Scholar
Risi Kondor
Google Scholar ID: v12-jLUAAAAJ
Associate Professor, The University of Chicago
Citations & Impact
Citations
10,069
H-index
28
i10-index
45
Publications
20
Co-authors
27
list available
Contact
Publications
Resume (English only)
Academic Achievements
- Published multiple papers on equivariant neural networks in journals and conferences such as PNAS, NeurIPS, and AISTATS. Developed several open-source software libraries including cnine, GElib, ptens, and more.
Research Experience
- Currently an Associate Professor in the Department of Computer Science at the University of Chicago, also affiliated with the Department of Statistics and the Computational and Applied Mathematics Initiative (CAMI). Leads a research group focused on fundamental methodological developments in machine learning.
Education
- Information not provided
Background
- Research interests include machine learning, machine learning for physics and chemistry, computational harmonic analysis, and group representation theory. Responsible for foundational work on equivariant neural networks. Developing high-performance, open-source AI software in Python and C++. Also engaged in work related to AI safety.
Miscellany
- Personal interests and other information not provided
