Summary
Michael Faerber is a professor and AI researcher leading the "Scalable Software Architectures for Data Analytics" group at TU Dresden, appointed at age 36 after serving as deputy full professor for Web Science at KIT. Over nine years he has built a research portfolio centered on LLMs, graph neural networks, and knowledge graphs, with a strong interest in neurosymbolic and explainable AI, and more than 100 peer-reviewed publications in top venues. As principal investigator he has secured multi-million euro funding for major projects and routinely teaches large undergraduate and graduate cohorts of up to 600 students. His background in philosophy gives his technical work an uncommon interdisciplinary perspective on meaning, explanation, and ethics in AI. Practically minded, he focuses on scalable architectures for data analytics that bridge research and deployable systems. Based in Dresden, he combines academic leadership with hands-on research that aims to make complex AI models more interpretable and useful in real-world data workflows.
9 years of coding experience