Conrad Indiono

Conrad Indiono is a researcher in the Faculty of Computer Science affiliated with the Research Group Workflow Systems and Technology. Holding Dipl.-Ing. and BSc qualifications, he focuses on advancing business process technologies through formal methods and system innovation.

His research spans critical areas in workflow systems:

• Business Process Management and Compliance
• Instance-Spanning Constraints Formalization
• Forward Inference Algorithms
• High-Performance Fact Processing
• Process Choreography Dynamics
• Process Model Evolution

Publication trends from 2014-2020 reveal consistent contributions to business process formalization, with recent work emphasizing in-memory processing optimization and dynamic constraint handling. His 2020 Hiperfact paper rethinks inference algorithms for performance-critical environments, while 2017-2018 works address real-world challenges in process choreography change propagation and instance-spanning constraints.

No scientific awards were documented in available sources.

Advising activities and grant funding details are not specified in current records.

He actively contributes to the Research Group Workflow Systems and Technology, developing frameworks for process-aware information systems with emphasis on formalization techniques and inference engine optimization.