Publications

Publications

  • F. Cao, S. Motsch, Uncovering a Two-Phase Dynamics from a Dollar Exchange Model with Bank and Debt, 2023, SIAM J. Applied Math. (PDF).
  • K. Wood, A. Comba, S. Motsch, T. Grigera, P. Lowenstein, Scale-free correlations and potential criticality in weakly ordered populations of brain cancer cells, 2023, Science Advances (PDF).
  • F. Cao, S. Motsch, Derivation of wealth distributions from biased exchange of money, 2023, Kinetic and Related Models (KRM) (preprint).
  • F. Cao, P-E Jabin, S. Motsch, Entropy Dissipation and Propagation of Chaos for the Uniform Reshuffling Model, 2023, Math. Models Methods Appl. Sci. (M3AS) (preprint).
  • Comba, A., Faisal, S.M., Dunn, P.J. et al., Spatiotemporal analysis of glioma heterogeneity reveals COL1A1 as an actionable target to disrupt tumor progression, 2022, Nature Communications (PDF).
  • A. Comba, S. Faisal, M. Varela, T. Hollon, W. Al-Holou, Y. Umemura, F. Nunez, S. Motsch, M. Castro, P. Lowenstein, Uncovering spatiotemporal heterogeneity of high-grade gliomas: from disease biology to therapeutic implications, 2021, Frontiers in oncology (PDF).
  • F. Cao, S. Motsch, A. Reamy, R. Theisen, Asymptotic flocking for the three-zone model, 2020, Mathematical Biosciences and Engineering (PDF).
  • G. Li, S. Motsch, D. Weber, Bounded confidence dynamics and graph control: Enforcing consensus, 2020, Networks & Heterogeneous Media (PDF).
  • S. Jamous, A. Comba, P. Lowenstein, S. Motsch, Self-organization in brain tumors: How cell morphology and cell density influence glioma pattern formation, 2020, PLoS Comp. Bio. (PDF).
  • L.A. Poissonnier, S. Motsch, J. Gautrais, J. Buhl, A. Dussutour, Still flowing, ant traffic under crowded conditions, 2019, eLife (PDF).
  • S. Motsch, Q. Griette, Kinetic equations and self-organized band formations, 2019,  Springer, Active Particles, Volume 2 (PDF).
  • D. Weber, R. Theisen, S. Motsch, Deterministic versus stochastic consensus dynamics on graphs, 2019, J. Stat. Phys. (PDF).
  • S. Motsch, M. Moussaid, E. Guillot, M. Moreau, J. Pettré, G. Théraulaz, C. Appert-Rolland, P. Degond, Modeling crowd dynamics through coarse-grained data analysis, 2018, Math. Bio. Engineering (PDF).
  • S. Motsch, D. Peurichard, From short-range repulsion to Hele-Shaw problem in a model of tumor growth, 2017, J. Math. Biol. (preprint, PDF).
  • P. Degond, M. Ferreira, S. Motsch, Damped Arrow-Hurwicz algorithm for sphere packing, 2017, J. Comput. Phys. (PDF).
  • D. Armbruster, S. Motsch, A. Thatcher, Swarming in Bounded Domains, 2017, Physica D. (PDF)
  • G. Dimarco, S. Motsch, Self-alignment driven by jump processes: macroscopic limit and numerical investigation, 2016, Math. Models Methods Appl. Sci. (M3AS) (Preprint, PDF).
  • J. Haack, I. Gamba, S. Motsch, Spectral method for a kinetic swarming model, 2015, J. Comput. Phys., 297:32-46, (Preprint, PDF).
  • G. Baker, V. Yadav, S. Motsch, C. Koschmann, A. Calinescu, Y. Mineharu, S. Camelo-Piragua, D. Orringer, S. Bannykh, W. Nichols, A. deCarvalho, T. Mikkelsen, M. Castro, P. Lowenstein, Mechanisms of Glioma Formation: Iterative Perivascular Glioma Growth and Invasion Leads to Tumor Progression, VEGF-Independent Vascularization, and Resistance to Antiangiogenic Therapy, 2014, Neoplasia, 16(7):543-561 (PDF).
  • P-E. Jabin, S. Motsch, Clustering and asymptotic behavior in opinion formation, 2014, J. Diffential Equations, 257(11):4165–4187 (Preprint, PDF).
  • S. Motsch, E. Tadmor, Heterophilious dynamics enhances consensus, 2014, SIAM review, 56(4):577–621 (arXiv, PDF).
  • P. Degond, J.G. Liu, S. Motsch, V. Panferov, Hydrodynamic models of self-organized dynamics: derivation and existence theory, 2013, Methods Appl. Anal., 20(2):89–114 (arXiv, PDF).
  • E. Boissard, P. Degond, S. Motsch, Trail formation based on directed pheromone deposition, 2013, J. Math. Biol., 66(6):1267-1301 (arXiv, PDF).
  • P. Degond, A. Frouvelle, J-G. Liu, S. Motsch, L. Navoret, Macroscopic models of collective motion and self-organization, 2012, Séminaire Laurent Schwartz – EDP et applications, exposé n°1 (arXiv, PDF).
  • S. Motsch, L. Navoret, Numerical simulations of a non-conservative hyperbolic system with geometric constraints describing swarming behavior, 2011, Multiscale Model. Simul., 9(3):1253-1275 (Preprint, PDF).
  • S. Motsch, E. Tadmor, A new model for self-organized dynamics and its flocking behavior, J. Stat. Phys., 144(5):923-947, 2011 (Preprint, PDF).
  • C. Appert-Rolland, P. Degond, S. Motsch, Two-way multi-lane traffic model for pedestrians in corridors, Netw. Heterog. Media, 6(3):351-381, 2011 (Preprint, PDF).
  • P. Degond, S. Motsch, A macroscopic model for a system of swarming agents using curvature control, J. Stat. Phys. Springer, 141(4):685-714, 2011 (Preprint, PDF).
  • P. Cattiaux, D. Chafai, S. Motsch, Asymptotic analysis and diffusion limit of the Persistent Turning Walker Model, Asymptot. Anal., 67(1-2):17-31, 2010 (Preprint, PDF).
  • J. Gautrais, C. Jost, M. Soria, A. Campo, S. Motsch, R. Fournier, S. Blanco, G. Theraulaz, Analyzing fish movement as a persistent turning walker, J. Math. Biol., 58(3):429-445, 2009 (PDF).
  • M. Herty, A. Klar, S. Motsch, F. Olawsky, A smooth model for fiber lay-down processes and its diffusion approximations, Kinet. Relat. Models, 2(3): 489-502, 2009 (Preprint, PDF).
  • G. Bal, J. Garnier, S. Motsch, V. Perrier, Random integrals and correctors in homogenization, Asymptot. Anal., 58(1-2):1-26, 2008 (Preprint, PDF).
  • P. Degond, S. Motsch, Continuum limit of self-driven particles with orientation interaction, Math. Models Methods Appl. Sci. (M3AS), 18(1):1193-1215, 2008 (Preprint, PDF).
  • P. Degond, S. Motsch, Large-scale dynamics of the Persistent Turning Walker model of fish behavior, J. Stat. Phys., 131(6):989-1021, 2007 (Preprint, PDF).

Curriculum vitae

PhD thesis

I have done my PhD in Toulouse (France) at the IMT (Institut de Mathematiques de Toulouse) under the direction of Pierre Degond and Guy Theraulaz. My thesis was an interdisciplinary project between two teams: MIP (Mathematics for Industry and Physics) and CRCA (Research Center of Animal Cognition).