Machine Learning Engineer at RWTH Aachen University
Aachen, North Rhine-Westphalia, Germany
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Summary
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Senior
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Daniel Swoboda is a machine learning engineer and PhD student at RWTH Aachen with 11 years of software and research experience spanning cognitive robotics, multi-agent coordination, and formal controller synthesis. He has driven research-grade tooling such as TACoS for timed automata and contributed a promise-based multi-agent coordination approach published at ICAPS' PlanRob workshop. Equally at home in distributed systems and drone/robotics applications, he combines theoretical rigor from his exchange at KAIST's graduate AI school with practical implementation as a long-term student research assistant. An Austrian living in Germany, he brings a global perspective and a keen interest in technology ethics, making him attentive to responsible ML and robotics deployment.
11 years of coding experience
4 years of employment as a software developer
Doctor of Science Computer Science, Doctor of Science Computer Science at RWTH Aachen University
Matura mit Auszeichnung Informatik, Matura mit Auszeichnung Informatik at HTBLuVA Wiener Neustadt, Abteilung Informatik
Exchange Semester at the Kim Jaechul Graduate School of AI, Exchange Semester at the Kim Jaechul Graduate School of AI at Korea Advanced Institute of Science and Technology
Contributions:1 release, 47 commits, 28 pushes in 4 days
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Daniel Swoboda - Machine Learning Engineer at RWTH Aachen University