Arnaldo Gomes Leal Júnior

Title: PhD (PPGEE-UFES, Brasil, 2018)

Research groups: CNPq (Google Translator version)
Curriculum: Lattes

Course starting: 24/02/2016

Participation in projects:

Title Starting datesort ascending Deadline (months) Participation in the project
01/06/2021 36 Coordinator *
02/03/2020 36 Coordinator *
30/04/2018 48 Researcher *
06/05/2016 36 Student Master *

Productions:

Titlesort descending Details Defense date
Polymer Optical Fiber Sensors for Healthcare Devices: From the Material Analysis to Practical Applications Mestrado Acadêmico dissertação 17/12/2018
Polymer Optical Fiber Sensors for Healthcare Devices: From the Material Analysis to Practical Applications Doutorado tese 17/12/2018

Participants in examination boards:

Title Name Defense datesort ascending Course
Digital Twins and Augmented Observability: An Architecture Model for Experimental Oil & Gas Separator Vessel Digitization Raphael Almeida Guimarães dos Santos 22/07/2021 MSc in Electrical Engineering
Renan Costa Lazaro 25/05/2021 MSc in Electrical Engineering
Liquid level estimation and fluid identification using FBG temperature sensors via machine learning algorithms Katiuski Pereira Nascimento 05/05/2021 MSc in Electrical Engineering
Higor Araújo Fim Camporez 28/05/2020 MSc in Electrical Engineering
Fabio Giesen Ludke 27/05/2020 MSc in Electrical Engineering

Disciplines taught:

Academic termsort ascending Code Name Hours Course
2021/1 PGEE-5577 45 MSc in Electrical Engineering
2020/2 PGEE-5577 45 MSc in Electrical Engineering

Guided Students:

Name Title Defense datesort ascending Role Type
Eduarda Pedruzzi da Silva Co-advisor * Proposal for msc dissertation
Leandro Munhoz de Avellar Advisor * Proposal for phd thesis
Raphael Almeida Guimarães dos Santos Digital Twins and Augmented Observability: An Architecture Model for Experimental Oil & Gas Separator Vessel Digitization 22/07/2021 Co-advisor * MSc dissertation
Renan Costa Lazaro 25/05/2021 Advisor * MSc dissertation
Katiuski Pereira Nascimento Liquid level estimation and fluid identification using FBG temperature sensors via machine learning algorithms 05/05/2021 Advisor * MSc dissertation
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