{"count":11,"items":[{"body":"## Abstract\n\neuroFMX develops foundation models for trustworthy industrial generative AI in Europe, with 72 partners from 20 countries and 10 industrial pilots. The Eindhoven University of Technology contribution, which I co-lead, covers graph-based data modelling, neuro-symbolic AI and active inference for AI agents in manufacturing.\n\n## Objectives\n\n- Graph-based data modelling of manufacturing processes, building on object-centric event data.\n- Neuro-symbolic AI that combines foundation models with symbolic process models.\n- Active inference for AI agents that act in manufacturing processes.","budget":"EUR 45 M","date":"2026-01-01","funder":"European Commission","funding_kind":"research","grant_number":"101299128","id":"eurofmx","markdown_url":"https://www.gyunam.com/funding/eurofmx/index.md","partners":["72 partners from 20 countries","10 industrial pilots"],"period":"2026 – 2029","projects":[],"research_lines":["object-centric-process-mining","neuro-symbolic-process-learning"],"role":"Co-PI; co-author of the proposal and co-lead of the TU/e contribution","summary":"EU project building trustworthy foundation models for industrial generative AI; the TU/e contribution covers graph-based data modelling, neuro-symbolic AI and active inference for AI agents in manufacturing.","title":"euroFMX: Foundational Models for Trustworthy Industrial Generative AI in Europe","url":"https://www.gyunam.com/funding/eurofmx/","url_project":"https://eurofmx.eu"},{"body":"## Abstract\n\nIndustry collaboration with EY at Eindhoven University of Technology: development of a tool for EY's auditing processes.\n\n## Outputs\n\n- One conference paper submitted.","budget":"","date":"2026-01-01","funder":"EY (Ernst \u0026 Young)","funding_kind":"industry","grant_number":"","id":"ey-auditing","markdown_url":"https://www.gyunam.com/funding/ey-auditing/index.md","partners":[],"period":"2026 – present","projects":[],"research_lines":[],"role":"","summary":"Industry collaboration with EY on a tool for auditing processes.","title":"Auditing Process Improvement","url":"https://www.gyunam.com/funding/ey-auditing/","url_project":""},{"body":"## Abstract\n\nIndustry contract with Process Intelligence Solutions GmbH for the development of a process-mining software toolkit, carried out at Fraunhofer FIT.","budget":"","date":"2025-01-01","funder":"Process Intelligence Solutions GmbH","funding_kind":"industry","grant_number":"","id":"pmtk","markdown_url":"https://www.gyunam.com/funding/pmtk/index.md","partners":[],"period":"2025 – 2026","projects":[],"research_lines":[],"role":"PI; negotiated and lead the contract","summary":"Development of a process-mining software toolkit for Process Intelligence Solutions.","title":"PMTk: Process Mining Toolkit","url":"https://www.gyunam.com/funding/pmtk/","url_project":""},{"body":"## Abstract\n\nThe JUPITER AI Factory makes JUPITER, Europe's first exascale supercomputer, usable for AI. I am responsible for a Fraunhofer FIT task that supports start-ups, SMEs, industry and academia in using JUPITER for AI.","budget":"EUR 55 M","date":"2025-01-01","funder":"EuroHPC Joint Undertaking, German Federal Ministry of Education and Research (BMBF), and the science ministries of North Rhine-Westphalia and Hesse","funding_kind":"research","grant_number":"","id":"jaif","markdown_url":"https://www.gyunam.com/funding/jaif/index.md","partners":[],"period":"2025 – 2028","projects":[],"research_lines":[],"role":"Subtask lead; responsible for a Fraunhofer FIT task","summary":"EuroHPC AI Factory around JUPITER, Europe's first exascale supercomputer; Fraunhofer FIT task supporting start-ups, SMEs, industry and academia in using JUPITER for AI.","title":"JAIF: JUPITER AI Factory","url":"https://www.gyunam.com/funding/jaif/","url_project":"https://www.jaif.ai"},{"body":"## Abstract\n\nAI-BioDynamics builds a monitoring platform for biodiversity at scale. It combines satellite, radar and citizen-science data with knowledge-guided deep learning, transfer learning and process mining. I lead the German consortium at Fraunhofer FIT; the Korean partners are Seoul National University of Science and Technology, Kwangwoon University and Moonsoft, with Geo Engine GmbH on the German side.","budget":"EUR 1.3 M","date":"2025-01-01","funder":"German Federal Ministry of Education and Research (BMBF) and Korean Ministry of Science and ICT (MSIT), bilateral DE-KR programme","funding_kind":"research","grant_number":"","id":"ai-biodynamics","markdown_url":"https://www.gyunam.com/funding/ai-biodynamics/index.md","partners":["Fraunhofer FIT","Geo Engine GmbH","Seoul National University of Science and Technology","Kwangwoon University","Moonsoft Co. Ltd."],"period":"2025 – 2029","projects":[],"research_lines":["neuro-symbolic-process-learning"],"role":"PI (German side); author of the German proposal and lead of the German consortium","summary":"Bilateral German-Korean project building a biodiversity monitoring platform that combines satellite, radar and citizen-science data with knowledge-guided deep learning, transfer learning and process mining.","title":"AI-BioDynamics: AI for Scalable Biodiversity Monitoring","url":"https://www.gyunam.com/funding/ai-biodynamics/","url_project":""},{"body":"## Abstract\n\nInternal Fraunhofer project on process modeling with large language models, carried out at Fraunhofer FIT.","budget":"EUR 30 k","date":"2024-01-01","funder":"Fraunhofer ZV","funding_kind":"research","grant_number":"","id":"process-modeling-llms","markdown_url":"https://www.gyunam.com/funding/process-modeling-llms/index.md","partners":[],"period":"2024 – 2025","projects":[],"research_lines":["neuro-symbolic-process-learning"],"role":"","summary":"Fraunhofer-funded project on generating process models with large language models.","title":"Process Modeling Using LLMs","url":"https://www.gyunam.com/funding/process-modeling-llms/","url_project":""},{"body":"## Abstract\n\nIndustry contract with KNIME AG for the design and development of an open process-mining extension for the KNIME analytics platform, carried out at Fraunhofer FIT.","budget":"","date":"2024-01-01","funder":"KNIME AG","funding_kind":"industry","grant_number":"","id":"pm4knime","markdown_url":"https://www.gyunam.com/funding/pm4knime/index.md","partners":[],"period":"2024 – present","projects":[],"research_lines":[],"role":"PI; negotiated and lead the contract","summary":"Design and development of an open process-mining extension for the KNIME analytics platform.","title":"PM4KNIME: Process Mining Extension for KNIME","url":"https://www.gyunam.com/funding/pm4knime/","url_project":""},{"body":"## Abstract\n\nAIStudyBuddy introduces AI-driven resources and assessments to improve teaching and learning for students and curriculum planners. The AI-enabled study companion gives students targeted assistance, such as setting objectives for a course and generating suggestions to meet them. The companion analytics tool gives curriculum planners dashboards and support for (re)structuring study programmes.\n\n## Outputs\n\n- [Learning recommendations from educational event data in higher education](/publication/2024-jiis-learningrecommendation/)\n- [Extracting rules from event data for study planning](/publication/2023-icpm-edupm/)\n- [Unlocking learner engagement and performance](/publication/2024-kim-unlocking/)","budget":"EUR 3.9 M","date":"2023-01-01","funder":"German Federal Ministry of Education and Research (BMBF), project agency VDI/VDE-IT","funding_kind":"research","grant_number":"","id":"aistudybuddy","markdown_url":"https://www.gyunam.com/funding/aistudybuddy/index.md","partners":[],"period":"2023 – 2024","projects":[],"research_lines":["prescriptive-process-analytics"],"role":"Led the RWTH Aachen University team in two work packages on AI-based study support for students","summary":"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.","title":"AIStudyBuddy","url":"https://www.gyunam.com/funding/aistudybuddy/","url_project":"https://learntech.rwth-aachen.de/cms/LearnTech/Forschung/Projekte/~siepo/AIStudyBuddy/?lidx=1"},{"body":"","budget":"","date":"2019-01-01","funder":"Samsung Electronics","funding_kind":"industry","grant_number":"","id":"samsung-3rd","markdown_url":"https://www.gyunam.com/funding/samsung-3rd/index.md","partners":[],"period":"2019 – 2020","projects":[],"research_lines":["process-discovery-and-diagnostics"],"role":"","summary":"","title":"Root cause analysis of bottlenecks in FAB","url":"https://www.gyunam.com/funding/samsung-3rd/","url_project":""},{"body":"","budget":"","date":"2018-01-01","funder":"Samsung Electronics","funding_kind":"industry","grant_number":"","id":"samsung-2nd","markdown_url":"https://www.gyunam.com/funding/samsung-2nd/index.md","partners":[],"period":"2018","projects":[],"research_lines":["process-discovery-and-diagnostics"],"role":"","summary":"","title":"Development of algorithm for recommending best resource path using AI","url":"https://www.gyunam.com/funding/samsung-2nd/","url_project":""},{"body":"","budget":"","date":"2017-01-01","funder":"Samsung Electronics","funding_kind":"industry","grant_number":"","id":"samsung-1st","markdown_url":"https://www.gyunam.com/funding/samsung-1st/index.md","partners":[],"period":"2017","projects":[],"research_lines":["process-discovery-and-diagnostics"],"role":"","summary":"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.","title":"Development of best reference resource mining algorithm","url":"https://www.gyunam.com/funding/samsung-1st/","url_project":""}],"kind":"grants","source":"https://www.gyunam.com/"}