Publications by Rafael Eduardo Carrillo Rangel

Uncertainty-aware Flexibility Envelope Prediction in Buildings with Controller-agnostic Battery Models

Baptiste Schubnel, Colin Neil Jones, Rafael Eduardo Carrillo Rangel, Pierre-Jean Alet, Paul Scharnhorst

Buildings are a promising source of flexibility for the application of demand response. In this work, we introduce a novel battery model formulation to capture the state evolution of a single building. Being fully data-driven, the battery model identificat ...

IEEE2023

Interpretable temporal-spatial graph attention network for multi-site PV power forecasting

Pascal Frossard, Baptiste Schubnel, Rafael Eduardo Carrillo Rangel, Pierre-Jean Alet, Jelena Simeunovic

Accurate forecasting of photovoltaic (PV) and wind production is crucial for the integration of more renewable energy sources into the power grid. To address the limited resolution and costs of methods based on numerical weather predictions (NWP), we take ...

ELSEVIER SCI LTD2022

A real-time optimal inverse planning for Gamma Knife radiosurgery by convex optimization: description of the system and first dosimetry data

Jean-Philippe Thiran, Rémi Charrier, Rafael Eduardo Carrillo Rangel

OBJECTIVE The authors developed a new, real-time interactive inverse planning approach, based on a fully convex framework, to be used for Gamma Knife radiosurgery. ...

AMER ASSOC NEUROLOGICAL SURGEONS2018

A Fourier dimensionality reduction model for big data interferometric imaging

Jean-Philippe Thiran, Yves Wiaux, Rafael Eduardo Carrillo Rangel, Vijay Kartik

Data dimensionality reduction in radio interferometry can provide savings of computational resources for image reconstruction through reduced memory footprints and lighter computations per iteration, which is important for the scalability of imaging method ...

Oxford Univ Press2017

Fourier dimensionality reduction of radio-interferometric data

Jean-Philippe Thiran, Yves Wiaux, Rafael Eduardo Carrillo Rangel, Vijay Kartik

Next-generation radio-interferometers face a computing challenge with respect to the imaging techniques that can be applied in the big data setting in which they are designed. Dimensionality reduction can thus provide essential savings of computing resourc ...

2017

Ultrafast ultrasound imaging as an inverse problem: Matrix-free sparse image reconstruction

Jean-Philippe Thiran, Yves Wiaux, Dimitris Perdios, Adrien Georges Jean Besson, Rafael Eduardo Carrillo Rangel, Florian Martinez, Marcel Arditi

Conventional ultrasound (US) image reconstruction methods rely on delay-and-sum (DAS) beamforming, which is a relatively poor solution of the image reconstruction problem. An alternative to DAS consists in using iterative techniques which require both an a ...

2017

A compressed-sensing approach for ultrasound imaging

Jean-Philippe Thiran, Yves Wiaux, Dimitris Perdios, Adrien Georges Jean Besson, Rafael Eduardo Carrillo Rangel, Marcel Arditi

Ultrasonography uses multiple piezo-electric element probes to image tissues. Current time-domain beamforming techniques require the signal at each transducer-element to be sampled at a rate higher than the Nyquist criterion, resulting in an extensive amou ...

2017

Robust sparse image reconstruction of radio interferometric observations with PURIFY

Yves Wiaux, Jason Douglas McEwen, Rafael Eduardo Carrillo Rangel

Next-generation radio interferometers, such as the Square Kilometre Array (SKA), will revolutionise our understanding of the universe through their unprecedented sensitivity and resolution. However, to realise these goals significant challenges in image an ...

OUP2016

A compressed beamforming framework for ultrafast ultrasound imaging

Jean-Philippe Thiran, Yves Wiaux, Olivier Bernard, Dimitris Perdios, Adrien Georges Jean Besson, Rafael Eduardo Carrillo Rangel, Marcel Arditi

Classical beamforming methods, based on Delay- And-Sum (DAS) require an extensive number of samples and delay calculations to obtain high-quality images. Compressed Beamforming (CB) proposes an alternative to DAS, based on compressed sensing, which aims at ...

Ieee2016

Morphological component analysis for sparse regularization in plane wave imaging

Jean-Philippe Thiran, Yves Wiaux, Dimitris Perdios, Adrien Georges Jean Besson, Rafael Eduardo Carrillo Rangel, Marcel Arditi, Eric Bezzam

Classical ultrasound image reconstruction mainly relies on the well-known delay-and-sum (DAS) beamforming for its simplicity and real-time capability. Sparse regularization methods propose an alternative to DAS which lead to a better inversion of the ill-p ...

Ieee2016

Sparse regularization methods in ultrafast ultrasound imaging

Jean-Philippe Thiran, Yves Wiaux, Olivier Bernard, Adrien Georges Jean Besson, Rafael Eduardo Carrillo Rangel

Ultrafast ultrasound (US) imaging based on plane wave (PW) insonification is a widely used modality nowadays. Two main types of approaches have been proposed for image reconstruction either based on classical delay-and-sum (DAS) or on Fourier reconstructio ...

Ieee2016

Robust compressive sensing of sparse signals: A review

Rafael Eduardo Carrillo Rangel, Alonso Ramirez Manzanares

Compressive sensing generally relies on the L2-norm for data fidelity, whereas in many applications robust estimators are needed. Among the scenarios in which robust performance is required, applications where the sampling process is performed in the prese ...

Springer International Publishing Ag2016

iNVESTIGA: Connecting the Colombian Scientific Diaspora with Secondary Schools in Colombia

Rafael Eduardo Carrillo Rangel, Ricardo Alberto Corredor Jerez

According to recent studies, Latin America is the region with the highest emigration rate in the world, specially affecting the highly educated population. One of the consequences of this process is the expansion of business and scientific diasporas. Colom ...

2016

Scalable splitting algorithms for big-data interferometric imaging in the SKA era

Jean-Philippe Thiran, Yves Wiaux, Jason Douglas McEwen, Rafael Eduardo Carrillo Rangel

In the context of next generation radio telescopes, like the Square Kilometre Array, the efficient processing of large-scale datasets is extremely important. Convex optimisation tasks under the compressive sensing framework have recently emerged and provid ...

OUP2016

A sparse reconstruction framework for Fourier-based plane wave imaging

Jean-Philippe Thiran, Yves Wiaux, Olivier Bernard, Adrien Georges Jean Besson, Rafael Eduardo Carrillo Rangel

Ultrafast imaging based on plane-wave (PW) insonification is an active area of research due to its capability of reaching high frame rates. Among PW imaging methods, Fourier-based approaches have demonstrated to be competitive compared to traditional delay ...

Ieee-Inst Electrical Electronics Engineers Inc2016

A randomised primal-dual algorithm for distributed radio-interferometric imaging

Yves Wiaux, Jason Douglas McEwen, Rafael Eduardo Carrillo Rangel

Next generation radio telescopes, like the Square Kilometre Array, will acquire an unprecedented amount of data for radio astronomy. The development of fast, parallelisable or distributed algorithms for handling such large-scale data sets is of prime impor ...

Ieee2016

Extension of ultrasound Fourier slice Imaging theory to sectorial acquisition

Jean-Philippe Thiran, Olivier Bernard, Adrien Georges Jean Besson, Rafael Eduardo Carrillo Rangel

Ultrasound image reconstruction from the echoes received by an ultrasound probe after the transmission of diverging waves is an active area of research because of its capacity to insonify at ultra-high frame rate with large regions of interest using small ...

2015

Dimension embedding for big data in radio interferometry

Yves Wiaux, Rafael Eduardo Carrillo Rangel, Vijay Kartik

As radio telescope data is now increasingly high-dimensional, data reduction has become essential to reduce computational load while preserving accurate signal reconstruction. Gridding the continuous Fourier visibilities represents the standard approach to ...

2015

Why CLEAN when you can PURIFY? A new approach for next-generation radio-interferometric imaging

Yves Wiaux, Jason Douglas McEwen, Rafael Eduardo Carrillo Rangel

In recent works, sparse models and convex optimization techniques have been applied to radio-interferometric (RI) imaging showing the potential to outperform state-of-the-art imaging algorithms in the field. In this talk, I will review our latest contribut ...

2015

A sparse regularization approach for ultrafast ultrasound imaging

Jean-Philippe Thiran, Yves Wiaux, Olivier Bernard, Adrien Georges Jean Besson, Rafael Eduardo Carrillo Rangel

Ultrafast imaging based on plane-wave (PW) in- sonification is an active area of research due to its capability of reaching high frame rates. Several approaches have been proposed either based on either of Fourier-domain reconstruction or on delay-and-sum ...

IEEE2015