Scholar
Christian Borgs
Google Scholar ID: B847xq8AAAAJ
Professor, UC Berkeley
Citations & Impact
Citations
7,414
H-index
41
i10-index
107
Publications
20
Co-authors
50
list available
Contact
Publications
Resume (English only)
Academic Achievements
- Authored nearly 150 research papers
- Named co-inventor on over 30 patents
- Recipient of the Karl-Scheel Prize from the German Physical Society
- Awarded the Heisenberg Fellowship by the German Research Council
- Twice a member of the Institute for Advanced Study in Princeton
- Fellow of the American Mathematical Society
- Fellow of the American Association for the Advancement of Science
- Served on multiple editorial and governing boards, including:
- - Board of Trustees of the Institute for Pure and Applied Mathematics (IPAM)
- - Governing Board of the Institute for Mathematics and its Applications (IMA), Chair (2017–2019)
- - Advisory Board of the Harvard Institute for Applied Computational Science (IACS)
- - External Advisory Board for Computing at NYU
- Key publications include 'Graph Limits, Graphons and Nonparametric Network Models' and 'Convergent Sequences of Dense Graphs I/II', co-authored with J. T. Chayes, L. Lovász, et al.
Background
- Professor of Computer Science in the EECS Department at the University of California, Berkeley
- Member of the Berkeley Artificial Intelligence Research (BAIR) Lab
- Director of the Bakar Institute of Digital Materials for the Planet (BIDMaP)
- Current research focuses on the science of networks, including the theory of graph limits (co-invented ~15 years ago), graph processes, graph algorithms, and applications in economics, systems biology, and epidemiology
- Earlier work centered on mathematical statistical physics, especially first-order phase transitions and finite-size effects
- Pioneered the application of mathematical statistical physics methods to theoretical computer science, including phase transitions in combinatorial optimization and Markov chain analysis
- Recently working on responsible AI, including differential privacy and bias in automated decision-making
- Recently interested in AI for Science, particularly AI for materials science with applications to climate change mitigation
