Gyunam Park

Gyunam Park

Researcher/Ph.D. Candidate

Biography

I’m Gyunam Park, a Ph.D. candidate and computer science researcher specializing in process mining at the chair of Process and Data Science (PADS), which is led by Prof. Dr. Wil M.P. van der Aalst. I am deeply passionate about designing/developing/implementing algorithms and methods to analyze event data in order to understand the underlying processes, e.g., healthcare, education, manufacturing processes. My research primarily revolves around object-centric process mining, which involves analyzing the interactions between objects or entities within processes, and action-oriented process mining, wherein the insights derived from object-centric process mining are translated into actions. Check out Google Scholar for my recent publications.

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Research Projects

AIStudyBuddy

AIStudyBuddy

This project aims to introduce AI-driven resources and assessments to enhance the teaching and learning experiences for students and curriculum planners. The AI-enabled ‘study companion’ tool offers targeted assistance to students, like setting objectives to secure top grades in a course and generating suggestions to meet those objectives. The AI-integrated ‘companion analytics’ tool equips curriculum planners with dashboards and assists them in the process of (re)structuring study programs.

Process Mining over SAP Data (PM-SAP)

Process Mining over SAP Data (PM-SAP)

The initial and most costly phase in process mining involves retrieving, converting, and uploading event logs from information systems. Specifically, pulling event data from prevalent ERP platforms like SAP is a significant hurdle due to the data’s magnitude and organization. The purpose of this project is to first obtain object-focused event data from SAP ERP platforms, and then uncover and examine both familiar and unfamiliar processes within these systems.

Development of best reference resource mining algorithm, *in cooperation with Samsung Electronics*

Development of best reference resource mining algorithm, in cooperation with Samsung Electronics

The importance of efficiently operating and managing manufacturing equipment in a process is highlighted in this research. By utilizing process mining techniques, analysis of equipment status and operation status becomes possible. The research aims to develop an equipment mining algorithm for deriving the Best Reference equipment. The study involves analyzing core semiconductor manufacturing processes, identifying problem equipment, engaging in process mining technology sensing activities that include technology and case introductions, and developing a methodology for identifying the Best Reference equipment using process mining techniques.

Software Projects

OCPA: Object-Centric Process Analysis
A Python library dedicated to the analysis of object-centric event data. The library includes capabilities for handling and processing object-centric event logs, carrying out process discovery, assessing process models, analyzing process performance, and supporting predictive process monitoring. This project is a collaboration with Niklas Adams.
OCPA: Object-Centric Process Analysis
ProAct: Action-Oriented Process Mining
A Tool for Action-Oriented Process Mining: Turning Events to Actions. Action-oriented process mining focuses on generating necessary management actions that enhance business processes’ performance. These actions are derived by analyzing event data through process mining techniques. ProAct is a tool that supports action-oriented process mining. ProAct is comprised of three main components: ProAct: Monitoring Engine, ProAct: Action Engine, ProAct: Impact Analysis.
ProAct: Action-Oriented Process Mining

Recent Publications

Super Variants
Super Variants
Improving Predictive Process Monitoring Using Object-Centric Process Mining
Improving Predictive Process Monitoring Using Object-Centric Process Mining
Incorporating Behavioral Recommendations Mined from Event Logs into AI Planning
Overstock Problems in a Purchase-to-Pay Process: An Object-CentricProcess Mining Case Study
A Generic Approach to Extract Object-Centric Event Data from Databases Supporting SAP ERP
A Generic Approach to Extract Object-Centric Event Data from Databases Supporting SAP ERP
Performance-preserving event log sampling for predictive monitoring
Interactive Process Identification and Selection from SAP ERP
Analyzing an After-Sales Service Process Using Object-Centric ProcessMining: A Case Study
Checking Constraints for Object-Centric Process Executions
Extracting Rules from Event Data for Study Planning
Explainable Predictive Decision Mining for Operational Support
Explainable Predictive Decision Mining for Operational Support
ocpa: A Python library for object-centric process analysis
ocpa: A Python library for object-centric process analysis
Detecting Context-Aware Deviations in Process Executions
Detecting Context-Aware Deviations in Process Executions
A Framework for Extracting and Encoding Features from Object-Centric Event Data
A Framework for Extracting and Encoding Features from Object-Centric Event Data
OPerA: Object-Centric Performance Analysis
OPerA: Object-Centric Performance Analysis
Event Log Sampling for Predictive Monitoring
Predictive process monitoring is a subfield of process mining that aims to estimate case or event features for running process …
Event Log Sampling for Predictive Monitoring
A Scalable Database for the Storage of Object-Centric Event Logs

Blog Posts

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