2026 Christian Borgs: Mathematics Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	62	2938	2853	1444	1391	192	13713
Mathematics	59	593	499	302	236	184	12852

Research.com Recognitions

2014 - Fellow of the American Mathematical Society For contributions bringing together analysis, probability theory, graph theory and combinatorics with mathematical statistical physics and rigorous computer science.
2013 - Fellow of the American Association for the Advancement of Science (AAAS)

Overview

Christian Borgs is a researcher affiliated with the University of California, Berkeley in the United States. Their research spans several interdisciplinary fields, with a strong focus on mathematics and computer science. Specifically, their work often intersects materials chemistry, statistics and probability, computational theory and mathematics, inorganic chemistry, and artificial intelligence.

The scientist's research portfolio prominently features topics such as machine learning in materials science, computational drug discovery methods, and metal-organic frameworks (MOFs) synthesis and applications. Other areas of interest include limits and structures in graph theory, advanced causal inference techniques, topic modeling, and complex network analysis techniques.

Christian Borgs has published extensively in various academic venues. Some frequent publication venues include:

arXiv (Cornell University)
Digital Discovery
Journal of the American Chemical Society
ACS Central Science
Proceedings of the National Academy of Sciences

Their recent papers from 2023 and 2025 reflect a focus on applications of advanced language models and computational methods in reticular chemistry and materials synthesis. Notable recent works include:

"ChatGPT Chemistry Assistant for Text Mining and the Prediction of MOF Synthesis" (2023, Journal of the American Chemical Society)
"A GPT-4 Reticular Chemist for Guiding MOF Discovery" (2023, Angewandte Chemie International Edition)
"ChatGPT Research Group for Optimizing the Crystallinity of MOFs and COFs" (2023, ACS Central Science)
"Shaping the Water-Harvesting Behavior of Metal-Organic Frameworks Aided by Fine-Tuned GPT Models" (2023, Journal of the American Chemical Society)
"Large language models for reticular chemistry" (2025, Nature Reviews Materials)

Christian Borgs has collaborated frequently with several researchers, with notable coauthors including Jennifer Chayes, Omar M. Yaghi, Nakul Rampal, Zhiling Zheng, and Zichao Rong. The collaboration network reflects an interdisciplinary approach involving both chemical synthesis and computational techniques.

Throughout their career, Borgs has received recognition from scientific societies. They were named a Fellow of the American Mathematical Society in 2014 for contributions bridging analysis, probability theory, graph theory, combinatorics, mathematical statistical physics, and rigorous computer science. They were also honored as a Fellow of the American Association for the Advancement of Science (AAAS) in 2013.

Best Publications

Maximizing social influence in nearly optimal time

Christian Borgs;Michael Brautbar;Jennifer Chayes;Brendan Lucier

965
Citations
Convergent sequences of dense graphs I: Subgraph frequencies, metric properties and testing

C. Borgs;Jennifer T. Chayes;László Lovász;Vera T. Sós

718
Citations
Entropy-SGD: biasing gradient descent into wide valleys*

Pratik Chaudhari;Pratik Chaudhari;Anna Choromanska;Stefano Soatto;Yann LeCun;Yann LeCun

583
Citations
Directed scale-free graphs

Béla Bollobás;Christian Borgs;Jennifer Chayes;Oliver Riordan

473
Citations
Convergent Sequences of Dense Graphs II. Multiway Cuts and Statistical Physics

Christian Borgs;Jennifer T. Chayes;László Lovász;Vera T. Sós

363
Citations
A Rigorous Theory of Finite-Size Scaling at First-Order Phase Transitions

Christian Borgs;Roman Kotecký

356
Citations
Trust-based recommendation systems: an axiomatic approach

Reid Andersen;Christian Borgs;Jennifer Chayes;Uriel Feige

291
Citations
Dynamics of bid optimization in online advertisement auctions

Christian Borgs;Jennifer Chayes;Nicole Immorlica;Kamal Jain

289
Citations
Multi-unit auctions with budget-constrained bidders

Christian Borgs;Jennifer Chayes;Nicole Immorlica;Mohammad Mahdian

264
Citations
On the spread of viruses on the internet

Noam Berger;Christian Borgs;Jennifer T. Chayes;Amin Saberi

262
Citations
The scaling window of the 2-SAT transition

Béla Bollobás;Béla Bollobás;Christian Borgs;Jennifer T. Chayes;Jeong Han Kim

255
Citations
Counting Graph Homomorphisms

Christian Borgs;Jennifer Chayes;László Lovász;Vera T. Sós

235
Citations
Graph limits and parameter testing

Christian Borgs;Jennifer Chayes;László Lovász;Vera T. Sós

231
Citations
Finite-size effects at asymmetric first-order phase transitions.

Christian Borgs;Roman Kotecký;Roman Kotecký

208
Citations
An $L^p$ theory of sparse graph convergence I: limits, sparse random graph models, and power law distributions

Christian Borgs;Jennifer T. Chayes;Henry Cohn;Yufei Zhao

200
Citations
Unreasonable Effectiveness of Learning Neural Networks: From Accessible States and Robust Ensembles to Basic Algorithmic Schemes

Carlo Baldassi;Christian Borgs;Jennifer T. Chayes;Alessandro Ingrosso

180
Citations
Finite-size scaling for Potts models

Christian Borgs;Roman Kotecký;Salvador Miracle-Solé

175
Citations
Local Computation of PageRank Contributions

Reid Andersen;Christian Borgs;Jennifer T. Chayes;John E. Hopcroft

168
Citations
Simultaneous Reconstruction of Multiple Signaling Pathways via the Prize-Collecting Steiner Forest Problem

Nurcan Tuncbag;Alfredo Braunstein;Andrea Pagnani;Shao-Shan Carol Huang

155
Citations
Finding undetected protein associations in cell signaling by belief propagation.

Marc Bailly-Bechet;Christian Borgs;Alfredo Braunstein;Jennifer T. Chayes

153
Citations
Local computation of PageRank contributions

Reid Andersen;Christian Borgs;Jennifer Chayes;John Hopcraft

124
Citations
Unreasonable Effectiveness of Learning Neural Nets: Accessible States and Robust Ensembles.

Carlo Baldassi;Christian Borgs;Jennifer T. Chayes;Alessandro Ingrosso

3
Citations

Frequent Co-Authors

Jennifer Chayes University of California, Berkeley

Shang-Hua Teng University of Southern California

Kamal Jain Microsoft (United States)

Adam Tauman Kalai Microsoft (United States)

Mohammad Mahdian Google (United States)

Nicole Immorlica Microsoft (United States)

Joel Spencer Courant Institute of Mathematical Sciences

László Lovász Eötvös Loránd University

Gordon Slade University of British Columbia

Vahab Mirrokni Google (United States)

External Links

Wikipedia of Christian Borgs Personal website of Christian Borgs Google Scholar page

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