I am fascinated by the science that takes data from the real world and transforms them into useful insights by discovering business process models or training descriptive and predictive models. I earned my Ph.D. in process and data science at RWTH Aachen University in Germany, under the supervision of Prof. Wil van der Aalst, the godfather of process mining. I am currently working as a Technical Product Manager and Sr. Researcher at SAP SE. I am also a former SAP Technical Consultant and was involved in several SAP ABAP development, SAP Fiori, and SAP PI/PO projects.
Experience
Senior Process and Data Scientist
Responsibilities include:
- Driving the process graph benchmarking project
- Driving the data topics of the transformation advisor project
- Fostering process-related insights based on event data
Process and Data Scientist (PhD Candidate)
Responsibilities include:
- Internal lead of the machine learning for process mining project (ML4ProM) at PADS
- Internal lead of the AI study buddy project (AIStudyBuddy) at PADS
- Researching on reponsible data science
- Researching on process-aware data science over SAP focusing on object-centric event data
- Researching on federated (inter-organizational) process mining
- Designing and implementing state-of-the-art privacy preservation techniques
- Teaching on process and data science
SAP Technical Consultant
Responsibilities include:
- Developing SAP ABAP applications for FI, MM, and SD modules
- Designing and developing SAP PI/PO projects
- Designing and developing SAP Fiori apps
Software Developer
Freelance
Some projects:
- Developing a web-based app for user account management (PHP)
- Developing a database search engine tool (C#)
- Developing a scheduling system for FMS (C#)
- Enhancing FileZilla FTP Server by adding new commands (C++)
- Developing a Gmail reader tool (Perl)
Awards & Honors
Best Paper Award
The PQMI Workshop of ICPM Conference
Best Reviewer Award
International Conference on Process Mining (ICPM)
The 2021 Best Paper Award from the DKE Journal of Elsevier
The 2021 Best Paper Award from the DKE Journal of Elsevier
The ICT Young Researcher Award
The ICT Young Researcher Award of RWTH Aachen University - PhD Category
Best Paper Award
The EduPM Workshop of ICPM Conference
Best Paper Award
The RPM Workshop of ICPM Conference
Best Paper Award Runner-Up
CoopIS Conference
Destinguished Paper Award
RCIS Conference
Best Paper Award
SIMPDA Conference
Among Top 0.05% Students of CS
University Entrance Exam (Master’s Degree)
Projects
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The goal of this project is to provide AI-based tools and analysis for students and study program designers to increase the quality of teaching and learning. The AI-based study buddy tool provides goal-oriented help for students such as setting a goal to achieve a high grade in a course and getting recommendations for that goal. The AI-based buddy analytics tool provides dashboards for study program designers and supports them to (re)design study programs.
In this project, the goal is to support and comprehend process mining results such as process models with predictive machine learning techniques. An example is to predict deviations from the reference model as early as possible. All the machine learning techniques are supported by explainable AI (XAI) to add transparency to decisions made by black-box models.
The extraction, transformation, and loading of event logs from information systems is the first and the most expensive step in process mining. In particular, extracting event data from popular ERP systems such as SAP poses major challenges, given the size and the structure of the data. The goal of this project is to first extract object-centric event data from SAP ERP systems, and then discover and analyze well-known and unknown processes from such systems.
RPM (Responsible Process Mining) aims to deal with FACT (Fairness, Accuracy, Confidentiality, and Transparency) challenges in process mining. This project is focused on privacy and confidentiality aspects, where process mining algorithms are applied with respect to the private (sensitive) information of individuals (organization).
In this project, I was working as SAP technical consultant, where I was involved in developing SAP applications (transactions) using SAP ABAP programming. I was also an SAP Fiori developer and PI/PO (Process Integration/Process Orchestration) architect.
An online community is a virtual community where people can express their opinions and their knowledge freely. There is a great deal of information in online communities. However, there is no way to determine its authenticity. Thus, the knowledge which has been shared in online communities is not reliable. The goal of this project is to determine the expertise level of users and find experts in online communities in order to evaluate the accuracy of posted comments.
Publications
Quickly discover relevant content by filtering publications.
(2026).
Enhancing explainability in process variant analysis: a framework for detecting and interpreting control-flow changes.
Softw. Syst. Model..
(2025).
Enriching Object-Centric Event Data with Process Scopes: A Framework for Aggregation and Analysis.
CoRR.
(2025).
Federated conformance checking.
Inf. Syst..
(2025).
Identifying Process Improvement Opportunities Through Process Execution Benchmarking.
Enterprise, Business-Process and Information Systems Modeling - 26th International Conference, BPMDS 2025, and 30th International Conference, EMMSAD 2025, Vienna, Austria, June 16-17, 2025, Proceedings.
(2025).
Releasing differentially private event logs using generative models.
Data Knowl. Eng..
