Kyle T. Mandli

Applied Physics and Applied Mathematics

Kyle Mandli is an associate professor of applied mathematics whose research interests involve the computational and analytical aspects of geophysical shallow mass flows such as tsunamis, debris-flow, and storm-surge. 

  • Research associate, University of Texas at Austin, 2013-2014
  • JTO Fellow, University of Texas at Austin, 2012-2013
  • ICES Postdoctoral Fellow, University of Texas at Austin, 2011-2012
  • Assistant professor of applied physics and applied mathematics, Columbia University, 2014 – 
  • All citations
  • “Baysian inference of earthquake parameters from buoy data using a polynomial chaos-based surrogate.” Giraldi, L., Le Maˆıtre, O. P, Mandli, K.T., Dawson, C.N., Hoteit, I., Knio, O.M. Comput Geosci 50, 117 (2017).
  • “Clawpack: building an open source ecosystem for solving hyperbolic PDEs”, Kyle T. Mandli, Aron J. Ahmadia, Marsha J. Berger, Donna A. Calhoun, David L. George, Yiannis Had-jimichael, David I. Ketcheson, Gray I. Lemoine, and Randall J. LeVeque. PeerJ Comput. Sci. 2, e68 (2016).
  • “Visualizing Uncertainties in a Storm Surge Ensemble Data Assimilation and Forecasting Sys-tem”, Thomas Hllt, M. Umer Altaf, Kyle T. Mandli, Markus Hadwiger, Clint N. Dawson, and Ibrahim Hoteit. Natural Hazards 120 (2015).
  • “Uncertainty quantification and inference of Mannings friction coefficients using DART buoy data during the Thoku tsunami.” Sraj, I., Mandli, K. T., Knio, O. M., Dawson, C. N. and Hoteit, I., Ocean Modelling, 83, 8297 (2014).
  • “Adaptive Mesh Refinement for Storm Surge”, Kyle T. Mandli, Clint N. Dawson, Ocean Mod-elling, Volume 75, March 2014, Pages 36-50.
  • “Forestclaw: Hybrid forest-of-octrees AMR for hyperbolic conservation laws”, Carsten Burstedde, Donna Calhoun, Kyle Mandli, and Andy R. Terrel. Accepted to ParCo 2013.
  • “A Numerical Method for the Multilayer Shallow Water Equations with Dry States”, Kyle T. Mandli., Ocean Modelling, 72, 8091 (2013).
  • “ManyClaw: Slicing and dicing Riemann solvers for next generation highly parallel architec-tures”, A.R. Terrel and K. T. Mandli, TACC-Intel Symposium on Highly Parallel Architectures (2012).
  • “PyClaw: Accessible, Extensible, Scalable Tools for Wave Propagation Problems”, David I. Ketcheson, Kyle T Mandli, Aron Ahmadia, Amal Alghamdi, Manuel Quezada, Matteo Parsani, Matthew G. Knepley, and Matthew Emmett. SIAM J. Sci. Comput., 34(4), C210C231, (2012).
  • “The GeoClaw software for depth-averaged flows with adaptive refinement”, M.J. Berger, D.L. George, R.J. LeVeque and K. T. Mandli. Advancement in Water Resources, Volume 34, Issue 9, Pages 1195-1206, September 2011.