Curriculum Vitae

Academic Positions

Education

Academic Summary

Selected Awards

AFOSR YIP, NSF CAREER, IUPAP Interdisciplinary Early Career Scientist Prize, CZI Neuroscience Pairs Pilot Award, Simons Foundation Faculty Fellowship, Outstanding PhD Thesis Prize

Publications

43 research articles (8 lead author, 25 corresponding author, 22 led by trainees), 6 workshop papers (3 spotlight), 5 extended abstracts, 1 commentary, 1 editorial, 2 provisional US patents.

Presentations

79 past talks (59 invited), 11 posters.

Funding

Total PI/co-PI extramural funding: $12,803,189 ($11,573,999 as PI).

Leadership

Lead PI of FERMat project, involving 8 investigators across 4 universities (NYU, UMN, UF, BYU) and 1 industry partner (AWS); co-PI of ColabFit Exchange; Program Chair AI4Mat Workshop (NeurIPS ×2, ICLR ×2); Organizer NYC AI4Chemistry Summit (2025, 2026); Co-founder and member of organizing committee KIMReview.

Teaching Innovation

Developed UMN's first non-CS/Stats ML course "Machine Learning for Chemical Sciences" and graduate course "Physics of Neural Systems" at NYU.

Mentorship

Currently leading a group of 8 graduate students, 9 postdocs/research scientists, 1 software developer, 1 MS, 1 UG. Past trainees: 2 PhDs in ChEn, 3 PhDs in Mathematics, 1 PhD Physics, 2 Postdoc, 1 master, 15 undergraduates (3 published), 4 high-school students (1 published), 3 ColabFit interns (2 published).

Media

Research highlighted on PRL cover, PCCP cover, Nature, Nature Materials, Physics (1, 2, 3), Physics Today (1, 2), New Scientist, Science & Vie, Sky News, ANSA.

Honors & Awards

Extramural Funding

1. Role: PI; PD/PI: Martiniani; Title: "Advancing Light Manipulation and Optical Computing with Engineered Disordered Photonic Metamaterials"; Program: AFOSR YIP; Funds: $449,420; Duration: Sept 2025 – Sept 2028; Award number: FA9550-25-1-0359.
2. Role: PI; PD/PI: Martiniani; Title: "CAREER: Quantifying the Complexity of Materials Landscapes by Basin Sampling"; Program: NSF DMR-CMMT; Funds: $700,000; Duration: 5 years (Mar 2025 – Feb 2030); Award number: 2443027.
3. Role: PI; PD/PI: Heeger (contact), Martiniani; Title: "Oscillatory Recurrent Gated Neural Integrator Circuits (ORGaNICs): a unified framework for neural dynamics and human cognition"; Program: NIH NIMH R01 (multi-PI); Funds: $3,670,550; Duration: 5 years (Jul 2024 – Jun 2029); Award number: R01MH137669.
4. Role: PI; PD/PI: Martiniani; Title: "Theme 2: AI Institute for Extreme Computing Materials (AI-XCoM)"; Program: NYU Mega Grants Initiative Seed Fund; Funds: $25,000; Duration: 11 months (Feb 2024 – Dec 2024).
5. Role: PI; PD/PI: Martiniani (contact), Fenton; Title: "Machine Learning the Biomolecular Basis of Memory Persistence"; Program: CZI Neuroscience Pairs Pilot Project Awards; Funds: $200,000; Duration: 2 years (March 2024 – March 2025); Award number: 2024-338565.
6. Role: PI; PD/PI: Martiniani; Title: "GOALI: Frameworks: At-Scale Heterogeneous Data based Adaptive Development Platform for Machine-Learning Models for Material and Chemical Discovery"; Program: NSF OAC; Funds: $4,500,000; Duration: 5 years (Oct 2023 – Sept 2028); Award number: 2311632.
7. Role: PI; PD/PI: Heeger (contact), Martiniani; Title: "Recurrent circuit model of neural response dynamics in V1"; Program: NIH NEI R01 (multi-PI); Funds: $1,879,804; Duration: 4 years (Sept 2023 – Sept 2027); Award number: R01EY035242.
8. Role: PI; PD/PI: Martiniani; Title: "EAGER: Quantifying the error landscape of deep neural networks"; Program: NSF III; Funds: $149,225; Duration: 2 years (Oct 2021 – Aug 2024); Award number: 2132995.
9. Role: co-PI; PD/PI: Tadmor; Title: "Data CI Pilot: CI-Based Collaborative Development of Data-Driven Interatomic Potentials for Predictive Molecular Simulations"; Program: NSF CESER; Funds: $1,127,993; Duration: 2 years (Oct 2020 – Sept 2024); Award number: 2039575.
10. Role: co-I; PD/PI: Kumar, Fenton; Title: "PKMzeta organization in persistent memory and non-memory identified spines"; Program: CZI Neuroscience Collaboration Supplements; Funds: $30,000; Duration: 1 year (Dec 2024 – Dec 2025); Award number: NS-CS-39.
11. Role: co-I; PD/PI: Hackel; Title: "Engineering Protein Developability"; Program: NIH GM R01; Funds: subaward $71,197 (total $1,815,456); Duration: 4 years (Oct 2022 – 2026); Award number: GM146372.

Publications

*trainee, †contributed equally, (co-)corresponding author

Preprints/Submitted

• 43. R. Sharma*, G. Hogervorst, W.E. Mackey, D.J. Heeger, S. Martiniani, "Cross-View World Models", arXiv:2602.07277 (2026)
• 42. P. Hoellmer*, S. Martiniani, "Open Materials Generation with Inference-Time Reinforcement Learning", arXiv:2602.00424 (2026)
• 41. L.V. Luzzatto, M. Casiulis*, S. Martiniani, I. Kovacs, "Spatial and Temporal Cluster Tomography of Active Matter", arXiv:2511.09444 (2025)
• 40. P. Prakash, J.B. Gibson, Z. Li, G. Di Gianluca, J. Esquivel, E. Fuemmeler*, B. Geisler, J.S. Kim, A. Roitberg, E.B. Tadmor, M. Liu, S. Martiniani, G.R. Stewart, J.J. Hamlin, P.J. Hirschfeld, R.G. Hennig, "Guided Diffusion for the Discovery of New Superconductors", arXiv:2509.25186 (2025)
• 39. F. Barrows, G. Zhang*, S. Anand*, Z. Chen*, J. Lin, A. Desai, S. Martiniani, F. Caravelli, "A unifying approach to self-organizing systems interacting via conservation laws", arXiv:2507.02575 (2025)
• 38. A. Pal*, S. Rawat*, D.J. Heeger, S. Martiniani, "Hierarchical Neural Circuit Theory of Normalization and Inter-areal Communication", bioRxiv 2025.07.15.664935 (2025)
• 37. F. Morone*, S. Rawat*, D.J. Heeger, S. Martiniani, "Stabilization of recurrent neural networks through divisive normalization", bioRxiv 2025.05.16.654567 (2025)
• 36. J. Han*, A. Grau-Perales, R.M. Harris, H. Kao, A. Pal*, J.M. Alarcon, T. Sacktor, S. Martiniani, H.A. Hofmann, A.A. Fenton, "Persistently increased expression of PKMς and unbiased gene expression profiles identify hippocampal molecular traces of a long-term active place avoidance memory and 'shadow' proteins", bioRxiv 2025.04.28.651143 (2025)
• 35. G. Zhang*, S. Martiniani, "Absorbing state dynamics of stochastic gradient descent", arXiv:2411.11834 (2024)
• 34. P. Suryadevara*, M. Casiulis*, S. Martiniani, "The Basins of Attraction of Soft Sphere Packings are Not Fractal", arXiv:2409.12113 (2024)
• 33. T.V. Phan, S. Li, D. Ferreris, R. Morris, J. Bos, B. Guo, S. Martiniani, P. Chaikin, Y.G. Kevrekidis, R.H. Austin, "Social Physics of Bacteria: Avoidance of an Information Black Hole", arXiv:2401.16691 (2024)

Peer-Reviewed Articles

• 32. S. Anand*, G. Zhang*, S. Martiniani, "Emergent universal long-range structure in random-organizing systems", Nat. Comm., accepted (arXiv:2505.22933) (2026)
• 31. C. Zeng, J. Jin, G. Karypis, M. Transtrum, E.B. Tadmor, R.G. Hennig, A. Roitberg, S. Martiniani, M. Liu, "PropMolFlow: Property-guided Molecule Generation with Geometry-Complete Flow Matching", Nat. Comp. Sci. (2026)
• 30. G. Zhang*, D.J. Heeger*, S. Martiniani, "Contrastive Self-Supervised Learning As Neural Manifold Packing", NeurIPS 2025, accepted (arXiv:2506.13717) (2025)
• 29. M. Martirossyan*, T. Egg*, P. Höllmer*, G. Karypis, M. Transtrum, A. Roitberg, M. Liu, R. Hennig, E.B. Tadmor, S. Martiniani, "All that structure matches does not glitter", NeurIPS 2025, accepted (arXiv:2509.12178) (2025)
• 28. M. Casiulis*, A. Shih*, S. Martiniani, "Gyromorphs: a new class of functional disordered materials", Phys. Rev. Lett., 135, 196101 (2025)
• 27. M. Casiulis*, E. Arbel, Y. Lahini, S. Martiniani, N. Oppenheimer, M. Yah Ben Zion, "A geometric condition for robot-swarm cohesion and cluster-flock transition", Proc. Natl. Acad. Sci., 122(37) e2502211122 (2025)
• 26. P. Hoellmer*, T. Egg*, M.M. Martirossyan*, E. Fuemmeler*, Z. Shui, A. Gupta*, P. Prakash, A. Roitberg, M. Liu, G. Karypis, M. Transtrum, R.G. Hennig, E.B. Tadmor, S. Martiniani, "Open Materials Generation with Stochastic Interpolants", Proc. 42nd Int. Conf. Mach. Learn. (ICML), PMLR 267 (2025)
• 25. Y. Wang, K. Takaba, M.S. Chen, M. Wieder, Y. Xu, T. Zhu, J.Z.H. Zhang, A. Nagle, K. Yu, X. Wang, D.J. Cole, J.A. Rackers, K. Cho, J.G. Greener, P. Eastman, S. Martiniani, M.E. Tuckerman, "On the design space between molecular mechanics and machine learning force fields", Appl. Phys. Rev. 12, 021304 (2025)
• 24. R. Jacobs, D. Morgan, S. Attarian, J. Meng, C. Shen, Z. Wu, C. Xie, J.H. Yang, N. Artrith, B. Blaiszik, G. Ceder, K. Choudhary, G. Csanyi, B. Deng, R. Drautz, J. Godwin, V. Honavar, O. Isayev, A. Johansson, S. Martiniani, S.P. Ong, I. Poltavsky, K.J. Schmidt, S. Takamoto, A. Thompson, J. Westermayr, "A Practical Guide to Machine Learning Interatomic Potentials–Status and Future", Curr. Opin. Solid State Mater. Sci., 35, 101214 (2025)
• 23. S. Anand*, X. Ma, S. Guo, S. Martiniani^†, X. Cheng^†, "Transport and Energetics of Bacterial Rectification", Proc. Natl. Acad. Sci., 121(52), e2411608121 (2024)
• 22. S. Rawat*, D. Heeger, S. Martiniani, "Unconditional stability of a recurrent neural circuit implementing divisive normalization", Adv. Neural. Inf. Process. Syst. 38 (NeurIPS 2024), (arXiv:2409.18946) (2024)
• 21. S. Rawat*, S. Martiniani, "Element-wise and Recursive Solutions for the Power Spectral Density of Biological Stochastic Dynamical Systems at Fixed Points", Phys. Rev. Res., 6, 043179 (2024)
• 20. A. Shih*, M. Casiulis*, S. Martiniani, "Fast Generation of Spectrally-Shaped Disorder", Phys. Rev. E 110, 034122 (2024) – Editor's Suggestion in Phys. Rev. E – Awarded Gallery of Soft Matter Prize; highlighted in Physics, 17, 41 (2024) – Highlighted in "Old Movie Demos New Tech", Physics, 17, 134 (2024)
• 19. J.A. Vita*, E.G. Fuemmeler*, A. Gupta*, G.P. Wolfe*, A.Q. Tao*, R.S. Elliott, S. Martiniani, E.B. Tadmor, "ColabFit Exchange: open-access datasets for data-driven interatomic potentials", J. Chem. Phys. 159, 154802 (2023)
• 18. A.W. Golinski*, Z.D. Schmitz*, G.H. Nielsen, B. Johnson*, D. Saha*, S. Appiah*, B.J. Hackel, S. Martiniani, "Predicting and Interpreting Protein Developability via Transfer of Convolutional Sequence Representation", ACS Synth. Biol. 12, 9, 2600 (2023)
• 17. M. Casiulis*, S. Martiniani, "When you can't count sample! Computable entropies beyond equilibrium from basin volumes", Papers in Physics, 15, 150001 (2023) – Invited perspective in "Focus Series on Challenges in Granular Matter"
• 16. C. Anzivino, M. Casiulis*, T. Zhang*, A.S. Moussa, S. Martiniani, A. Zaccone, "Estimating random close packing in polydisperse and bidisperse hard spheres via an equilibrium model of crowding", J. Chem. Phys., 158, 044901 (2023)
• 15. S. Ro, B. Guo, A. Shih*, T.V. Phan, R.H. Austin, D. Levine, P.M. Chaikin, S. Martiniani, "Model-Free Measurement of Local Entropy Production and Extractable Work in Active Matter", Phys. Rev. Lett. 129, 220601 (2022) – Cover article for Phys. Rev. Lett. – Editor's Suggestion in Phys. Rev. Lett. – Highlighted in "Measuring Entropy in Active-Matter Systems", Physics 15, 179 (2022)
• 14. A.W. Golinski*, K.M. Mischler, S. Laxminarayan, N. Neurock, M. Fossing, H. Pichman, S. Martiniani, B.J. Hackel, "High-Throughput Developability Assays Enable Library-Scale Identification of Producible Protein Scaffold Variants", Proc. Natl. Acad. Sci., 118, 23 (2021)
• 13. A. Cavagna, P.M. Chaikin, D. Levine, S. Martiniani, A. Puglisi, M. Viale, "Vicsek Model by Time-Interlaced Compression: a Dynamical Computable Information Density", Phys. Rev. E 103, 062141 (2021)
• 12. S. Martiniani, Y. Lemberg, P.M. Chaikin, D. Levine, "Correlation lengths in the language of computable information", Phys. Rev. Lett., 125, 170601 (2020)
• 11. S. Martiniani, P.M. Chaikin, D. Levine, "Quantifying hidden order out of equilibrium", Phys. Rev. X, 9, 011031 (2019) – Highlighted in "File compression uncovers hidden order", Physics Today (2019)
• 10. S. Martiniani, K.J. Schrenk, K. Ramola, B. Chakraborty, D. Frenkel, "Numerical test of the Edwards conjecture shows that all packings become equally probable at jamming", Nature Physics, 13, 848–851 (2017) – Highlighted in "Intuition harnessed in the name of particle packing", Nature, 546, 575 (2017) – Highlighted in "A thermodynamic theory of granular materials endures", Physics Today 70, 9 (2017) – Highlighted in "Material Witness: A jammy guess?", Nature Materials, 15, 1227 (2016)
• 9. D. Frenkel, K.J. Schrenk, S. Martiniani, "Monte Carlo sampling for stochastic weight functions", Proc. Natl. Acad. Sci., 114, 27 (2017)
• 8. A.J. Ballard, R. Das, S. Martiniani, D. Mehta, L. Sagun, J.D. Stevenson, D.J. Wales, "Energy Landscapes for Machine Learning", Phys. Chem. Chem. Phys., 19, 12585 (2017) – Cover article for Phys. Chem. Chem. Phys.
• 7. S. Martiniani, K.J. Schrenk, J.D. Stevenson, D.J. Wales, D. Frenkel, "Structural analysis of high dimensional basins of attraction", Phys. Rev. E 94, 031301 (2016)
• 6. S. Martiniani, K.J. Schrenk, J.D. Stevenson, D.J. Wales, D. Frenkel, "Turning intractable counting into sampling: computing the configurational entropy of three-dimensional jammed packings", Phys. Rev. E 93, 012906 (2016)
• 5. A.J. Ballard, S. Martiniani, J.D. Stevenson, S. Somani, D.J. Wales, "Exploiting the potential energy landscape to sample free energy", WIREs Comput. Mol. Sci. 5, 273 (2015)
• 4. S. Martiniani, J.D. Stevenson, D.J. Wales, D. Frenkel, "Superposition Enhanced Nested Sampling", Phys. Rev. X 4, 031034 (2014)
• 3. C. Magistris^†, S. Martiniani^†, N. Barbero, J. Park, C. Benzi, A. Anderson, C.H. Law, C. Barolo, B.C. O'Regan, "Near-infrared absorbing squaraine dye with extended π conjugation for dye-sensitized solar cells", Renewable Energy 60, 672 (2013)
• 2. C.E. Richards, A.Y. Anderson, S. Martiniani, C. Law, B.C. O'Regan, "The Mechanism of Iodine Reduction by TiO₂ Electrons and the Kinetics of Recombination in Dye-Sensitized Solar Cells", J. Phys. Chem. Lett. 3, 1980 (2012)
• 1. S. Martiniani, A.Y. Anderson, C. Law, B.C. O'Regan and C. Barolo, "New insight into the regeneration kinetics of dye sensitized solar cells", Chem. Commun. 48, 2406 (2012)

Peer-Reviewed Workshop Papers

• 6. P. Prakash, J.B. Gibson, Z. Li, G. Di Gianluca, J. Esquivel, E. Fuemmeler, B. Geisler, A. Roitberg, E.B. Tadmor, M. Liu, S. Martiniani, G.R. Stewart, J. Hamlin, P. Hirschfeld, R. Hennig, "Inverse Design of Novel Superconductors via Guided Diffusion", AI for Accelerated Materials Design – NeurIPS 2025 (Spotlight)
• 5. C. Zeng, J. Jin, P. Prakash, G. Karypis, M. Transtrum, E.B. Tadmor, R. Hennig, A. Roitberg, S. Martiniani, M. Liu, "MolGuidance: A Comparative Study of Guidance Methods for Conditional Molecule Generation", Generative AI and Biology (GenBio) Workshop – ICML 2025
• 4. P. Hoellmer*, T. Egg*, M.M. Martirossyan*, E. Fuemmeler*, Z. Shui, A. Gupta*, P. Prakash, A. Roitberg, M. Liu, G. Karypis, M. Transtrum, R.G. Hennig, E.B. Tadmor, S. Martiniani, "Open Materials Generation with Stochastic Interpolants", AI for Accelerated Materials Design – ICLR 2025 (Spotlight)
• 3. E. Fuemmeler*, G. Wolfe*, A. Gupta*, J.A. Vita, E.B. Tadmor, S. Martiniani, "Advancing the ColabFit Exchange towards a Web-scale Data Source for Machine Learning Interatomic Potentials", AI for Accelerated Materials Design – NeurIPS 2024 (Spotlight)
• 2. C. Gonzales, E. Fuemmeler*, E.B. Tadmor, S. Martiniani, S. Miret, "Benchmarking of Universal Machine Learning Interatomic Potentials for Structural Relaxation", AI for Accelerated Materials Design – NeurIPS 2024
• 1. A. Gupta*, E.B. Tadmor, S. Martiniani, "KUSP: Python server for deploying ML interatomic potentials", AI for Accelerated Materials Design – Vienna 2024

Peer-Reviewed Extended Abstracts

• 5. A. Pal*, S. Rawat*, D. Heeger, S. Martiniani, "Multi-stage Cortical Recurrent Circuit Implementing Normalization", CCN Abstracts (2024)
• 4. S. Rawat*, D. Heeger, S. Martiniani, "A comprehensive large-scale model of primary visual cortex (V1)", CCN Abstracts (2024)
• 3. G. Zhang*, S. Martiniani, "Neural manifold packing by stochastic gradient descent", CCN Abstracts (2024)
• 2. S. Rawat*, D. Heeger, S. Martiniani, "A comprehensive large-scale model of primary visual cortex (V1)", Cosyne Abstracts (2024)
• 1. S. Rawat*, D. Heeger, S. Martiniani, "Coherence influences the dimensionality of communication subspaces", Cosyne Abstracts (2023)

Commentaries & Editorials

• 1. S. Martiniani, "Bit-propelled Active Matter", Journal Club for Condensed Matter Physics (2023)
• 1. S. Miret, M. Skreta, G. Wellawatte, S. Martiniani, N.M.A. Krishnan, G. Karypis, K.M. Jablonka, "Perspective on Artificial Intelligence for Accelerated Materials Design (AI4Mat) Workshops in 2024", Mach. Learn.: Sci. Technol., 6(4), 040201 (2025)

PhD Thesis

• S. Martiniani, "On the complexity of energy landscapes: algorithms and a direct test of the Edwards conjecture", University of Cambridge (2017) – Awarded "Outstanding Thesis Prize", Dept. of Chemistry, University of Cambridge

Patents

• 1. A. Shih, M. Casiulis, S. Martiniani, "System, Method and Computer-Accessible Medium for Accelerated Generation of Statistically Correlated Point Structures", Provisional Patent Application 63/651,613 (May 2024)
• 2. A. Shih, M. Casiulis, S. Martiniani, "System, Method, and Computer-Accessible Medium for Generating Functional Correlated Disordered Materials", Provisional Patent Application 63/811,349 (May 2025)

Teaching

University Service

Other Service

Mentorship & Training

Public Engagement & Media

Other Professional Experience