Grant M. Rotskoff

1.8k total citations
39 papers, 1.0k citations indexed

About

Grant M. Rotskoff is a scholar working on Statistical and Nonlinear Physics, Atomic and Molecular Physics, and Optics and Materials Chemistry. According to data from OpenAlex, Grant M. Rotskoff has authored 39 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Statistical and Nonlinear Physics, 11 papers in Atomic and Molecular Physics, and Optics and 11 papers in Materials Chemistry. Recurrent topics in Grant M. Rotskoff's work include Advanced Thermodynamics and Statistical Mechanics (15 papers), Protein Structure and Dynamics (6 papers) and stochastic dynamics and bifurcation (6 papers). Grant M. Rotskoff is often cited by papers focused on Advanced Thermodynamics and Statistical Mechanics (15 papers), Protein Structure and Dynamics (6 papers) and stochastic dynamics and bifurcation (6 papers). Grant M. Rotskoff collaborates with scholars based in United States, Switzerland and France. Grant M. Rotskoff's co-authors include Phillip L. Geissler, Gavin E. Crooks, Todd R. Gingrich, Eric Vanden‐Eijnden, Jordan M. Horowitz, A. Paul Alivisatos, Layne B. Frechette, Matthew R. Jones, Julien Herrou and Sean Crosson and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Physical Review Letters.

In The Last Decade

Grant M. Rotskoff

34 papers receiving 1.0k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Grant M. Rotskoff United States 18 327 324 257 222 110 39 1.0k
Harm Hinrich Rotermund Germany 16 363 1.1× 278 0.9× 66 0.3× 369 1.7× 169 1.5× 31 1.1k
S. Jakubith Germany 10 337 1.0× 241 0.7× 67 0.3× 470 2.1× 147 1.3× 11 1.2k
Sanghyun Park South Korea 7 217 0.7× 383 1.2× 741 2.9× 477 2.1× 228 2.1× 13 1.5k
Kranthi K. Mandadapu United States 17 158 0.5× 213 0.7× 233 0.9× 197 0.9× 209 1.9× 47 859
Daniel S. Banks Canada 5 102 0.3× 239 0.7× 380 1.5× 123 0.6× 170 1.5× 8 883
Daniel Kandel Israel 26 197 0.6× 451 1.4× 227 0.9× 780 3.5× 175 1.6× 53 1.8k
E. Abad Spain 23 278 0.9× 512 1.6× 417 1.6× 400 1.8× 186 1.7× 83 1.6k
Hiroyuki Matsuda Japan 16 40 0.1× 167 0.5× 207 0.8× 147 0.7× 62 0.6× 60 900
Anatoly B. Kolomeisky United States 27 312 1.0× 507 1.6× 913 3.6× 334 1.5× 589 5.4× 70 2.6k
F. Falo Spain 21 570 1.7× 145 0.4× 347 1.4× 538 2.4× 132 1.2× 61 1.3k

Countries citing papers authored by Grant M. Rotskoff

Since Specialization
Citations

This map shows the geographic impact of Grant M. Rotskoff's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Grant M. Rotskoff with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Grant M. Rotskoff more than expected).

Fields of papers citing papers by Grant M. Rotskoff

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Grant M. Rotskoff. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Grant M. Rotskoff. The network helps show where Grant M. Rotskoff may publish in the future.

Co-authorship network of co-authors of Grant M. Rotskoff

This figure shows the co-authorship network connecting the top 25 collaborators of Grant M. Rotskoff. A scholar is included among the top collaborators of Grant M. Rotskoff based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Grant M. Rotskoff. Grant M. Rotskoff is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Rotskoff, Grant M., et al.. (2025). Computing Nonequilibrium Responses with Score-Shifted Stochastic Differential Equations. Physical Review Letters. 134(9). 97101–97101.
3.
Hurst, Paul J., et al.. (2025). Coacervation drives morphological diversity of mRNA encapsulating nanoparticles. The Journal of Chemical Physics. 162(7). 2 indexed citations
4.
Mitchell, Andrew & Grant M. Rotskoff. (2024). Committor Guided Estimates of Molecular Transition Rates. Journal of Chemical Theory and Computation. 20(21). 9378–9393. 2 indexed citations
5.
Lu, Yiping, et al.. (2024). Statistical Spatially Inhomogeneous Diffusion Inference. Proceedings of the AAAI Conference on Artificial Intelligence. 38(13). 14820–14828.
6.
7.
Rotskoff, Grant M., et al.. (2023). Unified, Geometric Framework for Nonequilibrium Protocol Optimization. Physical Review Letters. 130(10). 107101–107101. 22 indexed citations
8.
Rotskoff, Grant M., et al.. (2023). Ensuring thermodynamic consistency with invertible coarse-graining. The Journal of Chemical Physics. 158(12). 124126–124126. 22 indexed citations
9.
Yan, Jiawei & Grant M. Rotskoff. (2022). Physics-informed graph neural networks enhance scalability of variational nonequilibrium optimal control. The Journal of Chemical Physics. 157(7). 74101–74101. 4 indexed citations
10.
Mensch, Arthur, et al.. (2020). A mean-field analysis of two-player zero-sum games. Neural Information Processing Systems. 33. 20215–20226. 1 indexed citations
11.
Rotskoff, Grant M., et al.. (2019). Neuron birth-death dynamics accelerates gradient descent and converges asymptotically. International Conference on Machine Learning. 5508–5517. 2 indexed citations
12.
Rotskoff, Grant M. & Eric Vanden‐Eijnden. (2019). Dynamical Computation of the Density of States and Bayes Factors Using Nonequilibrium Importance Sampling. Physical Review Letters. 122(15). 150602–150602. 7 indexed citations
13.
Rotskoff, Grant M. & Eric Vanden‐Eijnden. (2018). Parameters as interacting particles: long time convergence and asymptotic error scaling of neural networks. Neural Information Processing Systems. 31. 7146–7155. 17 indexed citations
14.
Hauwiller, Matthew R., Layne B. Frechette, Matthew R. Jones, et al.. (2018). Unraveling Kinetically-Driven Mechanisms of Gold Nanocrystal Shape Transformations Using Graphene Liquid Cell Electron Microscopy. Nano Letters. 18(9). 5731–5737. 68 indexed citations
15.
Rotskoff, Grant M., Gavin E. Crooks, & Eric Vanden‐Eijnden. (2017). Geometric approach to optimal nonequilibrium control: Minimizing dissipation in nanomagnetic spin systems. Physical review. E. 95(1). 12148–12148. 49 indexed citations
16.
Rotskoff, Grant M.. (2017). Mapping current fluctuations of stochastic pumps to nonequilibrium steady states. Physical review. E. 95(3). 30101–30101. 18 indexed citations
17.
Gingrich, Todd R., Grant M. Rotskoff, & Jordan M. Horowitz. (2017). Inferring dissipation from current fluctuations. Journal of Physics A Mathematical and Theoretical. 50(18). 184004–184004. 111 indexed citations
18.
Ye, Xingchen, Matthew R. Jones, Layne B. Frechette, et al.. (2016). Single-particle mapping of nonequilibrium nanocrystal transformations. Science. 354(6314). 874–877. 217 indexed citations
19.
Willett, Jonathan W., Julien Herrou, Ariane Briegel, Grant M. Rotskoff, & Sean Crosson. (2015). Structural asymmetry in a conserved signaling system that regulates division, replication, and virulence of an intracellular pathogen. Proceedings of the National Academy of Sciences. 112(28). E3709–18. 43 indexed citations
20.
Pronk, Sander, et al.. (2015). Molecular Simulation Workflows as Parallel Algorithms: The Execution Engine of Copernicus, a Distributed High-Performance Computing Platform. Journal of Chemical Theory and Computation. 11(6). 2600–2608. 35 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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