Ziheng Chen is an ELLIS PhD student in Information Engineering and Computer Science at the University of Trento, supervised by Prof. Nicu Sebe, and a visiting PhD student at the Max Planck Institute for Intelligent Systems, working with Prof. Bernhard Schölkopf. His research lies at the intersection of machine learning and differential geometry, with a focus on deep learning over non-Euclidean spaces such as Riemannian manifolds, hyperbolic spaces, matrix manifolds, and Lie groups. His work develops geometric counterparts of core neural-network components, including normalization, classification, attention, and hyperbolic layers. His research has appeared at ICLR, NeurIPS, CVPR, ICML, AAAI, and IEEE journals. He has received a DAAD Research Grant, ELSA and ELIAS Mobility Grants.
© Ziheng Chen