Students

If you want to do your final project, Master/Ph.D. thesis in Artificial Intelligence, Reservoir Computing and related applications (Machine learning/Neural networks), please feel free to contact me.
 

CURRENT STUDENTS

PhD thesis co-supervision

  • Jean P. Jordanou. "Data-driven Modeling and Control of Large Scale Systems", 2020 - Present.
  • João Gabriel Zago. "Formal Verification of Deep Neural Networks", 2021 - Present. 

Master thesis supervision

  • Bruno Maciel. "Aprendizagem por Imitação com Redução de Situações de Risco para Condução de Veículos Autônomos". 2022 - Present.
  • Eric Mochiutti. "Redes de Estado de Eco Híbridas para Simulação Rápida e Controle de Processos Industriais: Aplicação em Poços de Petróleo com Gás-Lift". 2022 - Present.
  • Gustavo Claudio Karl Couto. "Generative Adversarial Imitation Learning with Mid-level Input Generation for Autonomous Vehicles in Urban Environments". 2020 - Present.
  • Irving Giovani.  "On the Beta distribution for Agents Learning through Interaction with their Environments". 2020 - Present.
  • Willian Benoski. "Primal Wasserstein Imitation Learning for Autonomous Driving". 2023 - Present.

Visitors:

  • Christian Hammacher, Technical University of Darmstadt, Germany, 2023 - Present.

Hiking with Master students in the island of Florianópolis, Brazil, in 2023:

group_autonomous_vehicles.jpg

 

FORMER STUDENTS

Master thesis

  • Rafael Toledo. "A Performance Increment Strategy for Semantic Segmentation of Low-Resolution Images from Damaged Roads". 2022.

Mentoring & Collaboration

  • Ph.D student: Manxing Du, SnT, University of Luxembourg. "Reinforcement learning for Real-time Bidding in display advertising". 2017 - 2018.
  • Ph.D student: Yuantao Fan, Halmstad University, Sweden. "Echo State Networks as models for deviation detection with application to predictive maintainance of fleets". 2016 - 2017.

Master thesis co-supervisions

  • Jonas Kittelsen. Physics-Informed Neural Networks for Modeling and Control of Gas-Lifted Oil Wells (co-orientador). 2022.
  • João Gabriel Zago. Defense Methods for Convolutional Neural Networks Against Adversarial Attacks (co-orientador). 2021.
  • Iver Osnes. Recurrent Neural Networks and Nonlinear Model-based Predictive Control of an Oil Well with ESP (co-orientador). 2020.
  • Sondre Bø Hernes. Recurrent Neural Networks and Practical NMPC of an Oil Well with ESP (co-orientador). 2020.
  • Jean P. Jordanou. "Echo State Networks for Online Learning Control and MPC of Unknown Dynamic Systems: application in Control of Oil Wells", 2019.
  • Ken Caluwaerts. "Design of a biologically inspired navigation system for the Psikharpax rodent robot", 2010.
  • Dries Van Puymbroeck. "Robot Navigation and Localization using Reservoir Computing", 2009.
  • Tim Waegeman. "Modeling Multiple Behaviors with Reservoir Computing for Autonomous Mobile Robots", 2009.
  • Karel Braeckman. "Localization of a mobile robot using Reservoir Computing", 2008.
  • Stijn Adam. "Reservoir Computing for robotics",  2008.

Undergraduate students

  • Laíza Milena Scheid Parizotto. Cone Detection with Convolutional Neural Networks for an Autonomous Formula SAE Race Car. 2020. 
  • Amanda Furtado Brinhosa. "Estruturação automática de laudos médicos utilizando processamento de linguagem natural e aprendizado de máquina para extração de informações clínicas". 2020.
  • Eduardo Rehbein. Physics informed neural networks (co-orientador), 2020.
  • Augusto Luiz Greuel. "Assistente virtual do tipo chatbot para gerenciamento de eventos em uma infra-estrutura de TI:". 2020.
  • Maria Fernanda Dias Portella, "Geração de laudos médicos por reconhecimento de fala". 2020.
  • Jean P. Jordanou. "Recurrent Neural Network Based Control for Risers and Oil Wells", 2017.
  • Marcelo Menezes Morato. "Controle um de Pêndulo Duplo Invertido com Redes de Estados de Eco", 2015.

 

 

 

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