Logo

Instituto de Ingeniería Matemática y Computacional

Facultad de Matemáticas - Escuela de Ingeniería

Actividades

El encuentro, que se realiza en el marco del Día Internacional de la Mujer en Matemáticas (12/5), busca visibilizar la labor de las mujeres en el área, con el fin de que su trabajo sirva de motivación e inspiración para estudiantes de pregrado y postgrado que estén interesados/as en seguir una carrera de investigación en esta área.

El evento contará con la participación de investigadoras nacionales e internacionales que ofrecerán charlas, plenarias y cursillos. Los contenidos de estas actividades están relacionados con diversas áreas afines a las matemáticas, incluyendo álgebra, física matemática, geometría, sistemas dinámicos, matemáticas aplicadas y educación matemática.

Fecha: 10 al 12 de mayo.

Sedes: Universidad Católica (Campus San Joaquín); Universidad de Santiago de Chile (Usach), Universidad de Chile.

Instituciones organizadoras: Centro de Modelamiento Matemático (CMM), Facultad de Matemáticas UC, Instituto de Ingeniería Matemática y Computacional (IMC), Universidad de Chile, Universidad de Santiago de Chile. 

Para más información, hacer clic aquí

 

Gianluca Iaccarino, Director, Institute for Computational Mathematical Engineering (ICME). Professor, Mechanical Engineering Department, Stanford University. 

Lunes 28 de noviembre de 2022, 13 hrs. (Presencial en Auditorio San Agustín).

ABSTRACT

The Institute for Computational and Mathematical Engineering (ICME) at Stanford University is an interdisciplinary graduate program (granting Masters and PhDs) at the intersection of mathematics, computing, and science and engineering. ICME was established in 2004, is part of Stanford School of Engineering and provides a link between fundamental mathematics/statistical sciences, computer science and engineering applications. In ICME:

  • We design state-of-the-art mathematical and computational models, methods and algorithms.
  • We collaborate closely with engineers and scientists in academia and industry to develop improved computational approaches and advance disciplinary fields.
  • We train students and scholars in mathematical modeling, scientific computing and advanced computational algorithms.

In this talk I will give an overview of ICME, and give examples of recent research activities highlighting ICME students.

Link de inscripción: https://forms.gle/YcQYNVfWvMr4end29 

Clement Lezane, University of Twente. 

Viernes 14 de octubre de 2022, 13 hrs. (Presencial en Auditorio San Agustín; Link Zoom disponible escribiendo a Esta dirección de correo electrónico está siendo protegida contra los robots de spam. Necesita tener JavaScript habilitado para poder verlo.)

ABSTRACT

Inspired by regularization techniques in statistics and machine learning, we study complementary composite minimization in the stochastic setting. This problem corresponds to the minimization of the sum of a (weakly) smooth function endowed with a stochastic first-order oracle, and a structured uniformly convex (possibly nonsmooth and non-Lipschitz) regularization term. Despite intensive work on closely related settings, prior to our work no complexity bounds for this problem were known. We close this gap by providing novel excess risk bounds, both in expectation and with high probability. Our algorithms are nearly optimal, which we prove via novel lower complexity bounds for this class of problems. We conclude by providing numerical results comparing our methods to the state of the art.

 

Rodrigo Carrasco, Departamento de Ingeniería Industrial y de Sistemas e Instituto de Ingeniería Matemática y Computacional, Pontificia Universidad Católica de Chile.

Miércoles 28 de septiembre de 2022, 13 hrs. (Presencial en Auditorio San Agustín; Link Zoom disponible escribiendo a Esta dirección de correo electrónico está siendo protegida contra los robots de spam. Necesita tener JavaScript habilitado para poder verlo.)

ABSTRACT

This work presents a novel approach to scheduling storage units in a photovoltaic generation system based on stochastic optimization. A common approach to take advantage of historical data for stochastic optimization has been to use machine learning techniques to compute relevant scenarios. Instead of this “predict THEN optimize” strategy, we show that using a combined “predict AND optimize” approach results in better recommendations. The resulting scenarios capture the relevant effects on the decision process and not just data features. We show experimental results applied to a real-life control system with limited computation capacity and further validate our results by testing the resulting schedules in an actual prototype.

Carlos Spa, Computer Applications in Science and Engineering (CASE) Department, Barcelona Supercomputing Center (BSC-CNS). 

Miércoles 19 de octubre de 2022, 13 hrs. (Presencial en Auditorio San Agustín; Link Zoom disponible escribiendo a Esta dirección de correo electrónico está siendo protegida contra los robots de spam. Necesita tener JavaScript habilitado para poder verlo.)

ABSTRACT

Room acoustics is the science concerned to study the behavior of sound waves in enclosed rooms. The acoustic information of any room, the so-called impulse response, is expressed in terms of the acoustic field as a function of space and time. In general terms, it is nearly impossible to find analytical impulse responses of real rooms. Therefore, in recent years, the use of computers for solving this type of problems has emerged as a proper alternative to calculate these responses. In this talk, we focus on the analysis of the wave-based methods in the time-domain. More concretely, we study in detail the main formulations of Finite-Difference methods, which have been widely used in many room acoustics applications, and the recently proposed Fourier Pseudo-Spectral methods. Both methods are studied and compared in the three different contexts: the wave propagation, the source generation and the locally reacting boundary conditions.