PERSONALWEB PAGE
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ABOUT

PERSONAL DETAILS
Campus Las Lagunillas s/n, A3-102, 23071, Jaén
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allopezr@ujaen.es
+34 953213356
Welcome to my academic profile Available as freelance

BIO

ABOUT ME

I received the B.Sc. degree in Computer Science and M.Sc. degree in Computer Science from the University of Jaén in 2019 and 2020, respectively. I was the recipient of a doctoral grant from the Spanish Ministry of Science, Innovation and Universities in 2020 (FPU19). Therefore, I am currently a Predoctoral Fellow and Professor at the University of Jaén. My research interests include fields in computer graphics such as GPU computing, rendering techniques, geometric algorithms or image processing, as well as the fusion and applications of Remote Sensing data from real-world environments. I was also the recipient of the Award of Best Bachelor Thesis by the Center for Advanced Studies in Information and Communication Technologies (CEATIC in Spanish).

HOBBIES

INTERESTS

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FACTS

FACTS ABOUT ME

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RESUME

EDUCATION
  • 2020
    -

    Computer Science PhD

    University of Jaén

    PhD program on Information and Communication Technologies.
  • 2019
    2020

    Computer Science Master

    University of Jaén

    Master of Science mainly focused on Management and Government of IT projects as well as Artificial Intelligence algorithms and tools. I passed 8 subjects out of 11 (including my Master Thesis) with honors and an average mark of 9.88.
  • 2015
    2019

    Computer Science Degree

    University of Jaén

    Degree of Computer Science specialized on Communication and Information Technologies as well as Graphic Systems. I passed 24 subjects with honors (including my Bachelor Thesis) and an average mark of 9.29.
ACADEMIC FELLOWSHIPS
  • 2020
    -

    Predoctoral Fellowship (FPU)

    Graphics and Geomatic Group. University of Jaén

    Doctoral grant from the Spanish Ministry of Science, Innovation and Universities for the acquisition of Ph.D. title and university teaching skills in the area of Computer Science and Information Technology.
  • 2019
    2020

    Research education grant

    Graphics and Geomatic Group. University of Jaén

    Research contract to collaborate with the Computer Science department at the University of Jaén on a research project entitled '3D scanning simulation'.
  • 2019
    2020

    Acción 3. Research initiation

    Graphics and Geomatic Group. University of Jaén

    Grant of excellence from University of Jaén to retain and recruit talent. Collaboration with the Computer Science department at the University of Jaén on a research project.
  • 2018
    2019

    Collaboration with University departments

    Graphics and Geomatic Group. University of Jaén

    Grant of excellence from Ministry of Education to collaborate with the Computer Science department at the University of Jaén on a research project.
HONORS AND AWARDS
  • 2019

    V Premios en Tecnologías de la Información y la Comunicación ‘Ada Lovelace’

    COMPETITIVE AWARD FOR ACADEMIC EXCELLENCE

    Award for the project 'Prototipo de control avanzado de grandes plantaciones mediante teledetección' as the best Degree/Master thesis during academic year 2018-2019.
LANGUAGES
  • 2021

    B2 First - Score 178

    Cambridge Assessment English

    Issued on January 2021. Exam: December 2020.
  • 2021

    B1 Preliminary - Score 159

    Cambridge Assessment English

    Issued on August 2016. Exam: July 2016.
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CONTACT

Drop us a line

GET IN TOUCH





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PUBLICATIONS

PUBLICATIONS LIST
22 Sep, 2021

A GPU-accelerated LiDAR sensor for generating
labelled datasets

Congreso Español de Informática Gráfica 2021 (CEIG), Málaga (España), 22-24 de septiembre de 2021

Volume ~, pp. ~, DOI: ~

Journal Paper PDF Bibtex Alfonso López; Carlos J. Ogayar; Francisco R. Feito
22 Sep, 2021

Comparison of GPU-based methods for handling
point cloud occlusion

Congreso Español de Informática Gráfica 2021 (CEIG), Málaga (España), 22-24 de septiembre de 2021

Volume ~, pp. ~, DOI: ~

Journal Paper PDF Bibtex Alfonso López; J. M. Jurado, E. J. Padrón, C. J. Ogayar; F. R. Feito
12 Jan, 2021

A framework for registering UAV-based imagery for crop-tracking in Precision Agriculture

International Journal of Applied Earth Observation and Geoinformation (Elsevier)

Volume 97, pp. 102274, DOI: 10.1016/j.jag.2020.102274

Conference PDF Bibtex Alfonso López; Juan M. Jurado; Carlos J. Ogayar; Francisco R. Feito
15 Dec, 2020

Simulación de escaneados 3D

Master of Computer Science thesis, 2020

With honors (10)


Thesis PDF Alfonso López
26 Jun, 2019

Multispectral Registration, Undistortion and Tree Detection for Precision Agriculture

Congreso Español de Informática Gráfica 2019 (CEIG), San Sebastián (España), 26-28 de junio de 2019

2019, pp. 85-88, DOI: 10.2312/ceig.20191209

Conference PDF Bibtex Alfonso López; Juan M. Jurado; Carlos J. Ogayar; Francisco R. Feito
20 Jun, 2019

Prototipo de control avanzado de grandes plantaciones mediante teledetección

Bachelor of Computer Science thesis, 2019

With honors (10)

Thesis PDF Alfonso López
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RESEARCH

RESEARCH PROJECTS
1 / 4 Research Date : 2006/2007

PROJECT TITLE

DESCRIPTION OF THE PROJECT

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PROJECT TITLE

DESCRIPTION OF THE PROJECT

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SKILLS

PROGRAMMING SKIILLS
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80%
LEVEL : INTERMEDIATE EXPERIENCE : 3 YEARS
Php Asp Ror
DESIGN SKILLS
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95%
LEVEL : ADVANCED EXPERIENCE : 5 YEARS
Photoshop Sketch Avocode
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WORKS

MY PORTFOLIO
Realistic RenderingOpenGL

Ray-Tracing

Ray-Tracing

Naive ray-tracer built over an OpenGL-based environment. The logic under this ray-tracer is described in Ray-Tracing in One Weekend, Ray-Tracing: The Next Week and Ray-Tracing: The Rest of Your Life series. The framework is developed as a sequential approach by hierarchically describing each material's behaviour. Therefore, its implementation in the GPU is not trivial. The repository contains an environment in development stage, though there are no plans to continue this work. Hence, there are some pending tasks yet, e.g. tackling null values visible on the image (completely dark or white pixels).

Some screenshots obtained from the ray-tracer are following attached:

Geometric AlgorithmsRealistic RenderingOpenGL

Large Point Cloud Rendering

Large Point Cloud Rendering

Framework for the rendering of large point clouds using GPU compute shaders instead of the traditional rendering pipeline. The size of the point clouds is limited by the memory capacity of the GPU, as they are fully loaded into the GPU, either as a single buffer or several chunks. The benefits of this framework are presented in a Conference paper entitled "Comparison of GPU-based methods for handling point cloud occlusion", where sorting algorithms are omitted, though they allow reducing the response time up to the half of the reported results. For that purpose, points are sorted along a Z-curve to place close points in similar buffer indices. This methodology is also used for providing a reduction tool, in order to decrease the number of points (mainly for large point clouds which cannot be fully wrapped in the GPU).

Some screenshots from the rendering tool are following attached: