Moe Thandar

Moe Thandar is a prominent academic researcher in the field of Process Mining and Business Process Management. Their work spans over 160 publications from 2012 to 2025, focusing on advancing methodologies for process analysis, data quality, and automation in healthcare, business, and cybersecurity domains. They have collaborated with leading institutions globally, contributing to standards like the IEEE XES format for process event data.

• Key areas of expertise: Event log analysis, data-driven process improvement, robotic process automation (RPA), and privacy-preserving techniques.
• Notable contributions include frameworks like xPM for integrating exogenous data and SwiftMend for repairing process logs.
• Active in conferences such as BPM, CAiSE, and ICPM, often serving as editor or co-author in proceedings.

Research emphasizes practical applications in healthcare (e.g., patient flow optimization), aviation safety, and cost-effective process management. Their work bridges theoretical advancements with real-world implementations, addressing challenges like data quality, scalability, and ethical considerations.