The goal is to develop teaching methods, support resources, and curricular designs through research, technological development projects, and educational innovation to train engineers.
The research group has recognized the importance of Engineering Education in pursuing academic excellence in student training. This line of research investigates and implements curriculum design methodologies, teaching strategies, and technologies to support student-centered education in the Group's areas of academic work. The GICI develops competency-based curriculum design frameworks and project-based learning environments, supported by local and remote laboratories, both physical and virtual, and tools for mathematical analysis, simulation, and emulation of dynamic systems.
The goal is to develop research, technological development projects and innovation in electronic power converters and intelligent energy management systems, through the application of advanced control algorithms, artificial intelligence, high-frequency switching technologies, real-time modeling and embedded systems, in order to improve the performance and utilization of available energy resources.
The Smart Power Electronics research line focuses on the development of advanced electronic converters and intelligent energy management systems. This research area addresses the modeling, design, control, implementation, and diagnostics of power electronic systems, employing both classic and modern strategies, such as linear, predictive, optimal, distributed, and agent-based control, as well as data-driven methods and artificial intelligence techniques. This research line aims to optimize the topology, control, and performance of electronic converters used in microgrids, renewable energy systems, battery storage, electric vehicles, and other applications.
The goal is to develop research, technological development projects and innovative solutions in biomechatronics, robotics, and biomedical engineering, using mathematical and engineering tools, to analyze physiological and biomechanical processes, and develop methods and devices applied in medicine, sports, among others.
This research area is an interdisciplinary field of work in emerging areas of biomechatronics, robotics, and biomedical engineering with significant social impact. It investigates and develops systems and devices for: supporting the rehabilitation and mobility of people with motor disabilities, preventing the risk of falls, analyzing balance, and developing data-driven models, physiological models, and optimization techniques. It develops applications in health-related fields such as ergonomics, sports, medicine, occupational health, biomechanics, and physiotherapy, among others.
The goal is to develop research, technological development projects and innovation in automation, industrial robotics and control: classic, advanced, and based on data and artificial intelligence for Industry 4.0.
The research group recognizes the importance of regulatory control, sequential control, and fault diagnosis in industrial processes. This line of research investigates problems related to: modeling, parametric identification and data-driven control, artificial intelligence, classical control, advanced control (optimal, predictive, agent-based, distributed, robust, among others), and process automation.