I am an assistant professor in the Department of Mathematical Sciences at NJIT. I teach applied mathematics courses (linear algebra, partial differential equations, vector analysis, etc.) and conduct research in scientific computing and numerical analysis. My primary research interests are in fast and high-order accurate numerical methods for the PDEs of mathematical physics and optimization algorithms for inverse problems.

Publications

Journal Articles
  • Travis Askham, Carlos Borges, Reconstructing the shape and material parameters of dissipative obstacles using an impedance model. Inverse Problems, Accepted 2024. accepted manuscript
  • Travis Askham, Carlos Borges, Jeremy Hoskins, and Manas Rachh, Random walks in frequency and the reconstruction of obstacles with cavities from multi-frequency data. Journal of Scientific Computing, 98(1) 15, 2023. accepted manuscript
  • Ruqi Pei, Travis Askham, Leslie Greengard, and Shidong Jiang, A fast method for imposing periodic boundary conditions on arbitrarily-shaped lattices in two dimensions. Journal of Computational Physics, 474:111792, 2023. accepted manuscript
  • Travis Askham, Peng Zheng, Aleksandr Aravkin, and J Nathan Kutz, Robust and scalable methods for the dynamic mode decomposition. SIAM Journal on Applied Dynamical Systems, 21(1):60–79, 2022. accepted manuscript
  • Ludvig af Klinteberg, Travis Askham, and Mary Catherine Kropinski, A fast integral equation method for the two-dimensional navier-stokes equations. Journal of Computational Physics, 409:109353, 2020. accepted manuscript
  • Travis Askham and Manas Rachh, A boundary integral equation approach to computing eigenvalues of the stokes operator. Advances in Computational Mathematics, 46(2):1–42, 2020. accepted manuscript
  • Niall M Mangan, Travis Askham, Steven L Brunton, J Nathan Kutz, and Joshua L Proctor, Model selection for hybrid dynamical systems via sparse regression. Proceedings of the Royal Society A, 475(2223):20180534, 2019. accepted manuscript
  • Peng Zheng, Travis Askham, Steven L Brunton, J Nathan Kutz, and Aleksandr Y Aravkin, A unified framework for sparse relaxed regularized regression: SR3. IEEE Access, 7:1404–1423, 2019. accepted manuscript
  • Travis Askham, A stabilized separation of variables method for the modified biharmonic equation. Journal of Scientific Computing, 76(3):1674–1697, 2018. accepted manuscript
  • Travis Askham and J Nathan Kutz, Variable projection methods for an optimized dynamic mode decomposition. SIAM Journal on Applied Dynamical Systems, 17(1):380–416, 2018. accepted manuscript
  • Emily Clark, Travis Askham, Steven L Brunton, and J Nathan Kutz, Greedy sensor placement with cost constraints. IEEE Sensors Journal, 19(7):2642–2656, 2018. accepted manuscript
  • Manas Rachh and Travis Askham, Integral equation formulation of the biharmonic dirichlet problem. Journal of Scientific Computing, 75(2):762–781, 2018. accepted manuscript
  • Chang Sun, Travis Askham, and J Nathan Kutz, Stability and dynamics of microring combs: elliptic function solutions of the Lugiato–Lefever equation. JOSA B, 35(6):1341–1353, 2018. accepted manuscript
  • Travis Askham and Antoine J Cerfon, An adaptive fast multipole accelerated poisson solver for complex geometries. Journal of Computational Physics, 344:1–22, 2017. accepted manuscript
  • Travis Askham and Leslie Greengard, Norm-preserving discretization of integral equations for elliptic pdes with internal layers I: The one-dimensional case. SIAM Review, 56(4):625–641, 2014. accepted manuscript

Software

Maintainer
  • chunkie A MATLAB package for integral equations in two dimensions.
  • optdmd A MATLAB package for computing optimized dynamic mode decompositions.
Contributor
  • fmm2d A Fortran package with wrappers in higher level languages for fast multipole calculations in two dimensions.
  • FMM3D A Fortran package with wrappers in higher level languages for fast multipole calculations in three dimensions.
  • fmm3dbie A Fortran package with wrappers in higher level languages for solving integral equations in three dimensions.

Grad Students

Plain Academic