE Task Force on Process Mining
Australian Women in Technology
Business Process Management Association
Associate Fellow of the Higher Education Academy
Teaching
I have worked as a tutor for different units (e.g., IAB206, IAB201, and IAB321) at QUT in the past 3 years.
Experience
I have experience working with Australian datasets from the insurance and health domains. I am currently involved in the quality assessment and root cause identification of data quality problems in electronic medical records of patients presenting at the Emergency Department of a Queensland hospital.
Publications
- Suriadi, S., Turkay, S., Sadeghianasl, S. & ter Hofstede, A. (2020). Collaborative and interactive detection and repair of activity labels in process event logs. Proceedings of the 2020 2nd International Conference on Process Mining: ICPM 2020, 41–48. https://eprints.qut.edu.au/205630
- Sadeghianasl, S., ter Hofstede, A., Wynn, M. & Lim, S. (2019). A contextual approach to detecting synonymous and polluted activity labels in process event logs. On the Move to Meaningful Internet Systems: OTM 2019 Conferences: Confederated International Conferences: CoopIS, ODBASE, C&TC 2019, Proceedings (Lecture Notes in Computer Science, Volume 11877), 76–94. https://eprints.qut.edu.au/133873
QUT ePrints
For more publications by Sareh, explore their research in QUT ePrints (our digital repository).