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Philip König

Philip König

is researcher at SBA Research.

Research Interests

Philip’s research focuses on applying machine learning to software development, particularly in predicting software faults. By analyzing a holistic metric suite—such as social, process, entropy, size, and complexity metrics—drawn from software repositories over a project’s lifetime, these metrics are used to identify where bugs are likely to emerge. He is also interested in exploring how similar approaches could be applied to biological data to better understand their underlying complexity.


Bio

Philip holds a Master’s degree in Molecular Medicine, where he conducted research on cancer, and a Bachelor’s degree in Philosophy, with a focus on ethics and the philosophy of science and technology, both from the University of Vienna. After his work in molecular biology, he transitioned into data science, with an emphasis on predictive analytics. His current focus is on software reliability, where he applies data-driven approaches, informed by his experience in analyzing complex biological systems.