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Paul Louis Escapil-Inchauspé Arnaud

Researcher

INRIA Chile

Las Condes, Chile

Líneas de Investigación


My topics of interest include Computational Mathematics, Deep Learning, and High Performance computing.

Educación

  •  Civil Engineering, PONTIFICIA UNIVERSIDAD CATOLICA DE CHILE. Chile, 2021
  •  Engineering, PONTIFICIA UNIVERSIDAD CATOLICA DE CHILE. Chile, 2016
  •  Engineering, Centrale Nantes. Francia, 2015

Experiencia Académica

  •   Data Science Engineer and Associate Researcher Full Time

    Fundación Data Observatory

    Chile

    2022 - 2024

  •   Postdoctoral Fellow Full Time

    UNIVERSIDAD ADOLFO IBANEZ

    Chile

    2021 - 2023

  •   Researcher Full Time

    INRIA CHILE

    Chile

    2024 - A la fecha

Experiencia Profesional

  •   Founder Part Time

    Yachay Group

    Chile

    2020 - A la fecha

  •   Co-founder Part Time

    bow.care

    Chillán, Chile

    2023 - A la fecha


 

Article (9)

Physics-Informed Neural Networks for Coupled Fluid Dynamics and Nutrient Transport: A Comparative Study of Causal Training Methods

Chacra, Emir; Escapil-Inchauspe, Paul; Marti, Luis; Sanchez-Pi, Nayat; IEEE

Article ISI
2025 15TH IEEE INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION SYSTEMS, ICPRS  (2025)

Shape Uncertainty Quantification for Electromagnetic Wave Scattering via First-Order Sparse Boundary Element Approximation

Escapil-Inchauspe, Paul; Jerez-Hanckes, Carlos

Article ISI SCOPUS
IEEE Transactions on Antennas and Propagation  (2024)

h-Analysis and data-parallel physics-informed neural networks



Article ISI SCOPUS
Scientific Reports  (2023)

Hyper-parameter tuning of physics-informed neural networks: Application to Helmholtz problems

Escapil-Inchauspe, Paul; Ruz, Gonzalo A.

Article ISI SCOPUS
Neurocomputing  (2023)

Accelerated Calderon preconditioning for Maxwell transmission problems

Kleanthous, Antigoni; Hewett, David P.; Baran, Anthony J.

Article ISI SCOPUS
Journal of Computational Physics  (2022)

Local Multiple Traces Formulation for electromagnetics: Stability and preconditioning for smooth geometries

Ayala, Alan; Claeys, Xavier; Escapil-Inchauspe, Paul; Jerez-Hanckes, Carlos

Article ISI SCOPUS
Journal of Computational and Applied Mathematics  (2022)

Bi-parametric operator preconditioning



Article ISI SCOPUS
Computers and Mathematics with Applications  (2021)

Helmholtz Scattering by Random Domains: First-Order Sparse Boundary Elements Approximation



Article ISI SCOPUS
SIAM Journal on Scientific Computing  (2020)

Fast Calderon Preconditioning for the Electric Field Integral Equation

Escapil-Inchauspé P.

Article ISI SCOPUS
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION  (2019)

Errata (1)

Author Correction: h-Analysis and data-parallel physics-informed neural networks (Scientific Reports, (2023), 13, 1, (17562), 10.1038/s41598-023-44541-5)

escapil-inchauspe; P.; Ruz; G.A.

Errata SCOPUS
Scientific Reports  (2024)

Proyecto (1)

UNCERTAINTY QUANTIFICATION IN PHYSICS-INFORMED NEURAL NETWORKS WITH APPLICATIONS

Paul Louis Escapil-Inchauspé Arnaud

Proyecto
 (2023)

2
Carlos Jerez

Dean, Full Professor

Faculty of Engineering and Sciences

Universidad Adolfo Ibánez

Santiago, Chile

1
Gonzalo Ruz

Full Professor

Engineering and Sciences

Universidad Adolfo Ibáñez

Santiago, Chile

18
Paul Escapil-Inchauspé

Researcher

INRIA Chile

Las Condes, Chile