Turning data into intelligence for processes and decisions.
The Analytics & Information Management (AIM) Lab at POSTECH develops data-driven methods to understand how processes work, determine what should happen next, and build intelligent solutions for real-world problems.
Research areas
Six areas the lab works in. They overlap far more than they compete — most projects pull on several at once.
Process Mining
Discovering, monitoring, and improving real-world processes from event data, including process discovery, conformance checking, object-centric process mining, event abstraction, and predictive process monitoring.
Recommender Systems
Developing personalized and context-aware recommendation methods, with a particular focus on fashion, customer preferences, and data-driven decision support.
Applied AI
Developing AI and machine learning methods for real-world problems, including deep learning, generative AI, large language models, and domain-specific foundation models.
AI-Driven Process Innovation
Combining process intelligence and AI to identify improvement opportunities, redesign workflows, automate decision-making, and develop new ways of working with human and AI collaboration.
Simulation & Digital Twins
Building data-driven simulation models and digital twins to understand, evaluate, and improve complex systems, particularly in manufacturing and healthcare.
Predictive & Prescriptive Analytics
Developing predictive and optimization methods to anticipate outcomes, recommend actions, allocate resources, and support better operational decisions.
About the Lab
The Analytics & Information Management (AIM) Lab at POSTECH conducts research at the intersection of Process Mining, Recommender Systems, and Applied AI. We develop data-driven methods to understand how complex processes work, determine what should happen next, and build intelligent solutions for real-world problems.
Our research combines artificial intelligence, machine learning, simulation, optimization, and digital twins to discover, predict, and improve process behavior, provide personalized recommendations, and support better operational decisions. Through these approaches, we aim to turn complex data into actionable intelligence and measurable improvement.
A defining feature of the AIM Lab is our close collaboration with industry. Our research has been supported by the Korean government and leading companies including Samsung Electronics, Samsung C&T, HD Hyundai, and POSCO, with projects spanning manufacturing, healthcare, and the fashion industry. These long-term collaborations provide opportunities to develop and validate new methods with real-world data and translate research into practical impact.
The lab has published more than 150 scientific papers in leading journals and conferences, including Decision Support Systems, Information Systems, Journal of Information Technology, International Journal of Medical Informatics, Business Process Management (BPM), and the International Conference on Process Mining (ICPM).
We are equally committed to translating research into practice. Puzzle Data, Korea’s first process mining software company, was established as a spin-off from the AIM Lab, bringing process mining research into enterprise applications. ZenAii Co., an AI-powered fashion recommendation company, was also spun off from the lab, translating our research in recommender systems and AI into personalized fashion services. Together, these ventures demonstrate our commitment to turning academic research into technologies, solutions, and businesses with real-world impact.
Latest news
Awards, appointments and events from the lab.
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NewsHyunjun Jung Begins His Ph.D. and Heeryeong Park Joins the Lab (정현준 박사과정 진학 및 박희령 연구원 합류)
Hyunjun Jung continues in the lab as a Ph.D. student in the Department of Industrial and Management Engineering from September 2026, after completing his master…
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NewsASPAI 2026: Process Mining Industry Day and the 3rd Process Mining Summer School (ASPAI 2026 — 프로세스 마이닝 인더스트리 데이 및 제3회 서머스쿨 개최)
The Wil van der Aalst Data & Process Science Research Center and the Graduate School of Convergence hosted the Process Mining Industry Day and the 3rd Process M…
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NewsCelebrating Prof. Wil van der Aalst's 60th Birthday (Wil van der Aalst 교수 60주년 기념 심포지엄 참석)
Prof. Minseok Song of the Analytics & Information Management (AIM) Lab at POSTECH joined researchers and collaborators from around the world in Aachen, Germany,…
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NewsChapter Contributed to the Festschrift for Wil van der Aalst's 60th Birthday (Wil van der Aalst 교수 60세 기념 논문집에 챕터 기고)
Prof. Minseok Song and Prof. Jae-Yoon Jung contributed the chapter “Process Mining in the Era of Smart Manufacturing: Applications, Limitations, and Opportuniti…
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NewsKongdan Zhou and Ingon Chu Begin Their Graduate Studies (Kongdan Zhou, Ingon Chu 대학원 입학)
Kongdan Zhou entered the Ph.D. programme in the Department of Industrial and Management Engineering, and Ingon Chu the M.S. programme in the Department of Defen…
Partners and funding
Our research is carried out with government agencies, hospitals and industry.
Considering graduate study?
We look for students who enjoy both the modelling and the messiness of real data. Ph.D., M.S. and undergraduate research positions open every semester.