Gabriel Da Silva Lima
gdasil@utu.fi |
Nonlinear control; Intelligent control; machine learning; Gaussian Process Regression; Artificial Neural Networks; Control of mechatronic systems.
PhD in Electrical and Computer Engineering, Master's in Mechanical Engineering from UFRN (Federal University of Rio Grande do Norte), and Bachelor's degrees in Mechanical Engineering and in Science and Technology with a focus on Mechanical Technology (UFRN). I am currently a postdoctoral researcher in the Smart Systems Research Group at the University of Turku. My main areas of expertise include Intelligent Control, Robotics and Autonomous Systems, Machine Learning, Control of Biological Systems, and the Analysis of Mechanical/Mechatronic Systems.
- Intelligent Control to Suppress Epileptic Seizures in the Amygdala: In Silico Investigation Using a Network of Izhikevich Neurons (2025)
- IEEE Transactions on Neural Systems and Rehabilitation Engineering
- Adaptive control of cardiac rhythms (2024)
- Scientific Reports
- In Silico Application of the Epsilon-Greedy Algorithm for Frequency Optimization of Electrical Neurostimulation for Hypersynchronous Disorders (2024)
- Communications in Computer and Information Science
- Accurate trajectory tracking control with adaptive neural networks for omnidirectional mobile robots subject to unmodeled dynamics (2023)
- Journal of the Brazilian Society of Mechanical Sciences and Engineering
- Intelligent control of cardiac rhythms using artificial neural networks (2023)
- Nonlinear Dynamics
- Intelligent Control of Seizure-Like Activity in a Memristive Neuromorphic Circuit based on the Hodgkin-Huxley Model (2022)
- Journal of Low Power Electronics and Applications
- Sliding Mode Control with Gaussian Process Regression for Underactuated Mechanical Systems (2022)
- IEEE Latin America Transactions
- Sliding Mode Control with Gaussian Process Regression for Underwater Robots (2020)
- Journal of Intelligent and Robotic Systems
UTU Research Portal