Publications

Preprints

Cross-View World Models
Sharma, R., Hogervorst, G., Mackey, W.E., Heeger, D.J., Martiniani, S.
(2026)
arXiv
Open Materials Generation with Inference-Time Reinforcement Learning
Hoellmer, P., Martiniani, S.
(2026)
arXiv
Guided Diffusion for the Discovery of New Superconductors
Prakash, P., Gibson, J.B., Li, Z., Di Gianluca, G., Esquivel, J., Fuemmeler, E., Geisler, B., Kim, J.S., Roitberg, A., Tadmor, E.B., Liu, M., Martiniani, S., Stewart, G.R., Hamlin, J.J., Hirschfeld, P.J., Hennig, R.G.
(2025)
arXiv
All that structure matches does not glitter
Martirossyan, M.M., Egg, T., Hoellmer, P., Karypis, G., Transtrum, M., Roitberg, A., Liu, M., Hennig, R.G., Tadmor, E.B., Martiniani, S.
(2025)
arXiv
Spatial and Temporal Cluster Tomography of Active Matter
Luzzatto, L.V., Casiulis, M., Martiniani, S., Kovacs, I.
(2025)
arXiv
Persistently increased expression of PKM$\zeta$ and unbiased gene expression profiles identify hippocampal molecular traces of a long-term active place avoidance memory and ``shadow'' proteins
Han, J., Grau-Perales, A., Harris, R.M., Kao, H., Pal, A., Alarcon, J.M., Sacktor, T., Martiniani, S., Hofmann, H.A., Fenton, A.A.
(2025)
bioRxiv
arXiv
A unifying approach to self-organizing systems interacting via conservation laws
Barrows, F., Zhang, G., Anand, S., Chen, Z., Lin, J., Desai, A., Martiniani, S., Caravelli, F.
(2025)
arXiv
Contrastive Self-Supervised Learning As Neural Manifold Packing
Zhang, G., Heeger, D.J., Martiniani, S.
(2025)
arXiv
Hierarchical Neural Circuit Theory of Normalization and Inter-areal Communication
Morone, F., Pal, A., Rawat, S., Heeger, D.J., Martiniani, S.
(2025)
bioRxiv
arXiv
Stabilization of recurrent neural networks through divisive normalization
Morone, F., Rawat, S., Heeger, D.J., Martiniani, S.
(2025)
bioRxiv
arXiv
Absorbing state dynamics of stochastic gradient descent
Zhang, G., Martiniani, S.
(2024)
arXiv
The Basins of Attraction of Soft Sphere Packings Are Not Fractal
Suryadevara, P., Casiulis, M., Martiniani, S.
(2024)
arXiv
Social Physics of Bacteria: Avoidance of an Information Black Hole
Phan, T.V., Li, S., Ferreris, D., Morris, R., Bos, J., Guo, B., Martiniani, S., Chaikin, P., Kevrekidis, Y.G., Austin, R.H.
(2024)
arXiv

Published

Emergent universal long-range structure in random-organizing systems
Anand, S., Zhang, G., Martiniani, S.
Nature Communications 17 , 2346 (2026)
DOI arXiv
PropMolFlow: Property-guided Molecule Generation with Geometry-Complete Flow Matching
Zeng, C., Jin, J., Wang, W., Banerjee, T., Li, Z., Martiniani, S., Liu, M.
Nature Computational Science (2026)
DOI arXiv
Gyromorphs: A New Class of Functional Disordered Materials
Casiulis, M., Shih, A., Martiniani, S.
Phys. Rev. Lett. 135 , 196101 (2025)
DOI arXiv
A geometric condition for robot-swarm cohesion and cluster-flock transition
Casiulis, M., Arbel, E., van Waes, C., Lahini, Y., Martiniani, S., Oppenheimer, N., Ben Zion, M.Y.
Proc. Natl. Acad. Sci. 122 , e2502211122 (2025)
DOI
On the design space between molecular mechanics and machine learning force fields
Wang, Y., Takaba, K., Chen, M.S., Wieder, M., Xu, Y., Zhu, T., Zhang, J.Z.H., Nagle, A., Yu, K., Wang, X., Cole, D.J., Rackers, J.A., Cho, K., Greener, J.G., Eastman, P., Martiniani, S., Tuckerman, M.E.
Appl. Phys. Rev. 12 , 021304 (2025)
DOI
Open Materials Generation with Stochastic Interpolants
Hoellmer, P., Egg, T., Martirossyan, M.M., Fuemmeler, E., Gupta, A., Shui, Z., Prakash, P., Roitberg, A., Liu, M., Karypis, G., Transtrum, M., Hennig, R.G., Tadmor, E.B., Martiniani, S.
Proc. 42nd Int. Conf. Mach. Learn. (ICML), PMLR 267 (2025)
arXiv
A practical guide to machine learning interatomic potentials -- Status and future
Jacobs, R., Morgan, D., Attarian, S., Meng, J., Shen, C., Wu, Z., Xie, C.Y., Yang, J.H., Artrith, N., Blaiszik, B., Ceder, G., Choudhary, K., Csanyi, G., Cubuk, E.D., Deng, B., Drautz, R., Fu, X., Godwin, J., Honavar, V., Isayev, O., et al.
Curr. Opin. Solid State Mater. Sci. 35 , 101214 (2025)
DOI
Perspective on Artificial Intelligence for Accelerated Materials Design (AI4Mat) Workshops in 2024
Miret, S., Skreta, M., Wellawatte, G., Martiniani, S., Krishnan, N.M.A., Karypis, G., Jablonka, K.M.
Mach. Learn.: Sci. Technol. 6 , 040201 (2025)
DOI
Transport and Energetics of Bacterial Rectification
Anand, S., Ma, X., Guo, S., Martiniani, S., Cheng, X.
Proc. Natl. Acad. Sci. 121 , e2411608121 (2024)
DOI
Unconditional stability of a recurrent neural circuit implementing divisive normalization
Rawat, S., Martiniani, S.
Adv. Neural. Inf. Process. Syst. 38 (NeurIPS 2024) (2024)
Link
Advancing the ColabFit Exchange towards a Web-scale Data Source for Machine Learning Interatomic Potentials
Fuemmeler, E., Wolfe, G., Gupta, A., Vita, J.A., Tadmor, E.B., Martiniani, S.
AI for Accelerated Materials Design - NeurIPS 2024 (2024)
Link
Benchmarking of Universal Machine Learning Interatomic Potentials for Structural Relaxation
Gonzales, A.C., Fuemmeler, E., Tadmor, E.B., Martiniani, S., Miret, S.
AI for Accelerated Materials Design - NeurIPS 2024 (2024)
Link
Element-wise and Recursive Solutions for the Power Spectral Density of Biological Stochastic Dynamical Systems at Fixed Points
Rawat, S., Martiniani, S.
Phys. Rev. Research 6 , 043179 (2024)
DOI arXiv
Fast Generation of Spectrally-Shaped Disorder
Shih, A., Casiulis, M., Martiniani, S.
Phys. Rev. E 110 , 034122 (2024)
Editor's Suggestion. Highlighted in Old Movie Demos New Tech, Physics 17, 134 (2024)
DOI
KUSP: Python server for deploying ML interatomic potentials
Gupta, A., Tadmor, E.B., Martiniani, S.
AI for Accelerated Materials Design - Vienna 2024 (2024)
Link
ColabFit Exchange: open-access datasets for data-driven interatomic potentials
Vita, A., Fuemmeler, E.G., Gupta, A., Wolfe, G.P., Tao, A.Q., Elliott, R.S., Martiniani, S., Tadmor, E.B.
J. Chem. Phys. 159 , 154802 (2023)
Link PDF
Predicting and Interpreting Protein Developability via Transfer of Convolutional Sequence Representation
Golinski, A.W., Schmitz, Z.D., Nielsen, G.H., Johnson, B., Saha, D., Appiah, S., Hackel, B.J., Martiniani, S.
ACS Synthetic Biology 12 , 2600--2615 (2023)
Link PDF
Coherence influences the dimensionality of communication subspaces
Rawat, S., Heeger, D., Martiniani, S.
Cosyne Abstracts (2023)
Link PDF
Bit-propelled active matter
Martiniani, S.
Journal Club for Condensed Matter Physics (2023)
Link PDF
When you can't count sample! Computable entropies beyond equilibrium from basin volumes
Casiulis, M., Martiniani, S.
Papers in Physics 15 , 150001 (2023)
Invited perspective in ``Focus Series on Challenges in Granular Matter''
Link PDF
Estimating random close packing in polydisperse and bidisperse hard spheres via an equilibrium model of crowding
Anzivino, C., Casiulis, M., Zhang, T., Moussa, A.S., Martiniani, S., Zaccone, A.
J. Chem. Phys. 158 , 044901 (2023)
Link PDF
Model-Free Measurement of Local Entropy Production and Extractable Work in Active Matter
Ro, S., Guo, B., Shih, A., Phan, T.V., Austin, R.H., Levine, D., Chaikin, P.M., Martiniani, S.
Phys. Rev. Lett. 129 , 220601 (2022)
Cover article. Editor's Suggestion. Highlighted in Viewpoint: Measuring Entropy in Active-Matter Systems, Physics 15, 179 (2022)
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High-Throughput Developability Assays Enable Library-Scale Identification of Producible Protein Scaffold Variants
Golinski, A.W., Mischler, K.M., Laxminarayan, S., Neurock, N., Fossing, M., Pichman, H., Martiniani, S., Hackel, B.J.
Proc. Natl. Acad. Sci. 118 (2021)
Link PDF
Vicsek Model by Time-Interlaced Compression: a Dynamical Computable Information Density
Cavagna, A., Chaikin, P.M., Levine, D., Martiniani, S., Puglisi, A., Viale, M.
Phys. Rev. E 103 , 062141 (2021)
Link PDF
Data-driven approach to engineering protein evolvability and developability
Golinski, A.
(2021)
Link PDF
Correlation lengths in the language of computable information
Martiniani, S., Lemberg, Y., Chaikin, P.M., Levine, D.
Phys. Rev. Lett. 125 , 170601 (2020)
Link PDF
Monte Carlo sampling for stochastic weight functions
Frenkel, D., Schrenk, K.J., Martiniani, S.
Proc. Natl. Acad. Sci. 114 (2017)
Link PDF
Energy Landscapes for Machine Learning
Ballard, A.J., Das, R., Martiniani, S., Mehta, D., Sagun, L., Stevenson, J.D., Wales, D.J.
Phys. Chem. Chem. Phys. 19 , 12585 (2017)
Cover article for Phys. Chem. Chem. Phys.
Link PDF
On the complexity of energy landscapes: algorithms and a direct test of the Edwards conjecture
Martiniani, S.
(2017)
Link PDF
Structural analysis of high dimensional basins of attraction
Martiniani, S., Schrenk, K.J., Stevenson, J.D., Wales, D.J., Frenkel, D.
Phys. Rev. E 94 , 031301 (2016)
Link PDF
Turning intractable counting into sampling: computing the configurational entropy of three-dimensional jammed packings
Martiniani, S., Schrenk, K.J., Stevenson, J.D., Wales, D.J., Frenkel, D.
Phys. Rev. E 93 , 012906 (2016)
Highlighted in NewScientist and other news sources
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Exploiting the potential energy landscape to sample free energy
Ballard, A.J., Martiniani, S., Stevenson, J.D., Somani, S., Wales, D.J.
WIREs Comput. Mol. Sci. 5 , 273 (2015)
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Superposition Enhanced Nested Sampling
Martiniani, S., Stevenson, J.D., Wales, D.J., Frenkel, D.
Phys. Rev. X 4 , 031034 (2014)
Link PDF
Near-infrared absorbing squaraine dye with extended $\pi$ conjugation for dye-sensitized solar cells
Magistris, C., Martiniani, S., Barbero, N., Park, J., Benzi, C., Anderson, A., Law, C.H., Barolo, C., O'Regan, B.C.
Renewable Energy 60 , 672 (2013)
Link PDF
The Mechanism of Iodine Reduction by TiO2 Electrons and the Kinetics of Recombination in Dye-Sensitized Solar Cells
Richards, C.E., Anderson, A.Y., Martiniani, S., Law, C., O'Regan, B.C.
J. Phys. Chem. Lett. 3 , 1980 (2012)
Link PDF
New insight into the regeneration kinetics of dye sensitised solar cells
Martiniani, S., Anderson, A.Y., Law, C., O'Regan, B.C., Barolo, C.
Chem. Commun. 48 , 2406 (2012)
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