INNOVATEC (Investigación en Ingeniería Operativa, Videojuegos y Aplicaciones Tecnológicas - Research in Operational Engineering, Video Games, and Technological Applications) is a new research group that combines:
Software Engineering, Computer Graphics, Video Games, and Educational Technologies
Qualitative, Operational, and Metaheuristic Research
Our research focuses on the design, development, and evaluation of advanced software systems (e.g. Cloud IoT-Edge based solutions), interactive technologies, and educational tools. We innovate in game development, and educational technology, creating solutions that enhance user experience and learning through interactive and challenge-based methods. We also explore DevOps culture, agile software engineering practices and advanced computer graphics to improve application quality and usability.
We study optimization and decision-making for complex technological applications. Our research includes operational modeling and simulation for resource management and planning efficiency. Additionally, we develop metaheuristic algorithms, such as genetic algorithms and swarm optimization, to solve complex problems in diverse fields.
Our research in software engineering focuses on advancing qualitative methods, particularly grounded theory (GT) and theory building, to develop deep insights into software practices and processes.
Research in Software Engineering, Computer Graphics, Videogames and Educational Technologies
Our research in this area focuses on the design, development and evaluation of systems and applications that integrate advanced software engineering, computer graphics, and interactive technologies. We seek to innovate in the field of video games and educational technologies, creating solutions that not only optimize software performance and quality, but also improve user experience and interactive learning.
In computer graphics, we explore both the creation of advanced visual environments and the simulation of virtual scenarios, which are directly applied to the video game industry. Our team also researches the use of video games as educational tools, developing and evaluating platforms that facilitate challenge-based learning, gamification and immersive training. We are passionate about the potential of technology to transform education and seek to integrate solutions that promote active and meaningful learning.
This multidisciplinary approach allows us to drive innovative applications that impact sectors such as entertainment, education, and software development through advanced digital learning and interaction methods.
Qualitative Research, Operational Research, Heuristics & Metaheuristics
Our research in software engineering is centered on advancing qualitative methodologies, with a particular focus on grounded theory (GT). We have developed a tailored GT process that integrates principles from established approaches, including Classic (Glaserian), Straussian, and Constructivist GT. This allows us to gain deep insights into software practices and processes. Additionally, we have created and published tutorials to guide researchers in calculating inter-coder agreement (IRA), offering clear and structured methods for ensuring reliability in qualitative studies. Our current focus is on theory building, with an emphasis on developing, operationalizing, and testing theories that propel software engineering forward as a robust academic and practical discipline.
In operations research, we address process optimization and complex problem-solving in industrial and technological contexts. Through advanced modeling and simulation, we optimize resource allocation, task scheduling, and logistics, ensuring efficiency and resilience in multifaceted systems. Our research investigates sophisticated optimization methods and decision-making frameworks, targeting a wide range of applications. By creating models and algorithms capable of addressing large-scale, highly complex problems, we aim to deliver innovative solutions where traditional methods fall short.
In the specialized area of metaheuristics, we design and implement cutting-edge optimization algorithms to solve intricate search and optimization problems. Our work spans diverse fields, including planning, network design, and artificial intelligence. Techniques such as genetic algorithms, particle swarm optimization, and other nature-inspired methods enable us to navigate vast, multi-constrained search spaces and identify near-optimal solutions efficiently.
Driving Innovation Through a Multidisciplinary Approach
By integrating qualitative, operational, and metaheuristic research, we tackle complex challenges with a holistic perspective. This multidisciplinary approach allows us to develop transformative solutions that bridge the gap between theoretical research and industrial application, empowering organizations to achieve their goals while advancing the frontiers of applied science and engineering.
@ Universidad Politécnica de Madrid