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MSc Computer Vision | Robotics Software Engineer
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AIVA_2024_DCMIA
March 5, 2024 – April 26, 2024
Simulación de proyecto entre cliente (profesor) y empresa (alumnos) para la asignatura Aplicaciones Industriales y Comerciales del Máster Universitario en Visión Artificial.
View Projectvision-robotica-2023-2024
February 8, 2024 – April 27, 2024
Memorias de las prácticas de la asignatura "Visión Robótica" del Máster en Visión Artificial de la Universidad Rey Juan Carlos.
View Projectemotion_detection_ros
May 30, 2022 – November 2, 2023
Real Time Emotion Detection for Low Cost Robot in ROS
View Projectaprendizaje-proyecto
November 29, 2021 – Present
Navegación autónoma basada en Redes Neuronales
View ProjectRobotica-Servicio-2021-2022
October 12, 2021 – December 21, 2021
Memorias de las prácticas de la asignatura "Robótica de Servicio" en la Universidad Rey Juan Carlos.
View ProjectMecatronica-proyecto
September 27, 2021 – Present
Robot educativo con forma de araña impreso en 3D y controlado a través de una FPGA
View Projectplansys2_optic_plan_solver
April 1, 2021 – April 1, 2021
Plan solver for ROS2 Planning System that uses OPTIC for solving PDDL plans.
View ProjectCultural Fit Analysis
The candidate's project portfolio shows a strong inclination towards academic and personal research in robotics and artificial vision. While this demonstrates initiative and passion, the lack of professional experience or team-based projects makes it difficult to assess cultural fit for a collaborative industry role. The projects align with the technical domain of a Data Scientist role, particularly in areas like computer vision and autonomous systems, but the breadth of data science applications (e.g., statistical modeling, large-scale data processing, business intelligence) is not evident.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's projects are primarily technical and personal, offering no insight into collaboration, communication, or problem-solving in a team or professional setting.