Dane Taylor, Assistant Professor of Mathematics

University at Buffalo, State University of New York

- CV - Google Scholar - UB Website -

email: danet [at] buffalo (dot) edu tel: (716) 645 8796 fax: (716) 645 5039 mail: 224 Mathematics Building University at Buffalo Buffalo, NY 14260-2900 .

Multiscale Modeling, Simulation and Theory of Complex Systems

  • I develop theory for models of high-dimensional data and nonlinear dynamical systems that involve multilayer, multiplex and temporal networks.

  • I develop methods including multiscale models, perturbation theory, random matrix theory, information theory, numerical methods, topological data analysis and dynamics-driven geometry.

  • I study multiscale and self-organizing aspects of biological, social, physical, and information systems through interdisciplinary collaborations with domain experts.


  • A Queiruga, NB Erichson, D Taylor and MW Mahoney (2020) Continuous-in-depth neural networks. Submitted. [arXiv]

  • NB Erichson, D Taylor, Q Wu and MW Mahoney (2020) Noise-response analysis for rapid detection of backdoors in deep neural networks. Submitted. [arXiv]

  • D Taylor, MA Porter and PJ Mucha (2019) Tunable eigenvector-based centralities for multiplex and temporal networks. Submitted. [arXiv]

Select Publications

  • D Taylor (2020) Multiplex Markov chains: Convection cycles and optimality. Physical Review Research 2, 033164.

  • PS Skardal, D Taylor, J Sun (2019) Synchronization of network-coupled oscillators with uncertain dynamics. SIAM Journal on Applied Mathematics 79(6), 2409–2433.

  • Z Li, PJ Mucha and D Taylor (2018) Network-ensemble comparisons with stochastic rewiring and von Neumann entropy. SIAM Journal on Applied Mathematics 78(2), 897–920.

  • D Taylor, RS Caceres and PJ Mucha (2017) Super-resolution community detection for layer-aggregated multilayer networks. Physical Review X 7, 031056.

  • D Taylor, S Shai, N Stanley and PJ Mucha (2016) Enhanced detectability of community structure in multilayer networks through layer aggregation. Physical Review Letters 116, 228301.

  • D Taylor, F Klimm, HA Harrington, M Kramar, K Mischaikow, MA Porter and PJ Mucha (2015) Topological data analysis of contagion maps for examining spreading processes on networks. Nature Communications 6, 7723.

  • J Sun, D Taylor and EM Bollt (2015) Causal network inference by optimal causation entropy. SIAM Journal on Applied Dynamical Systems 14(1), 73-106.

  • PS Skardal, D Taylor and J Sun (2014) Optimal synchronization of complex networks. Physical Review Letters 113, 144101.