Design computational algorithms for estimating the physicochemical properties of cocoa using selectednear-infrared spectral bands and Deep Learning algorithms.

Responsibilities include:

• Analyze and mathematically model the estimation of physicochemical properties and classification ofmaterials using spectral images and deep learning, within the framework of cocoa beans.
• Obtaining and organising the multispectral cocoa image database.
• Analyze and mathematically model a neural network to obtain the most significant bands in the nearinfrared for the estimation of the physicochemical properties of cocoa.

Achievement: Construction of a low-cost multispectral images camera to analyze the quality of Cocoa.

Professional R&D internship to develop an algorithm for wood-sand differentiation in drone imagery.

Responsibilities include:

• Data cleaning using the Fast Fourier Transform in the Matlab platform.
• Construction of the algorithm for obtaining the physical characteristics of wood and sand.
  

Achievement: Design and implementation of an algorithm with the objective of differentiating wood from sand on the beach of Puerto Velero, Colombia.

Volunteering to develop a protection system against COVID-19.

Responsibilities include:

• Mechanical design of the automatic cabin.
• Design and simulation of the electrical system using PROTEUS.
• Construction of the electronic system.

Achievement: Design and implementation of an automatic booth for the protection of people from COVID-19.

Research project to develop an algorithm for encoding car number plates in Special Topics in Optics.

Responsibilities include:

• Data cleaning using the Fast Fourier Transform in the Matlab platform.
• Development of an interactive application in Matlab to obtaincar number plate digits.

Achievement: Development of an algorithm to improve vehicle number plate resolutions.

R&D internship grant to implementan otitis classification algorithm.

Responsibilities include:

• Obtaining and organising the database using a digital otoscope and Matlab.
• Development of a mathematical model to obtain intrinsic characteristic of Otitis images.
• Creation of neural networks in Matlab to differentiate the different types of Otitis.Achievement: Implementation of an algorithm to differentiate between viral and bacterial otitis.
  

Achievement: Implementation of an algorithm to differentiate between viral and bacterial otitis.

Research project to develop an orchid classification algorithm using Digital Image Processing.

Responsibilities include:

• Obtaining and organising the Orchid database using a Sonic Camera, Microsoft Excel and Matlab.
• Creation of neural networks in Matlab to classify orchids.