Jayanth Mohan Jagalur profile

Jayanth Mohan Jagalur

Research Scientist

COMP / CASC DIV / Center for Applied Scientific Computing Division

Email

Biography

My interests lie at the intersection of physical modeling with statistical inference, machine learning and computation. In particular I develop methodologies for Uncertainty Quantification, Data Assimilation, Bayesian computation, and experimental design. My work is motivated by a wide variety of engineering problems, including remote sensing, geophysics, material science with a focus on additive manufacturing. I received my MS. and PhD degrees from RPI ,and spent several years at MIT as a researcher before moving to CASC at the LLNL.

Education

  • Ph.D., Computational Science & Engineering, RPI
  • M.S., Applied Mathematics, RPI

Publications

2024 2 publications

  • Optimal experimental design: formulations and computation, Acta Numerica, 2024. HTTPS://DOI.ORG/10.1017/S096249292400002

  • Evaluating the accuracy of Gaussian approximations in VSWIR imaging spectroscopy retrievals, IEEE Transactions on Geoscience and Remote Sensing, 2024. HTTPS://DOI.ORG/10.1109/TGRS.2024.3411916

2021 1 publication

  • Batch greedy maximization of non-submodular functions: Guarantees and applications to experimental design, Journal of Machine Learning Research, 2021. HTTPS://JMLR.ORG/PAPERS/V22/20-1023.HTML

2018 1 publication

  • Inferring fault frictional and reservoir hydraulic properties from injection induced seismicity, Geophysical Research Letters, 2018. DOI:10.1002/2017GL075925

2017 1 publication

  • Stochastic variational multiscale analysis of the advection diffusion equation: Advective diffusive regime and multi-dimensional problems, Computer Methods in Applied Mechanics and Engineering, 2017. DOI:10.1016/J.CMA.2017.07.013

2015 1 publication

  • Approximate optimal projection for reduced-order models, International Journal for Numerical Methods in Engineering, 2015. DOI:10.1002/NME.4963

2014 1 publication

  • Variational multiscale analysis: The fine scale Green’s functions for stochastic partial differential equations, SIAM/ASA Journal on Uncertainty Quantification, 2014. DOI:10.1137/130940359

2013 1 publication

  • A Galerkin least squares method for time-harmonic Maxwell equations using Nédélec elements, Journal of Computational Physics, 2013. DOI:10.1016/J.JCP.2012.10.003

2009 1 publication

  • A computational technique to optimally design in-situ diffractive elements: applications to projection lithography at the resist resolution limit, Proceedings of SPIE, 2009. DOI:10.1117/12.814251