Cristóbal Quiñinao ● Profesor Asociado

[vc_section el_class="container mx-auto align-items-center circle--pattern" css=".vc_custom_1648956589196{padding-top: 3rem !important;}"][vc_row el_class="pb-5"][vc_column][vc_wp_custommenu nav_menu="6"][uoh_breadcrumb_component automatic_breadcrumb="true"][uoh_title_component title_dropdown="big" title_decorator="true"]{{title}}[/uoh_title_component][vc_column_text css=""]Métodos basados en representaciones neuronales implícitas están empezando a usarse ampliamente en distintos ámbitos de visión computacional, robótica y sensado remoto. Este tipo de representaciones están permitiendo abordar múltiples problemas en ambientes no controlados como la agricultura, de manera robusta. Por ejemplo, métodos basados en Neural Radiance Fields (NeRF) se están explorando de manera amplia tanto con imágenes satelitales como en problemas de robótica de campo. En este contexto, el proyecto busca aunar competencias en visión computacional y aprendizaje de máquinas, usadas en la detección remota y en robótica, para abordar nuevas técnicas basadas en representaciones neuronales implícitas, para aplicaciones de la agricultura de precisión. Para lograr este objetivo, los investigadores convocados tienen un profundo conocimiento en estas áreas complementarias. Es importante destacar que las áreas de sensado remoto (satelital y drones) y sensado próximo (robots y redes de sensores) están experimentando una aceleración sin precedentes. En el caso de sensado remoto, además de los grandes programas públicos como Sentinel, los actores privados están creando flotas de microsatélites capaces de vigilar la Tierra con revisitas diarias. Estos datos abundantes, baratos y de alta resolución están creando oportunidades para desarrollar aplicaciones novedosas para la supervisión de la actividad agrícola. En el caso del sensado próximo, las redes de sensores, junto con el uso de robots para monitoreo, está permitiendo un seguimiento regular de los procesos agrícolas, con una alta resolución temporal y espacial, por lo que cada vez hay una mayor disponibilidad de datos, que complementan los datos obtenidos mediante sensado remoto. A nivel de uso, estas tecnologías se complementan, y a nivel de investigación, las técnicas utilizadas están empezando a converger, mediante el uso de métodos basados en redes neuronales, y más específicamente por métodos basados en representaciones neuronales implícitas, tales como Neural Radiance Fields (NeRF). Por todo esto, el estudio del sensado remoto y próximo de manera conjunta, y mediante marcos de trabajo con técnicas similares como las representaciones neuronales implícitas, tiene un gran potencial para en un futuro próximo generar una visión integrada de los procesos agrícolas mejorando la sostenibilidad y eficiencia en la agricultura. Durante su ejecución, el proyecto llevará a cabo actividades de investigación conjunta, incluyendo seminarios online regulares, la toma de datos en terreno, y un workshop de cierre en el contexto de una conferencia internacional, que junto con el intercambio de investigadores en formación (magíster, doctorado y/o postdoctorado), así como visitas de investigadores senior, buscan articular una de red de trabajo que aborde de manera interdisciplinar y con técnicas modernas, problemáticas de sensado remoto y próximo en agricultura de precisión mediante representaciones neuronales implícitas, tales como Neural Radiance Fields (NeRF), entre otras.[/vc_column_text][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649209804184{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5"][vc_row el_class="container mx-auto align-items-center p-md-0 pt-5"][vc_column el_class="p-0"][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649210787516{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5 pb-md-5"][vc_row el_class="container mx-auto align-items-center"][vc_column][/vc_column][/vc_row][/vc_section]

[vc_section el_class="container mx-auto align-items-center circle--pattern" css=".vc_custom_1648956589196{padding-top: 3rem !important;}"][vc_row el_class="pb-5"][vc_column][vc_wp_custommenu nav_menu="6"][uoh_breadcrumb_component automatic_breadcrumb="true"][uoh_title_component title_dropdown="big" title_decorator="true"]{{title}}[/uoh_title_component][vc_column_text css=""]En este proyecto, se busca general nuevas tecnologías que permitan mejorar el manejo de recursos hídricos en la sexta región. Director de línea "Gestión de Riego Intrapredial con Inteligencia Artificial"[/vc_column_text][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649209804184{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5"][vc_row el_class="container mx-auto align-items-center p-md-0 pt-5"][vc_column el_class="p-0"][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649210787516{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5 pb-md-5"][vc_row el_class="container mx-auto align-items-center"][vc_column][/vc_column][/vc_row][/vc_section]

[vc_section el_class="container mx-auto align-items-center circle--pattern" css=".vc_custom_1648956589196{padding-top: 3rem !important;}"][vc_row el_class="pb-5"][vc_column][vc_wp_custommenu nav_menu="6"][uoh_breadcrumb_component automatic_breadcrumb="true"][uoh_title_component title_dropdown="big" title_decorator="true"]{{title}}[/uoh_title_component][vc_column_text css=""][/vc_column_text][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649209804184{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5"][vc_row el_class="container mx-auto align-items-center p-md-0 pt-5"][vc_column el_class="p-0"][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649210787516{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5 pb-md-5"][vc_row el_class="container mx-auto align-items-center"][vc_column][/vc_column][/vc_row][/vc_section]

[vc_section el_class="container mx-auto align-items-center circle--pattern" css=".vc_custom_1648956589196{padding-top: 3rem !important;}"][vc_row el_class="pb-5"][vc_column][vc_wp_custommenu nav_menu="6"][uoh_breadcrumb_component automatic_breadcrumb="true"][uoh_title_component title_dropdown="big" title_decorator="true"]{{title}}[/uoh_title_component][vc_column_text css=""]Transferencia y adopción de Tecnologías para la Gestión de Riesgo en el Proceso Productivo de la Cereza: hacia una agricultura de precisión para la Región de O’Higgins[/vc_column_text][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649209804184{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5"][vc_row el_class="container mx-auto align-items-center p-md-0 pt-5"][vc_column el_class="p-0"][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649210787516{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5 pb-md-5"][vc_row el_class="container mx-auto align-items-center"][vc_column][/vc_column][/vc_row][/vc_section]

[vc_section el_class="container mx-auto align-items-center circle--pattern" css=".vc_custom_1648956589196{padding-top: 3rem !important;}"][vc_row el_class="pb-5"][vc_column][vc_wp_custommenu nav_menu="6"][uoh_breadcrumb_component automatic_breadcrumb="true"][uoh_title_component title_dropdown="big" title_decorator="true"]{{title}}[/uoh_title_component][vc_column_text css=""]Large systems which can be described in terms of mean-field equations provide a general framework for modeling complex systems where the understanding of few collective modes cannot explain long term behavior. They frequently arise in biological applications, in particular in theoretical neuroscience. The study of mean field equations in theoretical neuroscience started long ago with integrate-and-fire systems and has been a driving force in the development of new tools and techniques in functional analysis, numerics, stochastic systems and partial differential equations. This project is placed in these mathematical fields and aims to study, for a particular kinetic equation modeling a multi-population network of FitzHugh- Nagumo interconnected neurons with chemical synapses three fundamental aspects: (1) Consistency between finite particle system and the respective limit mean field equation; (2)Qualitative properties such as existence, stability, and exponential convergence under different parameters regime; and (3) Convergence of the solutions to Dirac masses for strongly interconnectivity parameters. The particle system corresponds to a fully connected FHN neurons with synapses given by a Destexhe- Sejnowski gating model. Moreover, the channels are noisy and modeled as reflected processes. The mean field model consists of two coupled non-linear partial differential equations with unbounded coefficients, where the right-hand side includes the first moment of the unknowns. They correspond to the law of finding a neuron of each subpopulation in a particular state. The equation is obtained via the Fokker-Planck formulation, and therefore is related to a mean-field stochastic process. In this proposal, we describe our plans to get new results on consistency, existence of solutions and their stability for the aforementioned class of models. From a transdiscliplinary viewpoint, the main novelty is that in certain parameter regimes, numerical simulations on the finite system indicates that our model converges towards Dirac masses with support on a manifold where the inhibition and excitation balance condition hold true. This approach provides a novel interpretation of the balance in brain and requires the development and adaptation of new mathematical tools. Moreover, under external excitatory input, the system comes back - in a faster time scale - towards the E/I balance condition, showing high excitation activity followed by inhibition. This results is in line with important functional properties of inhibition in the brain, particularly in auditory and somatosensory cortex. This question raises a number of new mathematical problems that this proposal aims at addressing. The methods that we propose combine techniques from several fields such as stochastic processes, partial differential equations, functional analysis, viscosity solutions and numerics.[/vc_column_text][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649209804184{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5"][vc_row el_class="container mx-auto align-items-center p-md-0 pt-5"][vc_column el_class="p-0"][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649210787516{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5 pb-md-5"][vc_row el_class="container mx-auto align-items-center"][vc_column][/vc_column][/vc_row][/vc_section]

[vc_section el_class="container mx-auto align-items-center circle--pattern" css=".vc_custom_1648956589196{padding-top: 3rem !important;}"][vc_row el_class="pb-5"][vc_column][vc_wp_custommenu nav_menu="6"][uoh_breadcrumb_component automatic_breadcrumb="true"][uoh_title_component title_dropdown="big" title_decorator="true"]{{title}}[/uoh_title_component][vc_column_text css=""]Predictores socioeconómicos y psicobiológicos del desempeño académico en estudiantes de primer año de pedagogía de la UOH (Programa de Formación Inicial Docente) Clásicamente se ha descrito que el rendimiento durante la enseñanza media de los estudiantes en Chile a través del NEM y sus resultados en las pruebas de ingreso a la universidad, además un factor determinando son las condiciones socioeconómicas, que resultan ser un factor predictivo de rendimiento académico durante los primeros años de educación universitaria. Paralelamente, se ha constatado que los estudiantes a lo largo del primer semestre en la universidad sufren un deterioro en su calidad del sueño y en los hábitos alimenticios, todo relacionado con un aumento de sus niveles de estrés. Por otro lado, hipotetizamos una asociación de estos indicadores con el desempeño en pruebas de memoria de trabajo, y pueden ser elementos predictivos que determinen el desempeño académico. Nuestra investigación tiene por objetivo estudiar ciertos indicadores de higiene, tales como sueño, estrés y alimentación, con el fin de predecir su importancia en la predicción del desempeño académico. Contemplamos el uso de datos anonimizados en acuerdo con lo que establezca el comité de ética institucional. En el caso específico de estudiantes de educación básica y educación especial, determinar los principales factores que afectan el rendimiento académico, es una herramienta útil que creemos permitirá modificar ciertos modelos con el fin de mejorar los procesos de enseñanza – aprendizaje. Este estudio se enmarca en un proyecto de Fortalecimiento a la formación Inicial Docente el cual apoyará con los fondos necesarios para el buen desarrollo de esta investigación. La contribución institucional de la UOH se limita a autorizar la participación voluntaria de sus estudiantes, que se formalizará a través de la firma del consentimiento informado por cada uno de los estudiantes de forma voluntaria sin mediar recompensa ni perjuicio fruto de su decisión de colaborar en el estudio. A los estudiantes de pedagogía que voluntariamente decidan participar, se les aplicará, al inicio y al final del presente semestre académico, una encuesta online que evaluará diferentes marcadores de estrés y mediante el uso de una aplicación, se recopilará información aleatorizada de sus hábitos de alimentación y de descanso. Estos datos serán analizados considerando elementos de rendimiento en la educación media y marcadores socioeconómicos. Junto con esto, al finalizar el semestre, siempre con el consentimiento de cada participante, se solicitará al docente responsable del curso las calificaciones y nota final de todos ellos. Estos datos serán analizados cuantitativamente y de forma anonimizada. Finalmente se evaluarán todos los marcadores obtenidos, realizando un análisis cuantitativo y cualitativo, combinando métodos univariados y multivariados para evaluar estos de manera exploratoria e inferencial. Posteriormente proponemos dar punto final al estudio realizando un análisis profundo del efecto de los diferentes componentes a través de la técnica de PCA.[/vc_column_text][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649209804184{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5"][vc_row el_class="container mx-auto align-items-center p-md-0 pt-5"][vc_column el_class="p-0"][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649210787516{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5 pb-md-5"][vc_row el_class="container mx-auto align-items-center"][vc_column][/vc_column][/vc_row][/vc_section]

[vc_section el_class="container mx-auto align-items-center circle--pattern" css=".vc_custom_1648956589196{padding-top: 3rem !important;}"][vc_row el_class="pb-5"][vc_column][vc_wp_custommenu nav_menu="6"][uoh_breadcrumb_component automatic_breadcrumb="true"][uoh_title_component title_dropdown="big" title_decorator="true"]{{title}}[/uoh_title_component][vc_column_text css=""]aaaa[/vc_column_text][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649209804184{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5"][vc_row el_class="container mx-auto align-items-center p-md-0 pt-5"][vc_column el_class="p-0"][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649210787516{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5 pb-md-5"][vc_row el_class="container mx-auto align-items-center"][vc_column][/vc_column][/vc_row][/vc_section]

[vc_section el_class="container mx-auto align-items-center circle--pattern" css=".vc_custom_1648956589196{padding-top: 3rem !important;}"][vc_row el_class="pb-5"][vc_column][vc_wp_custommenu nav_menu="6"][uoh_breadcrumb_component automatic_breadcrumb="true"][uoh_title_component title_dropdown="big" title_decorator="true"]{{title}}[/uoh_title_component][vc_column_text css=""]The field of remote sensing is experiencing an unprecedented acceleration. Besides the large public programs such as Sentinel (see e.g. https://sentinel.esa.int/web/sentinel/missions/sentinel-2), private actors are creating fleets of micro-satellites capable of monitoring of the earth with daily revisits. This abundant and cheap data is creating opportunities for developing novel applications for the monitoring of industrial and agricultural activity. The automatic exploitation of this data is bound to specific application domain knowledge, which requires a mastery of advanced techniques such as computer vision and machine learning, as well as expert knowledge in the field of agriculture. To do this, the team must master earth observation satellites, be able to define the adequate mathematical detection theories, and build on a deep knowledge of satellite image processing, while also including expert knowledge in agriculture. This project aims at uniting competences across the fields of computer vision and machine learning, remote sensing to address emerging applications in agronomy. This project will in addition foster the creation of reproducible research by adopting a reproducible research methodology thus contributing the resulting algorithms to the journal Image Processing On-Line (IPOL). The IPOL journal is an initiative to establish a clear and reproducible state-of-the-art in the domain of image processing and computer vision.[/vc_column_text][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649209804184{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5"][vc_row el_class="container mx-auto align-items-center p-md-0 pt-5"][vc_column el_class="p-0"][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649210787516{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5 pb-md-5"][vc_row el_class="container mx-auto align-items-center"][vc_column][/vc_column][/vc_row][/vc_section]

[vc_section el_class="container mx-auto align-items-center circle--pattern" css=".vc_custom_1648956589196{padding-top: 3rem !important;}"][vc_row el_class="pb-5"][vc_column][vc_wp_custommenu nav_menu="6"][uoh_breadcrumb_component automatic_breadcrumb="true"][uoh_title_component title_dropdown="big" title_decorator="true"]{{title}}[/uoh_title_component][vc_column_text css=""][/vc_column_text][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649209804184{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5"][vc_row el_class="container mx-auto align-items-center p-md-0 pt-5"][vc_column el_class="p-0"][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649210787516{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5 pb-md-5"][vc_row el_class="container mx-auto align-items-center"][vc_column][/vc_column][/vc_row][/vc_section]

[vc_section el_class="container mx-auto align-items-center circle--pattern" css=".vc_custom_1648956589196{padding-top: 3rem !important;}"][vc_row el_class="pb-5"][vc_column][vc_wp_custommenu nav_menu="6"][uoh_breadcrumb_component automatic_breadcrumb="true"][uoh_title_component title_dropdown="big" title_decorator="true"]{{title}}[/uoh_title_component][vc_column_text css=""]Este proyecto de carácter nacional busca entregar un espacio en la red donde se pueda encontrar las herramientas necesarias para realizar vigilancia, pronóstico, investigación y control de la plaga emergente Drosophila suzukii. Busca articular información técnica, proyectos, artículos de investigación e investigadores. Además entrega información en tiempo real a los beneficiarios, productores, investigadores, asesores, sobre las detecciones validadas a nivel comunal.[/vc_column_text][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649209804184{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5"][vc_row el_class="container mx-auto align-items-center p-md-0 pt-5"][vc_column el_class="p-0"][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649210787516{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5 pb-md-5"][vc_row el_class="container mx-auto align-items-center"][vc_column][/vc_column][/vc_row][/vc_section]

[vc_section el_class="container mx-auto align-items-center circle--pattern" css=".vc_custom_1648956589196{padding-top: 3rem !important;}"][vc_row el_class="pb-5"][vc_column][vc_wp_custommenu nav_menu="6"][uoh_breadcrumb_component automatic_breadcrumb="true"][uoh_title_component title_dropdown="big" title_decorator="true"]{{title}}[/uoh_title_component][vc_column_text css=""]The main goal of this proposal is to study different particle systems interacting through a empirical mean term and the corresponding mean field descriptions when the number of individuals is going to infinity. In particular, we are interested in well posedness questions for those nonlinear SDEs, with coefficients depending on the law of the unknown process itself. Classically, the existence of those solutions can be addressed via propagation of chaos arguments. By using tightness arguments on the particle system solutions one can find weak solutions to the mean field nonlinear processes using the consistency of equations. In that sense, we are concerned in revisit some classical techniques and adapt them to some modern problems involving L ́evy, Hawkes and Asymmetric noisy components. Thus, we are interested in stating a new framework to englobe some applications that are not rigorously treated in literature (specially in theoretical biology, neuroscience and ecology). Mathematically speaking, the proposed methodology is quite standard. We start by well known problems and modify the proofs to attack perturbations of the seminal equations. In doing so, we will find out what are the key constraints and get some insights of the elements we need to develop in order to study the new questions stated. To fill the gaps between classic and modern applications, there are some very interesting prints stating general BDG inequalities for L ́evy processes and central limit theorems for Hawkes processes (see Proposed Research for more details). The proposed research was motivated by the final goal of having process with memory, but when Markov Property no longer apply there is no much we can solve directly. Thus, we will try to restraint first to the Markovian framework by using compactness assumptions in past/delay dependance and/or regular approximations of the functions involved in the SDEs. The goals and expected results are in particular: 1. Toy model 1: The justification of the mean-field limit process for a general model of interacting particles connected through Poisson measures. The main novelty of the equation is presence of the unknown in the size and intensity of the mean field jump part. By imposing a non mass creation hypothesis, solutions still upper bounded and the tightness method of Sznitman for proving the chaos propagation holds. 2. Toy model 2: The analysis of a model composed by a small world network of interacting particles and a large scale interaction in an open system approach. To use the coupling technique and prove the consistence between the particle system and the nonlinear process of a system driven by one (or in general a sequence) of compound Poisson process(es). This result can be done by using the arguments of Jourdain et al. 2008, in particular, by using the BDG type of inequality stated there. 3. Study numerically the shape of the invariant measures in some ecologically inspired models of type 1 and 2. This equations are naturally found by using logistic growth dynamics and competitive/cooperative interaction functions (Lotka-Volterra kind of interactions). To find resolvable toy models and prove stability of the steady states. ˆ 4. L ́evy particle system: to use the L ́evy-Ito decomposition theorem to write the randomness as the sum of a continuous part, a compound Poisson process and a square integrable pure jump part. To control the deterministic part of the dynamics by using a Lipschitz hypothesis. The stochastic components, can be treated by using classical arguments on diffusive particles, the toy-model 2 and again the BDG type of inequality of Jourdain et al. 2008. 5. Hawkes particle system: to prove an equivalence between Hawkes processes and a system of equations involving Poisson measures by using the method of Delattre et al. 2016. To solve the well posedness of the new particle system by using the arguments of the toy-model 1. By using the results of Chevallier et al. 2015 for the pure point process case, to solve our limit equation. With the well posedness of both systems, to use the consistence part of the chaoticity to conclude the convergence in law towards the mean field equation. 6. Asymmetric particle system: to use the regularity approximation of LeGall to justify the passage from an equation involving local times, to a classical diffusive equation. Solve the well-posedness and the chaos propagation questions for this new system which is an application of the classical version of the chaos property. To take the limit on the approximation functions for the new mean-field equation and study the convergence towards an asymmetric nonlinear process.[/vc_column_text][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649209804184{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5"][vc_row el_class="container mx-auto align-items-center p-md-0 pt-5"][vc_column el_class="p-0"][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649210787516{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5 pb-md-5"][vc_row el_class="container mx-auto align-items-center"][vc_column][/vc_column][/vc_row][/vc_section]