Recent research:
The research focuses on the intersection of industrial automation, advanced control systems, and sustainable technology. A significant portion of the work involves the application of artificial intelligence and computer vision to optimize industrial processes, including the deployment of hybrid machine learning models for environmental monitoring and real-time alerting, as well as the implementation of deep learning architectures for quality control and logistics automation in manufacturing. Furthermore, the research addresses critical challenges in electrical engineering, specifically through the simulation and experimental validation of grounding systems, dielectric breakdown in medium-voltage switchgear, and the performance assessment of building-integrated photovoltaic systems. Beyond industrial applications, the work extends to agricultural innovation, where intelligent control systems are utilized to optimize organic hydroponic production through precise nutrient and water recirculation management. Finally, the research emphasizes pedagogical advancement by developing portable, PLC-based didactic modules that bridge the gap between theoretical engineering education and practical industrial requirements, ensuring that modern automation technologies are effectively integrated into academic and professional training environments.

Key Topics:

• Industrial Automation and Control Systems
• Artificial Intelligence and Computer Vision
• Electrical Power Systems and Grounding
• Sustainable Energy and Photovoltaics
• Precision Agriculture and Hydroponics
• Engineering Education and Didactic Modules