Process Mining Summer School @POSTECH · Pohang

About

3rd Process Mining Summer School

The 3rd Process Mining Summer School follows the two previous successful editions in Aachen, Germany, in 2022 and in Bolzano, Italy, in 2026. It is the first edition of the Process Mining Summer School that is held in the Asia-Pacific region.

The Process Mining Summer School @POSTECH is the premier forum for exploring the intersection of process mining, data science, and AI in the region. Over two intensive days, a diverse community of participants and speakers from across the globe come together to learn and develop new approaches in the field. The curriculum covers process discovery and conformance checking in depth, alongside essential topics in data preprocessing, performance analysis, predictive analytics, and the ethical dimensions of responsible process mining. Beyond the lectures, participants engage in interactive hands-on sessions with both open-source and commercial process mining tools to apply theory to real-world scenarios.

Program

Two days at the POSCO International Center. Day 1 builds the foundations of process mining with hands-on tool sessions; Day 2 turns to AI and real-world case studies.

Day 1 Thursday, August 27 POSCO International Center · Large Meeting Room (1F)

08:45 ~ 09:00	OpeningMinseok Song (POSTECH) · Marco Comuzzi (UNIST)
09:00 ~ 10:30	RWTHUnlocking Process Intelligence: A 360° Introduction to Process Mining Wil van der Aalst
10:45 ~ 12:15	RWTHFrom Event Logs to Process Logic: The Basics of Process Discovery Wil van der Aalst
12:15 ~ 13:30	Lunch
13:30 ~ 14:30	RWTHConformance Checking: Token-Based Replay and Alignments Wil van der Aalst
14:45 ~ 15:30	QUTBuilding Strong Data Foundations for Process Mining Moe Wynn
15:45 ~ 16:45	CelonisHands-OnProcess Mining Hands-On A Poornima Dhall
17:00 ~ 18:00	SAP BTMHands-OnProcess Mining Hands-On B: AI Agent Mining in Practice Julian Lebherz · Tony (RaeSung) Park
18:00 ~	Dinner & Networking

Day 2 Friday, August 28 POSCO International Center · Large Meeting Room (1F)

08:45 ~ 09:45	UNISTUnleashing Predictive and Generative AI in Process Mining Marco Comuzzi
10:00 ~ 10:45	HUFSFederated Process Mining: Federated Event Log Generation for Process Discovery across Organizational Boundaries Bernardo Nugroho Yahya
10:45 ~ 11:30	TelkomProcess Mining Case Studies Angelina Prima Kurniati
11:30 ~ 12:15	SydneyEvidence-Based Evaluation of Process Mining in Healthcare Simon Poon
12:15 ~ 12:30	ClosingMinseok Song (POSTECH) · Marco Comuzzi (UNIST)
12:30 ~	Lunch

Lecturers

Meet the Lecturers

From the founder of process mining to the industry experts behind today's leading tools and research leaders across the Asia-Pacific — the faculty shaping the present and future of process intelligence.

RWTH Aachen

Wil van der Aalst

RWTH Aachen University · Germany

Intro to Process Mining · Process Discovery · Conformance Checking

Widely known as the "Godfather of Process Mining," Prof. van der Aalst leads the Process and Data Science (PADS) group at RWTH Aachen University and serves as Chief Scientist at Celonis. One of the most-cited computer scientists in the world and an IFIP, IEEE, and ACM Fellow, he is the author of the seminal book "Process Mining: Data Science in Action."

QUT

Moe Wynn

Queensland University of Technology · Australia

Building Strong Data Foundations for Process Mining

Prof. Wynn is a Professor in the Information Systems School at QUT, where she leads the Process Science group, and a steering committee member of the IEEE Task Force on Process Mining. Her research spans process data quality, cost-aware and cross-organisational process mining, and process automation.

Celonis

Poornima Dhall

Celonis

Process Mining Hands-On A (Celonis)

Poornima Dhall is a Lead Partner Manager for Academic Alliances (APAC) at Celonis. She works with universities and organizations across the Asia-Pacific region to introduce process mining, run training cohorts, and bring an industry perspective on applying the technology to real-world process improvement.

SAP BTM

Julian Lebherz

Strategic Solution Advisor, APAC · SAP BTM

Process Mining Hands-On B: AI Agent Mining in Practice

Julian Lebherz is a Strategic Solution Advisor for APAC in SAP Business Transformation Management (BTM) and a QUT Industry Fellow. With over a decade of specialized experience deploying process intelligence solutions and building delivery organizations across industries — from manufacturing to life sciences — he is recognized as one of the leading experts in the field, and helps enterprises realize sustainable value from the SAP Signavio suite.

SAP BTM

Tony (RaeSung) Park

Head of Solution Advisory, Korea · SAP BTM

Process Mining Hands-On B: AI Agent Mining in Practice

Tony (RaeSung) Park heads Solution Advisory for Korea in SAP Business Transformation Management (BTM), supporting process innovation for Korean enterprises with the SAP Signavio portfolio at its core. He co-leads the hands-on session with Julian Lebherz, bringing the perspective of local enterprise deployments.

UNIST

Marco Comuzzi

UNIST · South Korea

Unleashing Predictive and Generative AI in Process Mining

Prof. Comuzzi is an Associate Professor in the Department of Industrial Engineering at UNIST, where he leads the Intelligent Enterprise Lab and directs the Blockchain Research Center. He earned his PhD from Politecnico di Milano and previously held positions at Eindhoven University of Technology and City, University of London; his research centers on process mining, machine learning, and blockchain systems.

HUFS

Bernardo Nugroho Yahya

Hankuk University of Foreign Studies · South Korea

Federated Process Mining: Federated Event Log Generation across Organizational Boundaries

Prof. Yahya is a Full Professor in the Industrial & Management Engineering Department (Data Analytics Program) at Hankuk University of Foreign Studies. He holds a PhD in Industrial Engineering from Pusan National University, and his research spans machine learning, business process intelligence, process mining, and pattern analysis, with applications in supply chains and manufacturing.

Telkom Univ.

Angelina Prima Kurniati

Telkom University · Indonesia

Process Mining Case Studies

Prof. Kurniati is an Associate Professor in the School of Computing at Telkom University, with expertise in data science, data mining, and process mining. Her research applies process mining to healthcare — including oncology care pathways and disease-trajectory analysis on Indonesian health-insurance data — with an emphasis on process-data quality.

Univ. of Sydney

Simon Poon

The University of Sydney · Australia

Evidence-Based Evaluation of Process Mining in Healthcare

Prof. Poon is an Associate Professor in the School of Computer Science at the University of Sydney. His research sits at the intersection of health informatics, data analytics, and process mining, with a focus on evaluating how data-driven methods deliver measurable value in clinical and healthcare settings.

Curriculum

Lecture Overview

From foundational theory to hands-on practice, AI, and real-world case studies — here is how the two days unfold.

Day 1RWTHWil van der Aalst

Unlocking Process Intelligence: A 360° Introduction to Process Mining

Process mining serves as the essential bridge between data science and process science, utilizing event data to reveal how operational processes actually function in the real world. This session explores the core pillars of the field — discovery, conformance, and performance — demonstrating how organizations can automatically transform "digital footprints" into actionable insights and process improvements. By examining diverse process modeling notations such as BPMN and Petri nets alongside event data standards such as XES and OCEL, you will learn to navigate end-to-end processes, eliminate bottlenecks, and ensure compliance.

Day 1RWTHWil van der Aalst

From Event Logs to Process Logic: The Basics of Process Discovery

Process discovery automatically constructs models from event data, yet it must navigate the complex trade-offs between recall, precision, generalization, and simplicity. This session introduces the Directly-Follows Graph (DFG) as a scalable baseline and demonstrates how advanced filtering techniques are essential for isolating dominant behavior from infrequent "noise". We will dive into the core foundations of both bottom-up discovery — uncovering local patterns through the Alpha algorithm — and top-down discovery, which uses inductive mining to recursively decompose logs into sound-by-construction process trees.

Day 1RWTHWil van der Aalst

Conformance Checking: Token-Based Replay and Alignments

The goal of conformance checking is to compare observed behavior (i.e., event data) with modeled behavior (e.g., a BPMN model, a Petri net, or DFG) to discover compliance problems and diagnose them. This session explains the key techniques for conformance checking: token-based replay and alignments. These techniques are also needed to project performance information onto process models, enable machine learning on process data, and to evaluate process discovery techniques.

Day 1QUTMoe Wynn

Building Strong Data Foundations for Process Mining

Process event data is the cornerstone of process mining. The quality and structure of this data directly determine the accuracy and value of process mining insights. Thus, building high-quality event logs is essential for generating trustworthy insights and driving meaningful process improvements. This session will cover the core structures of case-centric and object-centric event data, discuss key considerations for event log preparation, and demonstrate the impact of data quality on process mining results.

Day 1CelonisHands-OnPoornima Dhall

Process Mining Hands-On A (Celonis)

A hands-on session working directly with the Celonis platform on real event data. From data connection to process visualization and the detection of bottlenecks and inefficiencies, participants learn to implement process intelligence with a commercial tool.

Day 1SAP BTMHands-OnJulian Lebherz · Tony (RaeSung) Park

Process Mining Hands-On B: AI Agent Mining in Practice

A hands-on session on what it takes to put AI agents to work on real business processes. Participants see how agent behaviour can be captured and mined like any other process — making the decisions and hand-offs of AI agents observable, measurable, and improvable — and apply the theory from earlier sessions on top of a commercial process intelligence platform.

Day 2UNISTMarco Comuzzi

Unleashing Predictive and Generative AI in Process Mining

This lecture examines the evolution of artificial intelligence (AI) in process mining over the past decade. It begins by exploring how predictive models of key process aspects can be developed by applying traditional machine learning techniques to event log data. The session then turns to the emerging role of generative AI, with a particular focus on Large Language Models (LLMs), and their potential to transform process mining. After analyzing how LLMs can influence different stages of the process mining lifecycle, the lecture concludes with a concrete application that leverages LLMs to assess and enhance the quality of event log data.

Day 2HUFSBernardo Nugroho Yahya

Federated Process Mining: Federated Event Log Generation for Process Discovery across Organizational Boundaries

This lecture introduces Federated Process Mining, a method for anonymizing local event logs and merging them into a federated event log. In the supply chain processes where multiple organizations are involved, it poses crucial challenges due to the information silo, privacy and interoperability concerns. The session introduces the concept of Horizontal Federated Learning (same process, different cohorts) and Vertical Federated Learning (same case split across organizational stages). The session details how local log anonymization, privacy-preserving event correlation, and federated log construction enable end-to-end process discovery across organizational boundaries without exposing transactional data.

Day 2TelkomAngelina Prima Kurniati

Process Mining Case Studies

Through a range of real-world applications, this session shows how theory translates into results. It shares experiences and lessons from domains — such as healthcare — where data quality is especially challenging.

Day 2SydneySimon Poon

Evidence-Based Evaluation of Process Mining in Healthcare

Covers how process mining is applied to the complex care and treatment pathways of clinical settings, with an emphasis on evidence-based evaluation — how the impact of process mining on the quality and efficiency of healthcare services can be assessed through patient-flow analysis and care-pathway improvement.

Registration

Register Now

Registration for the Process Mining Summer School @POSTECH is handled through the button below. Seats are limited, so we encourage you to register early.

The registration form is being finalized. Online sign-up opens soon.

Venue

Getting There

POSTECH · Aug 27–28

POSCO International Center Large Meeting Room (1F)

77, Cheongam-ro, Nam-gu, Pohang · POSTECH
Gyeongsangbuk-do, Republic of Korea

Location

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