معرفی
Christopher Künneth is an Assistant Professor at the University of Bayreuth (UBT) since March 2023. He holds a PhD from the Technical University of Munich (2018, summa cum laude), where his research focused on pyroelectricity and ferroelectricity in HfO₂/ZrO₂ using density functional theory and molecular dynamics. He completed a postdoctoral fellowship (Feodor Lynen, Humboldt Foundation) in the Ramprasad Group at Georgia Tech (2019–2023), specializing in machine learning for polymer informatics, including predictive models deployed via the Polymers Genome project.
Education:
- PhD (summa cum laude), Technical University of Munich, 2018
- Postdoctoral Research, Georgia Tech, 2019–2023
Research Focus: The Kuenneth Group advances materials informatics through cutting-edge machine learning techniques, with applications in sustainable and polymeric materials. Key areas include accelerating materials discovery/design, polymer property prediction, and AI-driven material systems. The group emphasizes democratizing ML tools for broader materials science adoption.
Awards:
- Feodor Lynen Fellowship (Humboldt Foundation, 2019)
Advising & Labs: Leads the Kuenneth Group at UBT, fostering interdisciplinary research. Open positions in computational materials science and ML are available via the lab's portal. Active in teaching and mentoring early-career researchers.
