CONTACT INFORMATION
Tel: Use my personal phone number.
email: rdelgadillo0000@gmail.com
Linkedin: (17) デルガディージョリカルド | LinkedIn/ (Link)
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Education:
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University of California San Diego (2006-2010)
-B.A. Pure Mathematics with a minor in physics
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University of California Santa Barbara (2010-2016)
-MA Applied Mathematics, 2012
-Ph.D. Applied Mathematics 2016
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Doctoral Advisor: Xu Yang (UC Santa Barbara)
Employment:​
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Current: Senior Algorithm Developer and Mathematician specializing in Computer Vision, Deep Learning for Computer Vision, Graphics Programming, Simulations and Control systems. Job Location: Santa Barbara.
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Research Fellow at National University of Singapore: Civil and Enviornmental
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engineering Department, April 30, 2020.
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Research Fellow at National University of Singapore: Mathematics Department, August 2019
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Postdoctoral researcher at Michigan State University mathematics department, August 2016.
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Current Interest:
Computer Vision and Multiscale Computer Vision Algorithms. Electronic and Computer Engineering.
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Areas of Research:
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Applied mathematics and scientific computing. Asymptotic analysis and semiclassical approximations in quantum mechanics. Time-dependent density functional theory. PDE discovery algorithms and Machine Learning. Bridging Machine Learning and Asymptotic Analysis.
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Published, Submitted Papers and Preprints
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(1) Frozen Gaussian approximation for high frequency wave propagation in periodic media with Jianfeng Lu and Xu Yang, Journal of Asymptotic Analysis, 110, 113--135, 2018.
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(2) Gauge-invariant frozen Gaussian approximation method for the Schrodinger equation with periodic potentials with Jianfeng Lu and Xu Yang,
Siam J. Sci. Comp, 38, A2440--A2463, 2016.
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(3) Frozen Gaussian approximation-based artificial boundary conditions for one-dimensional nonlinear Schrodinger equation in the semiclassical regime with Jiwei Zhang and Xu Yang, Siam J. Sci. Comp, 75, 1701--1720, 2018.
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(4) A Spectral Algorithm for the Time-Dependent Kohn-Sham Equations Based on Frozen Gaussian Approximations with Di Liu, submitted to SISC, 2018. Accepted.
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(5) Multiscale and nonlocal learning for PDE's using densely connected RNNs (Recuring Neural Networks) with Jingwei Hu and Yang Haizhao. Submitted.
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