{"version":"1.0","provider_name":"DEPARTAMENTO DE INGENIER\u00cdA EL\u00c9CTRICA","provider_url":"https:\/\/www.ing.uc.cl\/electrica","title":"Charla de postgrado - DEPARTAMENTO DE INGENIER\u00cdA EL\u00c9CTRICA","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"2V4SkqnVjs\"><a href=\"https:\/\/www.ing.uc.cl\/electrica\/2026\/04\/23\/charla-de-postgrado-34\/\">Charla de postgrado<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/www.ing.uc.cl\/electrica\/2026\/04\/23\/charla-de-postgrado-34\/embed\/#?secret=2V4SkqnVjs\" width=\"600\" height=\"338\" title=\"&#8220;Charla de postgrado&#8221; &#8212; DEPARTAMENTO DE INGENIER\u00cdA EL\u00c9CTRICA\" data-secret=\"2V4SkqnVjs\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script>\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),o=l.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),c=new RegExp(\"^https?:$\",\"i\"),i=0;i<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener(\"message\",d.wp.receiveEmbedMessage,!1),l.addEventListener(\"DOMContentLoaded\",function(){for(var e,t,s=l.querySelectorAll(\"iframe.wp-embedded-content\"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute(\"data-secret\"))||(t=Math.random().toString(36).substring(2,12),e.src+=\"#?secret=\"+t,e.setAttribute(\"data-secret\",t)),e.contentWindow.postMessage({message:\"ready\",secret:t},\"*\")},!1)))}(window,document);\n\/\/# sourceURL=https:\/\/www.ing.uc.cl\/electrica\/wp-includes\/js\/wp-embed.min.js\n<\/script>\n","thumbnail_url":"https:\/\/www.ing.uc.cl\/electrica\/wp-content\/uploads\/2026\/04\/11.png","thumbnail_width":1086,"thumbnail_height":1448,"description":"El pasado mi\u00e9rcoles 22 de Abril, se realiz\u00f3 un anueva charla. Una nueva charla de postgrado se realiz\u00f3 el pasado mi\u00e9rcoles en la sala de clases de nuestro departamento, en esta ocasi\u00f3n Javier Bisbal Z., alumno de Doctorado del \u00e1rea Sistemas de Informaci\u00f3n, profesor(a) supervisor(a) Cristi\u00e1n Tejos present\u00f3 el trabajo titulado &#8220;Enhancing Hemodynamic Quantification in 4D Flow MRI Using Deep Learning&#8221;. Abstract:\u00a0Four-dimensional flow magnetic resonance imaging, or 4D flow MRI, provides time-resolved three-dimensional velocity fields within a volumetric anatomic region of interest. In vascular imaging, this technique enables the assessment of advanced hemodynamic markers that can improve the characterization of vascular diseases. However, its broader clinical use remains limited by low spatiotemporal resolution, measurement noise, and time-consuming, user-dependent post-processing workflows. In this talk, I will present innovative deep learning approaches designed to enhance 4D flow MRI data and automate key post-processing tasks. In particular, I will show how deep reinforcement learning, uncertainty-awar U-Net models, and physics-informed machine learning can incorporate human-inspired processing, data-specific uncertainty, and blood-flow physics to achieve more robust, reliable, and efficient 4D flow MRI post-processing. Tambi\u00e9n present\u00f3 Joaqu\u00edn La Rosa, alumno de Doctorado del \u00e1rea Energ\u00eda, profesor(a) supervisor(a) David Watts cuyo trabajo se titul\u00f3 &#8220;Un enfoque de Opciones Reales para la gesti\u00f3n del fin de vida de activos e\u00f3licos en un marco de Econom\u00eda Circular&#8221;. Abstract:\u00a0Ante el envejecimiento masivo de los primeros activos e\u00f3licos, la industria enfrenta el desaf\u00edo de gestionar su desmantelamiento no como un gasto inevitable de cierre, sino como una oportunidad de recuperaci\u00f3n de capital. Esta investigaci\u00f3n aborda la rigidez de los m\u00e9todos de valoraci\u00f3n tradicionales, los cuales ignoran la volatilidad del mercado el\u00e9ctrico y el valor din\u00e1mico de los componentes reciclables. Se propone un modelo basado en Opciones Reales para valorar la flexibilidad de posponer el cierre hasta que las condiciones sean \u00f3ptimas. Al integrar la Econom\u00eda Circular, el modelo transforma el retiro en una decisi\u00f3n estrat\u00e9gica que captura el m\u00e1ximo valor residual y mitiga riesgos para el operador."}