AL

Andrea J. Liu

0000-0002-2295-2729

cond-mat.softcond-mat.stat-mechcond-mat.dis-nncond-mat.mtrl-sciphysics.bio-phModels, Biologicalmachine learningcs.LGphysics.chem-phbiophysics

On Valency

published · living versions

Identifying structural flow defects in disordered solids using machine learning methods

with Ekin D. Cubuk, Samuel S. Schoenholz, Jennifer M. Rieser, Brad D. Malone +3

1 version

W_y25n99c2v1 · current

Preprints & journals

175 papers in the corpus · 1985–2026

Double descent without digital computation.

Dillavou, Sam, Rocks, Jason W, Wycoff, Jacob F et al.

1 citation

427845142026Proceedings of the National Academy of Sciences of the United States of America. 2026;123(39):e2604421123

Epithelial convergent extension as a tuning process.

Arzash, Sadjad, Liu, Andrea J, Manning, M Lisa

1 citation

426734652026Proceedings of the National Academy of Sciences of the United States of America. 2026;123(36):e2532099123

Unsupervised and probabilistic learning with Contrastive Local Learning Networks: The Restricted Kirchhoff Machine.

Guzman, Marcelo, Ciarella, Simone, Liu, Andrea J

0 citations

421662382026Proceedings of the National Academy of Sciences of the United States of America. 2026;123(21):e2525792123

Contrastive learning in tunable dynamical systems

Menachem Stern, Adam G. Frim, Ra'ul Cand'as et al.

0 citations

2603.26969v12026arXiv

Remembrance of Tasks Past in Tunable Physical Networks

Purba Chatterjee, Marcelo Guzman, Andrea J. Liu

0 citations

2512.03799v12025arXiv

Mechanosensitive Remodeling Sustains Rigidity Homeostasis and Elastic Memory in Actin Cortex Models

Wang, H., Galvani Cunha, M. A., Crocker, J. C. et al.

3 citations

10.1101/2025.10.05.680567v22025bioRxiv

Thermally Robust Cooperative Function in Mechanical Networks

Ben Pisanty, Jovana A. Kim, Andrea J. Liu et al.

0 citations

2509.20560v22025arXiv

Training of physical neural networks.

Momeni, Ali, Rahmani, Babak, Scellier, Benjamin et al.

90 citations

409036032025Nature. 2025;645(8079):53-61

Cornerstones are the key stones: using interpretable machine learning to probe the clogging process in 2D granular hoppers.

Hanlan, Jesse M, Dillavou, Sam, Liu, Andrea J et al.

6 citations

406657672025Soft matter. 2025;21(30):6107-6113

Solving the compute crisis with physics-based ASICs

Maxwell Aifer, Zach Belateche, Suraj Bramhavar et al.

2 citations

2507.10463v12025arXiv

Understanding and Embracing Imperfection in Physical Learning Networks

Sam Dillavou, Marcelo Guzman, Andrea J. Liu et al.

0 citations

2505.22887v22025arXiv

US researchers must stand up to protect freedoms, not just funding.

Leifer, Andrew M, Liu, Andrea J, Nagel, Sidney R

3 citations

403608932026Nature. 2025;641(8063):592-593

Physical Networks Become What They Learn.

Stern, Menachem, Guzman, Marcelo, Martins, Felipe et al.

5 citations

402795982025Physical review letters. 2025;134(14):147402

A minimal vertex model explains how the amnioserosa avoids fluidization during Drosophila dorsal closure.

Tah, Indrajit, Haertter, Daniel, Crawford, Janice M et al.

17 citations

397930572025Proceedings of the National Academy of Sciences of the United States of America. 2025;122(1):e2322732121

Microscopic imprints of learned solutions in adaptive resistor networks

Marcel Guzman, Felipe Martins, Menachem Stern et al.

2 citations

2412.19356v12024arXiv

Where physics and biology meet.

Marshall, Wallace, Baum, Buzz, Fairhall, Adrienne et al.

2 citations

394377342024Current biology : CB. 2024;34(20):R950-R960

Minimal vertex model explains how the amnioserosa avoids fluidization during Drosophila dorsal closure.

Tah, Indrajit, Haertter, Daniel, Crawford, Janice M et al.

10 citations

381877302025bioRxiv : the preprint server for biology. 2024

Machine learning without a processor: Emergent learning in a nonlinear analog network.

Dillavou, Sam, Beyer, Benjamin D, Stern, Menachem et al.

39 citations

389545452025Proceedings of the National Academy of Sciences of the United States of America. 2024;121(28):e2319718121

The dynamics of machine-learned "softness" in supercooled liquids describe dynamical heterogeneity

Sean A. Ridout, Andrea J. Liu

1 citation

2406.05868v12024arXiv

Physical effects of learning.

Stern, Menachem, Liu, Andrea J, Balasubramanian, Vijay

24 citations

384916582024Physical review. E. 2024;109(2-1):024311

Topological characterization of the continuum of allosteric response

Jason W. Rocks, Eleni Katifori, Andrea J. Liu

0 citations

2401.13861v12024arXiv

Dynamical Facilitation Governs the Equilibration Dynamics of Glasses

Rahul N. Chacko, Francois P. Landes, Giulio Biroli et al.

11 citations

2312.15069v22023Physical Review X 14.3 (2024): 031012

Rigidity of Epithelial Tissues as a Double Optimization Problem

Sadjad Arzash, Indrajit Tah, Andrea J. Liu et al.

18 citations

2312.11683v52023arXiv

Building rigid networks with prestress and selective pruning

Marco Aurelio Galvani Cunha, John C. Crocker, Andrea J. Liu

7 citations

2312.06119v22023Phys. Rev. Research 6, L042020 (2024)

Roadmap on machine learning glassy dynamics

Gerhard Jung, Rinske M. Alkemade, Victor Bapst et al.

45 citations

2311.14752v22023Nat. Rev. Phys. 7, 91 (2025)

Experimental Demonstration of Coupled Learning in Elastic Networks

Lauren E. Altman, Menachem Stern, Andrea J. Liu et al.

22 citations

2311.00170v22023arXiv

Physical learning of power-efficient solutions

Menachem Stern, Sam Dillavou, Dinesh Jayaraman et al.

1 citation

2310.10437v12023arXiv

Identifying microscopic factors that influence ductility in disordered solids.

Xiao, Hongyi, Zhang, Ge, Yang, Entao et al.

13 citations

378127092024Proceedings of the National Academy of Sciences of the United States of America. 2023;120(42):e2307552120

Discontinuous instabilities in disordered solids.

Xu, Ding, Zhang, Shiyun, Liu, Andrea J et al.

10 citations

375854682024Proceedings of the National Academy of Sciences of the United States of America. 2023;120(34):e2304974120

Building a "trap model" of glassy dynamics from a local structural predictor of rearrangements

Sean A. Ridout, Indrajit Tah, Andrea J. Liu

5 citations

2308.07913v12023Europhysics Letters, 144 (2023) 47001

Slow dynamics in disordered materials across theory, experiments, and simulations.

Del Gado, Emanuela, Liu, Andrea, Royall, C Patrick

2 citations

374940182023The Journal of chemical physics. 2023;159(4)

Universal scaling function ansatz for finite-temperature jamming

Sean A. Ridout, Andrea J. Liu, James P. Sethna

1 citation

2304.11152v22023arXiv

Machine learning-informed structuro-elastoplasticity predicts ductility of disordered solids

Hongyi Xiao, Ge Zhang, Entao Yang et al.

1 citation

2303.12486v12023arXiv

Fragility in glassy liquids: A structural approach based on machine learning.

Tah, Indrajit, Ridout, Sean A, Liu, Andrea J

36 citations

361824092022The Journal of chemical physics. 2022;157(12):124501

Probing Gardner Physics in an Active Quasithermal Pressure-Controlled Granular System of Noncircular Particles.

Xiao, Hongyi, Liu, Andrea J, Durian, Douglas J

13 citations

357764742022Physical review letters. 2022;128(24):248001

Structuro-elasto-plasticity (StEP) model for plasticity in disordered solids

Ge Zhang, Hongyi Xiao, Entao Yang et al.

1 citation

2205.08678v12022arXiv

Transient learning degrees of freedom for introducing function in materials.

Hagh, Varda F, Nagel, Sidney R, Liu, Andrea J et al.

41 citations

355120902022Proceedings of the National Academy of Sciences of the United States of America. 2022;119(19):e2117622119

Desynchronous learning in a physics-driven learning network.

Wycoff, J F, Dillavou, S, Stern, M et al.

26 citations

354283882022The Journal of chemical physics. 2022;156(14):144903

Physical learning beyond the quasistatic limit

Menachem Stern, Sam Dillavou, Marc Z. Miskin et al.

25 citations

2112.11399v12021arXiv

Scaling concepts in 'omics: Nuclear lamin-B scales with tumor growth and often predicts poor prognosis, unlike fibrosis.

Vashisth, Manasvita, Cho, Sangkyun, Irianto, Jerome et al.

23 citations

348102662021Proceedings of the National Academy of Sciences of the United States of America. 2021;118(48)

Probing the Gardner transition in an active quasi-thermal pressure-controlled granular system

Hongyi Xiao, Andrea J. Liu, Douglas J. Durian

0 citations

2111.03921v12021arXiv

Demonstration of Decentralized, Physics-Driven Learning

Sam Dillavou, Menachem Stern, Andrea J. Liu et al.

86 citations

2108.00275v42021arXiv

Elastoplasticity Mediates Dynamical Heterogeneity Below the Mode Coupling Temperature.

Chacko, Rahul N, Landes, François P, Biroli, Giulio et al.

44 citations

343559342021Physical review letters. 2021;127(4):048002

Scaling concepts in 'omics: nuclear lamin-B scales with tumor growth and predicts poor prognosis, whereas fibrosis can be pro-survival

Vashisth, M., Discher, D., Cho, S. et al.

1 citation

10.1101/2021.02.25.432860v12021bioRxiv

Tilting the playing field: Dynamical loss functions for machine learning

Miguel Ruiz-Garcia, Ge Zhang, Samuel S. Schoenholz et al.

7 citations

2102.03793v32021arXiv

Hidden Topological Structure of Flow Network Functionality.

Rocks, Jason W, Liu, Andrea J, Katifori, Eleni

31 citations

335121862021Physical review letters. 2021;126(2):028102

Periodic training of creeping solids.

Hexner, Daniel, Liu, Andrea J, Nagel, Sidney R

42 citations

332575822021Proceedings of the National Academy of Sciences of the United States of America. 2020;117(50):31690-31695

Learning-based approach to plasticity in athermal sheared amorphous packings: Improving softness

Jason W. Rocks, Sean A. Ridout, Andrea J. Liu

10 citations

2010.14637v12020arXiv

Interplay of rearrangements, strain, and local structure during avalanche propagation

Ge Zhang, Sean Ridout, Andrea J. Liu

25 citations

2009.11414v12020arXiv

Unifying framework for strong and fragile liquids via machine learning: a study of liquid silica

Ekin D. Cubuk, Andrea J. Liu, Efthimios Kaxiras et al.

6 citations

2008.09681v12020arXiv

Career total: 398 works. 175 are in this corpus.Showing the 50 most recent.

Profile built from the corpus for this byline.

398

works

19.4K

citations

69

h-index

Corpus papers per year

Corpus papers per year, 1985 to 2026. Busiest year 2023, 15 papers.
Year	Papers
1985	1
1986	1
1987	1
1988	1
1989	1
1990	1
1991	1
1992	1
1993	2
1994	0
1995	0
1996	1
1997	0
1998	1
1999	2
2000	1
2001	4
2002	0
2003	3
2004	2
2005	3
2006	3
2007	3
2008	3
2009	7
2010	8
2011	7
2012	3
2013	9
2014	5
2015	13
2016	13
2017	9
2018	7
2019	8
2020	5
2021	8
2022	4
2023	15
2024	8
2025	8
2026	2

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