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---
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title: "Eduardo Cueto-Mendoza"
image: "images/author.jpg"
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description: "Author introduction"
sidebar: true
widgets: ["recommended","categories"]
draft: false
---
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Hello, I'm Eduardo. Currently, pursuing a PhD in Computer Science. Some places where I have previously worked are: Intel, InfolinkEXP, and Indboo, as an AI engineer.
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My current interests are optimization (combinatorial, convex, etc), neural networks (NN), and systems programming.
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> Current research on Neural Networks does not consider parameter other than the accuracy obtained by the model on unknown data.
Currently I am working on unraveling the relationships that exists between several hyper-parameters of NN's. Current research on this area does not consider this type of hyper-parameters: network size, energy consumed, time, fitting methodology, etc.
there is research where those parameters are taken into account, but they are only presented as information, there is no real attempt to use those parameters as a guideline (or model) to produce a training/inference methodology that can optimize any of the parameters being studied.