Nicholas F. Marshall

  
  Assistant Professor
  Department of Mathematics
  Oregon State University
  
  Email: [email protected]
  Office: Kidder 292
  Directory
  Link
  Research interests
I am interested in problems that
  involve an interplay between analysis, geometry, and probability
  (especially such problems motivated by data science).
  About
  
  Research
  
    - 
      arXiv:2510.24608
      Random Walks, Faber Polynomials and Accelerated Power Methods
      with Peter Cowal, Sara Pollock
     
    - 
      arXiv:2507.01885
      Faber polynomials in a deltoid region and power iteration momentum methods
      with Peter Cowal, Sara Pollock
     
    - 
      arXiv:2406.05922
      Fast expansion into harmonics on the ball
      with Joe
      Kileel, Oscar Mickelin,
      Amit
      Singer
      SIAM Journal on Scientific Computing doi.org/10.1137/24M1668159
     
    - 
      arXiv:2406.01552
      Learning equivariant tensor functions with applications to
      sparse vector recovery
      with Wilson G.
      Gregory, Josué
      Tonelli-Cueto, Andrew S. Lee,
      Soledad
      Villar
     
    - 
      arXiv:2404.10759
      Laplace-HDC: Understanding the geometry of binary
      hyperdimensional computing
      with 
      Saeid Pourmand, Wyatt
      Whiting, Alireza Aghasi
      Journal of Artificial Intelligence Research doi.org/10.1613/jair.1.17688
     
    - 
      arXiv:2401.15183
      Moment-based metrics for molecules computable from cryo-EM
      images
      with Andy
      Zhang, Oscar Mickelin,
      Joe
      Kileel, Eric
      Verbeke, Marc
      Gilles, Amit Singer
      Biological Imaging doi.org/10.1017/S2633903X24000023
     
    - 
      arXiv:2401.09415
      Randomized Kaczmarz with geometrically smoothed
      momentum
      with 
      Seth Alderman, Roan Luikart
      SIAM Journal on Matrix Analysis and Applications
      doi.org/10.1137/24M1633820
     
    - 
      arXiv:2212.14288
      From the binomial reshuffling model to Poisson
      distribution of money
      with Fei Cao
      Networks and Heterogeneous Media doi.org/10.3934/nhm.2024002
     
    - 
      arXiv:2210.17501
      Fast Principal Component Analysis for Cryo-EM
      Images
      with Oscar
      Mickelin, Yunpeng Shi, Amit Singer
      Biological Imaging doi.org/10.1017/S2633903X23000028
     
    - 
      arXiv:2207.13674
      Fast expansion into harmonics on the disk: a steerable
      basis with fast radial convolutions
      with Oscar
      Mickelin, Amit Singer
      SIAM Journal on Scientific Computing doi.org/10.1137/22M1542775
     
    - 
      arXiv:2202.12224
      An optimal scheduled learning rate for a randomized
      Kaczmarz algorithm
      with Oscar
      Mickelin
      SIAM Journal on Matrix Analysis and Applications
      doi.org/10.1137/22M148803X
     
    - 
      arXiv:2201.13386
      On a linearization of quadratic Wasserstein
      distance
      with 
      Philip Greengard, Jeremy Hoskins, Amit Singer
     
    - 
      arXiv:2107.14747
      A common variable minimax theorem for graphs
      with 
      Ronald Coifman, Stefan
      Steinerberger
      Foundations of Computational Mathematics doi.org/10.1007/s10208-022-09558-8
     
    - 
      arXiv:2101.07709
      Multi-target detection with rotations
      with Tamir
      Bendory, 
      Ti-Yen Lan, 
      Iris Rukshin, Amit Singer
      Inverse Problems and Imaging doi.org/10.3934/ipi.2022046
     
    - 
      arXiv:1910.10006
      Image recovery from rotational and translational
      invariants
      with Tamir
      Bendory, 
      Ti-Yen Lan, Amit Singer
      ICASSP doi.org/10.1109/ICASSP40776.2020.9053932
     
    - 
      arXiv:1910.04201
      Randomized mixed Hölder function approximation in
      higher-dimensions
      Technical Report
     
    - 
      arXiv:1907.03873
      A fast simple algorithm for computing the potential of
      charges on a line
      with Zydrunas
      Gimbutas, Vladimir
      Rokhlin
      Applied and Computational Harmonic Analysis doi.org/10.1016/j.acha.2020.06.002
     
    - 
      arXiv:1902.06633
      A Cheeger inequality for graphs based on a reflection
      principle
      with 
      Edward Gelernt, Diana Halikias,
      Charles
      Kenney
      Involve doi.org/10.2140/involve.2020.13.475
     
    - 
      arXiv:1810.00823
      Approximating mixed Hölder functions using random
      samples
      Annals of Applied Probability doi.org/10.1214/19-AAP1471
     
    - 
      arXiv:1711.06711
      Manifold learning with bi-stochastic kernels
      with 
      Ronald Coifman
      IMA Journal of Applied Mathematics doi.org/10.1093/imamat/hxy065
     
    - 
      arXiv:1707.00682
      Stretching convex domains to capture many lattice
      points
      International Mathematics Research Notices doi.org/10.1093/imrn/rny102
     
    - 
      arXiv:1706.04170
      Triangles capturing many lattice points
      with Stefan
      Steinerberger
      Mathematika doi.org/10.1112/S0025579318000219
     
    - 
      arXiv:1704.02962
      The Stability of the First Neumann Laplacian Eigenfunction
      Under Domain Deformations and Applications
      Applied and Computational Harmonic Analysis doi.org/10.1016/j.acha.2019.05.001
     
    - 
      arXiv:1608.03628
      Time Coupled Diffusion Maps
      with Matthew Hirn
      Applied and Computational Harmonic Analysis doi.org/10.1016/j.acha.2017.11.003
     
    - 
      arXiv:1607.05235
      Extracting Geography from Trade Data
      with Yuke Li,
      Tianhao
      Wu, Stefan
      Steinerberger
      Physica A doi.org/10.1016/j.physa.2017.01.037
     
  
  Notes
  Some short notes on various topics
  
    - 
      some-math-for-numerics.pdf
      
        - Introductory note about some key mathematical ideas
        used in numerical methods
 
        - Discusses asymptotic series, Richardson extrapolation,
        contraction mapping, and simple iteration
 
      
     
    - 
      stirlings-approximation.pdf
      
        - Elementary proof of Stirling's approximation up to
        constant
 
        - Discusses concave functions, trapezoid rule, midpoint
        rule
 
      
     
    - 
      euler-maclaurin.pdf
      
        - Informal and precise statements of Euler-Maclaurin
        formula
 
        - Preliminaries about asymptotic series, Richardson
        extrapolation, Taylor's theorem, Trapezoid rule
 
      
     
    - 
      gaussian-quadrature.pdf
      
        - Introduction to Gaussian quadrature
 
        - Introduces Legendre polynomials, Gaussian quadrature
        remainder formula, numerical example
 
      
     
    - 
      chebyshev-interpolation.pdf
      
        - Introduction to polynomial interpolation
 
        - Includes polynomial interpolation remainder formula,
        Chebyshev polynomials, Chebyshev nodes
 
      
     
    - 
      de-moivre-thm.pdf
      
        - Sketch of de Moivre's central limit theorem
 
        - Uses Binomial distribution, Stirling's formula, Reimann
        sum
 
      
     
  
  Mentoring
  
    - Graduate Students
      
    
 
    - Undergraduate Students
      
        - Summer research 2023 at Oregon State
          
         
        - Summer research 2020 at Princeton
          
         
        - Summer research 2018 at Yale
          
        
 
      
     
  
  Teaching
  
    - 
      Fall 2025
      
        - Advanced Calculus I, MTH 611, Oregon State University
 
        - Numerical Linear Algebra, MTH 451, Oregon State University
 
        - Probability I, MTH 463, Oregon State University
 
      
     
    - 
      Spring 2025
      
        - Complex Analysis, MTH 611, Oregon State University
 
      
     
    - 
      Winter 2025
      
        - Advanced Calculus II, MTH 312, Oregon State
        University
 
        - Mathematics of Data Science, MTH 499/599, Oregon State
        University
 
      
     
    - 
      Fall 2024
      
        - Probability Theory I, MTH 664, Oregon State
        University
 
      
     
    - 
      Spring 2024
      
        - High Dimensional Probability, MTH 669, Oregon State
        University
 
      
     
    - 
      Winter 2024
      
        - Probability Theory II, MTH 665, Oregon State
        University
 
      
     
    - 
      Fall 2023
      
        - Probability Theory, MTH 664, Oregon State
        University
 
      
     
    - 
      Spring 2023
      
        - Advanced Calculus II, MTH 312, Oregon State
        University
 
        - Probability III, MTH 465/565, Oregon State
        University
 
      
     
    - 
      Winter 2023
      
        - Probability II, MTH 464/564, Oregon State
        University
 
      
     
    - 
      Fall 2021
      
        - Numerical methods, MAT 321/APC 321, Princeton
        University
 
      
     
    - 
      Fall 2020
      
        - Numerical methods, MAT 321/APC 321, Princeton
        University
 
      
     
    - 
      Spring 2021
      
        - Linear Algebra with Applications, MAT 202, Princeton
        University
 
      
     
    - 
      Fall 2018
      
        - Calculus II, MATH 115, Yale University