<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Funded research/industry projects | GYUNAM PARK</title><link>https://www.gyunam.com/funding/</link><atom:link href="https://www.gyunam.com/funding/index.xml" rel="self" type="application/rss+xml"/><description>Funded research/industry projects</description><generator>Wowchemy (https://wowchemy.com)</generator><language>en-us</language><image><url>https://www.gyunam.com/media/icon_hu_ce903e1fcc9df493.png</url><title>Funded research/industry projects</title><link>https://www.gyunam.com/funding/</link></image><item><title>Auditing Process Improvement</title><link>https://www.gyunam.com/funding/ey-auditing/</link><pubDate>Thu, 01 Jan 2026 00:00:00 +0000</pubDate><guid>https://www.gyunam.com/funding/ey-auditing/</guid><description>&lt;h2 id="abstract">Abstract&lt;/h2>
&lt;p>Industry collaboration with EY at Eindhoven University of Technology: development of a tool for EY&amp;rsquo;s auditing processes.&lt;/p>
&lt;h2 id="outputs">Outputs&lt;/h2>
&lt;ul>
&lt;li>One conference paper submitted.&lt;/li>
&lt;/ul></description></item><item><title>euroFMX: Foundational Models for Trustworthy Industrial Generative AI in Europe</title><link>https://www.gyunam.com/funding/eurofmx/</link><pubDate>Thu, 01 Jan 2026 00:00:00 +0000</pubDate><guid>https://www.gyunam.com/funding/eurofmx/</guid><description>&lt;h2 id="abstract">Abstract&lt;/h2>
&lt;p>euroFMX 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.&lt;/p>
&lt;h2 id="objectives">Objectives&lt;/h2>
&lt;ul>
&lt;li>Graph-based data modelling of manufacturing processes, building on object-centric event data.&lt;/li>
&lt;li>Neuro-symbolic AI that combines foundation models with symbolic process models.&lt;/li>
&lt;li>Active inference for AI agents that act in manufacturing processes.&lt;/li>
&lt;/ul></description></item><item><title>AI-BioDynamics: AI for Scalable Biodiversity Monitoring</title><link>https://www.gyunam.com/funding/ai-biodynamics/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0000</pubDate><guid>https://www.gyunam.com/funding/ai-biodynamics/</guid><description>&lt;h2 id="abstract">Abstract&lt;/h2>
&lt;p>AI-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.&lt;/p></description></item><item><title>JAIF: JUPITER AI Factory</title><link>https://www.gyunam.com/funding/jaif/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0000</pubDate><guid>https://www.gyunam.com/funding/jaif/</guid><description>&lt;h2 id="abstract">Abstract&lt;/h2>
&lt;p>The JUPITER AI Factory makes JUPITER, Europe&amp;rsquo;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.&lt;/p></description></item><item><title>PMTk: Process Mining Toolkit</title><link>https://www.gyunam.com/funding/pmtk/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0000</pubDate><guid>https://www.gyunam.com/funding/pmtk/</guid><description>&lt;h2 id="abstract">Abstract&lt;/h2>
&lt;p>Industry contract with Process Intelligence Solutions GmbH for the development of a process-mining software toolkit, carried out at Fraunhofer FIT.&lt;/p></description></item><item><title>PM4KNIME: Process Mining Extension for KNIME</title><link>https://www.gyunam.com/funding/pm4knime/</link><pubDate>Mon, 01 Jan 2024 00:00:00 +0000</pubDate><guid>https://www.gyunam.com/funding/pm4knime/</guid><description>&lt;h2 id="abstract">Abstract&lt;/h2>
&lt;p>Industry 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.&lt;/p></description></item><item><title>Process Modeling Using LLMs</title><link>https://www.gyunam.com/funding/process-modeling-llms/</link><pubDate>Mon, 01 Jan 2024 00:00:00 +0000</pubDate><guid>https://www.gyunam.com/funding/process-modeling-llms/</guid><description>&lt;h2 id="abstract">Abstract&lt;/h2>
&lt;p>Internal Fraunhofer project on process modeling with large language models, carried out at Fraunhofer FIT.&lt;/p></description></item><item><title>AIStudyBuddy</title><link>https://www.gyunam.com/funding/aistudybuddy/</link><pubDate>Sun, 01 Jan 2023 00:00:00 +0000</pubDate><guid>https://www.gyunam.com/funding/aistudybuddy/</guid><description>&lt;h2 id="abstract">Abstract&lt;/h2>
&lt;p>AIStudyBuddy 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.&lt;/p>
&lt;h2 id="outputs">Outputs&lt;/h2>
&lt;ul>
&lt;li>&lt;a href="https://www.gyunam.com/publication/2024-jiis-learningrecommendation/">Learning recommendations from educational event data in higher education&lt;/a>&lt;/li>
&lt;li>&lt;a href="https://www.gyunam.com/publication/2023-icpm-edupm/">Extracting rules from event data for study planning&lt;/a>&lt;/li>
&lt;li>&lt;a href="https://www.gyunam.com/publication/2024-kim-unlocking/">Unlocking learner engagement and performance&lt;/a>&lt;/li>
&lt;/ul></description></item><item><title>Root cause analysis of bottlenecks in FAB</title><link>https://www.gyunam.com/funding/samsung-3rd/</link><pubDate>Tue, 01 Jan 2019 00:00:00 +0000</pubDate><guid>https://www.gyunam.com/funding/samsung-3rd/</guid><description/></item><item><title>Development of algorithm for recommending best resource path using AI</title><link>https://www.gyunam.com/funding/samsung-2nd/</link><pubDate>Mon, 01 Jan 2018 00:00:00 +0000</pubDate><guid>https://www.gyunam.com/funding/samsung-2nd/</guid><description/></item><item><title>Development of best reference resource mining algorithm</title><link>https://www.gyunam.com/funding/samsung-1st/</link><pubDate>Sun, 01 Jan 2017 00:00:00 +0000</pubDate><guid>https://www.gyunam.com/funding/samsung-1st/</guid><description/></item></channel></rss>