About Us
Our research is aimed at advancing the state of the art on sensor-based systems on classic and intelligent instrumentation using hardware (electronics and microelectronics) and software solutions.
The IEE-IA was founded with the objective of acting in teaching, research and extension activities in the area of electro-electronic instrumentation and artificial intelligence applied to sensor-based system.
Our team develops sensors, analog and digital signal conditioning and techniques to apply computational intelligence to instrumentation in hardware (analog processing and accelerators) and software.
The lab name was previously IEE-Bio and was updated to IEE-IA to reflect a broader scope of research using instrumentation and artificial intelligence techniques, which includes Classical and Intelligent Instrumentation, Biomedical and Microelectronics.
Research Lines
Classical and Intelligent Instrumentation
- Sensor transducers: force, torque, temperature, piezoelectric accelerometers;
- analog and digital signal conditioning;
- machine learning strategies applied to sensor-based systems;
- computational intelligence for industry, healthcare and agriculture;
Biomedical
- biomedical signal processing and classification (ECG, sEMG, EEG);
- virtual sensors;
- image processing;
Microelectronics
- neuromorphic circuits applied to sensor-based systems
- AI hardware (mixed-signal hardware accelerators) and analog computing.
- analog design synthesis and optimization.
Our Team
We are a group of researchers commited to delivering high-quality research on our fields of interest.
Professors
Alexandre Balbinot
Principal Investigator
Tiago Oliveira Weber
Professor/Researcher
Leia Bagesteiro
Professor/Researcher
Mauricio Tosin
Professor/ResearcherStudents (Ph.Ds, M. Sc. and Undergraduate)
Guilherme Pastre
Doctorade Student (PhD candidate)
Gabriel Cianni de Oliveira
M.Sc. Student
Fernando Borges Weimer
M.Sc. Student
Matheus Lopes da Silva
M.Sc. Student
Bruno Moreira Nabinger
M.Sc. Student
Germano Caberlan Smaniotto
M.Sc. Student
Bernardo Caetani
M.Sc. Student
Lucas Alves
Undegraduate Student
Matheos Ghellar
Undegraduate Student
Pedro Sito Monaco
Undegraduate StudentAlumni
Resources
Some of the datasets developed by the group are available for other researchers.
IEE EMG DATABASE
The IEE sEMG database was formed to provide benchmark data for the scientific community to enable tests on different methodologies involving classification and actuation based on EMG signal processing.
Research with us
Students (under and post graduation) interested in our research lines and willing to study and investigate them should seek opportunities with us.
Be part of our research groupContact Us
For more information about collaboration and opportunities, contact us.
Av. Osvaldo Aranha, 103
Room #206-D - Graduate Program of Electrical Engineering (PPGEE)
Porto Alegre, RS, Brazil
alexandre.balbinot@ufrgs.br · tiago.weber@ufrgs.br