Andrea J. Liu

18.8k total citations · 4 hit papers
193 papers, 13.7k citations indexed

About

Andrea J. Liu is a scholar working on Materials Chemistry, Condensed Matter Physics and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Andrea J. Liu has authored 193 papers receiving a total of 13.7k indexed citations (citations by other indexed papers that have themselves been cited), including 110 papers in Materials Chemistry, 47 papers in Condensed Matter Physics and 37 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Andrea J. Liu's work include Material Dynamics and Properties (99 papers), Theoretical and Computational Physics (41 papers) and Electrostatics and Colloid Interactions (17 papers). Andrea J. Liu is often cited by papers focused on Material Dynamics and Properties (99 papers), Theoretical and Computational Physics (41 papers) and Electrostatics and Colloid Interactions (17 papers). Andrea J. Liu collaborates with scholars based in United States, Netherlands and China. Andrea J. Liu's co-authors include Sidney R. Nagel, Corey S. O’Hern, Leonardo E. Silbert, Bae‐Yeun Ha, Stephen A. Langer, Michael E. Fisher, Samuel S. Schoenholz, D. J. Durian, Glenn H. Fredrickson and Carl P. Goodrich and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Physical Review Letters.

In The Last Decade

Andrea J. Liu

190 papers receiving 13.4k citations

Hit Papers

Jamming is not just cool ... 1998 2026 2007 2016 1998 2003 2010 2002 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Andrea J. Liu United States 60 8.0k 3.2k 2.8k 2.3k 1.7k 193 13.7k
Masao Doi Japan 64 7.9k 1.0× 1.9k 0.6× 5.4k 1.9× 2.1k 0.9× 2.8k 1.6× 320 22.6k
Gerhard Gompper Germany 71 4.4k 0.5× 5.0k 1.6× 5.4k 1.9× 2.2k 1.0× 2.2k 1.2× 358 16.4k
Wilson C. K. Poon United Kingdom 66 9.6k 1.2× 3.0k 0.9× 4.6k 1.6× 1.1k 0.5× 1.9k 1.1× 232 15.7k
Michael E. Cates United Kingdom 75 9.8k 1.2× 7.6k 2.4× 4.1k 1.4× 2.5k 1.1× 2.1k 1.2× 287 21.7k
Igor S. Aranson United States 55 2.2k 0.3× 5.8k 1.8× 3.2k 1.2× 2.1k 0.9× 1.6k 0.9× 243 11.7k
Steve Granick United States 82 10.2k 1.3× 3.3k 1.0× 6.1k 2.2× 1.4k 0.6× 5.1k 2.9× 340 23.2k
Eric R. Weeks United States 46 5.5k 0.7× 1.6k 0.5× 2.3k 0.8× 966 0.4× 1.2k 0.7× 107 9.5k
Jack F. Douglas United States 81 16.2k 2.0× 3.2k 1.0× 7.1k 2.5× 2.2k 1.0× 2.4k 1.4× 548 28.7k
Giancarlo Ruocco Italy 60 7.2k 0.9× 2.8k 0.9× 3.3k 1.2× 558 0.2× 4.5k 2.6× 474 14.6k
David J. Pine United States 78 13.1k 1.6× 3.6k 1.1× 5.4k 1.9× 932 0.4× 3.0k 1.7× 186 22.0k

Countries citing papers authored by Andrea J. Liu

Since Specialization
Citations

This map shows the geographic impact of Andrea J. Liu'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 Andrea J. Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrea J. Liu more than expected).

Fields of papers citing papers by Andrea J. Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrea J. Liu. 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 Andrea J. Liu. The network helps show where Andrea J. Liu may publish in the future.

Co-authorship network of co-authors of Andrea J. Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Andrea J. Liu. A scholar is included among the top collaborators of Andrea J. Liu 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 Andrea J. Liu. Andrea J. Liu 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.
Jung, Gerhard, Victor Bapst, Daniele Coslovich, et al.. (2025). Roadmap on machine learning glassy dynamics. Nature Reviews Physics. 7(2). 91–104. 10 indexed citations
2.
Stern, Menachem, Sam Dillavou, Dinesh Jayaraman, D. J. Durian, & Andrea J. Liu. (2024). Training self-learning circuits for power-efficient solutions. SHILAP Revista de lepidopterología. 2(1). 5 indexed citations
3.
Biroli, Giulio, et al.. (2024). Dynamical Facilitation Governs the Equilibration Dynamics of Glasses. Physical Review X. 14(3). 3 indexed citations
4.
Gado, Emanuela Del, Andrea J. Liu, & C. Patrick Royall. (2023). Slow dynamics in disordered materials across theory, experiments, and simulations. The Journal of Chemical Physics. 159(4). 1 indexed citations
5.
Ridout, Sean A., et al.. (2023). Building a “trap model” of glassy dynamics from a local structural predictor of rearrangements. Europhysics Letters (EPL). 144(4). 47001–47001. 5 indexed citations
6.
Dillavou, Sam, Menachem Stern, Andrea J. Liu, & D. J. Durian. (2022). Demonstration of Decentralized Physics-Driven Learning. Physical Review Applied. 18(1). 50 indexed citations
7.
Vashisth, Manasvita, Sang-Kyun Cho, Jerome Irianto, et al.. (2021). Scaling concepts in ‘omics: Nuclear lamin-B scales with tumor growth and often predicts poor prognosis, unlike fibrosis. Proceedings of the National Academy of Sciences. 118(48). 16 indexed citations
8.
Biroli, Giulio, et al.. (2021). Elastoplasticity Mediates Dynamical Heterogeneity Below the Mode Coupling Temperature. Physical Review Letters. 127(4). 48002–48002. 33 indexed citations
9.
Richard, David, Misaki Ozawa, Sylvain Patinet, et al.. (2020). Predicting plasticity in disordered solids from structural indicators. Physical Review Materials. 4(11). 147 indexed citations
10.
Ma, Xiaoguang, Zoey S. Davidson, Tim Still, et al.. (2019). Heterogeneous Activation, Local Structure, and Softness in Supercooled Colloidal Liquids. Physical Review Letters. 122(2). 28001–28001. 44 indexed citations
11.
Sharp, Tristan A., Matthias Merkel, M. Lisa Manning, & Andrea J. Liu. (2019). Inferring statistical properties of 3D cell geometry from 2D slices. PLoS ONE. 14(2). e0209892–e0209892. 8 indexed citations
12.
Sharp, Tristan A., Spencer L. Thomas, Ekin D. Cubuk, et al.. (2018). Machine learning determination of atomic dynamics at grain boundaries. Proceedings of the National Academy of Sciences. 115(43). 10943–10947. 70 indexed citations
13.
Pfeifer, Charlotte R., Jerome Irianto, Rachel R. Bennett, et al.. (2017). Nuclear Constriction Segregates Mobile Nuclear Proteins Away from Chromatin. Biophysical Journal. 112(3). 337a–337a. 3 indexed citations
14.
Cubuk, Ekin D., Samuel S. Schoenholz, Jennifer M. Rieser, et al.. (2015). Identifying Structural Flow Defects in Disordered Solids Using Machine-Learning Methods. Physical Review Letters. 114(10). 108001–108001. 337 indexed citations
15.
Chen, Ke, Tim Still, Kevin B. Aptowicz, et al.. (2012). Phonons in pristine and imperfect two-dimensional soft colloidal crystals. arXiv (Cornell University). 1 indexed citations
16.
Manning, M. Lisa & Andrea J. Liu. (2011). Vibrational Modes Identify Soft Spots in a Sheared Disordered Packing. Physical Review Letters. 107(10). 108302–108302. 301 indexed citations
17.
Xu, Ning, et al.. (2007). Excess Vibrational Modes in Model Glasses. Bulletin of the American Physical Society.
18.
Silbert, Leonardo E., Andrea J. Liu, & Sidney R. Nagel. (2006). Structural signatures of the unjamming transition at zero temperature. Physical Review E. 73(4). 41304–41304. 81 indexed citations
19.
Liu, Andrea J.. (2004). Jamming and the Glass Transition. APS March Meeting Abstracts. 2004. 2 indexed citations
20.
Liu, Andrea J.. (1997). Morphology Development in Liquid-Crystal/Polymer Mixtures. Liquid Crystals Today. 7(4). 1–7. 1 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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