Research Projects

The Graduate Program in Electrical Engineering (PPEEL) has seven laboratories where five research projects are developed by faculty and students, involving various collaborations through national and international partnerships.

I - Research Project: Analysis and Development of Optical and Radiofrequency Systems and Devices

Research Line: Signal Processing and Transmission

The development of LASER technology and fiber optics in the 20th century was instrumental in advancing research in optical devices and creating a paradigm shift in telecommunications. Today, more than 90% of internet traffic is carried through submarine optical cables connecting continents. This technology has impacted many areas such as medicine, construction, metrology, and aviation. Optical fiber sensors offer numerous advantages over their electrical counterparts, such as smaller size, lighter weight, longer lifespan, electromagnetic interference immunity, lower power consumption, resistance to corrosive environments, and higher sensitivity.

Integrated photonic circuits (PICs) are devices that integrate multiple optical functions in a manner similar to integrated electronic circuits (ICs). In this context, this research project aims to analyze, optimize, and develop optical systems and devices, particularly optical fiber sensors and CMOS-compatible integrated optics devices.

At the same time, RF systems continue to be relevant and present in daily applications. The evolution of RF systems is evident in technologies like IoT and 5G. These technologies impose challenges such as improving radio propagation channels, processing signals, and managing the transition to millimeter-wave frequencies for 5G.

The second objective of this project is the analysis of RF systems, focusing on overcoming radio propagation challenges for IoT and 5G implementation. Topics include IoT use cases, radio propagation characteristics, signal processing techniques, MIMO systems, and exploratory use of software-defined radios (SDRs).

Faculty Involved:

• João Terêncio Dias
• Maurício Henrique Costa Dias
• Maria Aparecida Gonçalves Martinez
• Maria Thereza Miranda Rocco Giraldi

II - Research Project: Intelligent Instrumentation and Advanced Control of Uncertain Systems

Research Line: Instrumentation and Control

This project focuses on applied research in control systems, especially for uncertain nonlinear systems. It aims to develop control methodologies for systems whose mathematical models are imprecise or vary unpredictably over time. The project covers robust and adaptive control methodologies and artificial intelligence techniques such as fuzzy logic, neural networks, and genetic algorithms.

These control strategies are applied to robotic systems, including large-structure inspections, surveillance, and delivery systems, minimizing risks to human operators.

Faculty Involved:

• Alessandro Rosa Lopes Zachi
• Fabio Augusto de Alcantara Andrade
• Luis Fabián Olivera Mederos
• Milena Faria Pinto
• Thiago Americano do Brasil

III - Research Project: Nanotechnology Applied to Functional Nanomaterials for the Manufacture of Energy Generation and Storage Devices

Research Line: Instrumentation and Control

This project focuses on nanotechnology, renewable energy, and energy storage. It involves the development of new nanomaterials for use in solar cells, supercapacitors, and biosensors. These efforts contribute to low-cost, renewable energy solutions and the development of adaptive filters for estimating parameters of the devices built in the laboratories.

Faculty Involved:

• Ana Lucia Ferreira de Barros
• Luis Fabián Olivera Mederos
• Gabriel Matos Araújo
• Diego Barreto Haddad
• Milena Faria Pinto
• Thiago Americano do Brasil

IV - Research Project: Applied Intelligent Systems

Research Line: Signal Processing and Transmission

This project seeks to develop signal processing and artificial intelligence strategies to infer necessary parameters for various applications. These applications include acoustics, neuroscience, computer vision, time series prediction, deep learning, and oil and energy industries. Intelligent systems are also critical in fields such as acoustic monitoring in noisy environments, biological signal extraction, and human-machine interfaces.

In the oil industry, intelligent systems are developed for managing reservoirs, as decisions in this area involve a large number of variables, constraints, and uncertainties.

Faculty Involved:

• Luciana Faletti Almeida
• Diego Barreto Haddad
• Fabio Augusto de Alcantara Andrade
• Gabriel Matos Araújo
• João Terêncio Dias
• Milena Faria Pinto
• Thiago Americano do Brasil