Ricardo Rodríguez Jorge, PhD
Research Scientist
Department of Information and communications technologies
Ceit Research Center /“Researching Today, Creating the Future”
Donosti, Spain


Reseach group: Data Analysis and Information Management Group

Research visit. Institution: National Technologic of Mexico / Technological Institute of Ciudad Victoria.
(July 1st – July 31th 2022)

Visiting Professor
Czech Technical University in Prague, Czech Republic
(Dec 2016 -January 2017)

Research visit
Tohoku University, Japan (May- Jul 2011)

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I welcome my colleagues and fellow academics to this web site. If you would like to discuss any of my published work, please feel free to contact me. My professional interests are mainly in Engineering and my work today has been focused on signal processing and machine learning to bridge innovative ways in these areas.
 
I am always looking for industrial and academic collaboration, please do not hesitate to contact me for project collaborations. For more information about my current running projects please visit Research projects.
 
Institute web page:  Data Analysis and Information Management Group
Call for papers: https://www.rodriguezricardo.net/rodriguezjorgericardo/
Courses: https://www.rodriguezricardo.net/rodriguezjorgericardo/
Research Interest Group: Mechatronics,  Signal Processing, Control and Artificial Neural Networks
Contact Information: E-mail: rrodriguezj@ceit.es, Telephone: +34 943 212 800 / Ext. 2940, Office: 011, Skype: rodriguezri,  Mobile phone:
 

My proposed Master's thesis catalog is presented in the following table

 
<< TO BE UPDATED, PLEASE VISIT AGAIN >>

Master's Thesis
 
Non-linear neuro-controller for automatic control tasks
Use of Raspberry Pi for the adaptive identification and management of hydraulic systems
Deep learning for visual recognition
Planning of energy efficient routes for industrial robots
Self-tuning of PID controllers for robot manipulators
Production technology processes monitoring
Characterization and analysis of micro-TC of biomedical tissues
Predictor of the behavior of soft robot using machine learning
Global optimization study using particle swarm
Rigid body movement as a predictor of wave status
Calibration of a heliostat with drones
Impact quantification of sensor capabilities in UAV localization
Restriction of tracking algorithm for SLAM features with body mode
High precision dimensional metrology
Development of a microfluidic device for the isolation of bacteria from bodily fluids
Machine learning for CT-PET scans co-registered for identification of TB lesions in lungs
Adaptive control of automatic pneumatic pressure regulator
Classification of cardiac arrhythmias using neural networks
Neural networks for the reconstruction of thermal images
Higher-order unit for modeling fuel consumption of an aircraft
Validation of the aerodynamic profile data
Architecture for the early detection of hyperglycemia
Low-cost hardware for ergonomic applications
Wireless physiological measurement system using FPGA and Bluetooth
Collaborative human-machine interaction in industrial environments
Characterization and analysis of low-cost biomedical platforms
Multi-sensor mHealth system based on Android
Smartphone-based monitoring system for the evaluation of long-term sleep
Contextualized application for the control of mobile robots using physiological data
A web platform for viewing and obtaining biosignals in real time
Adaptive control of a robotic prosthesis
Linear discriminant analysis for electrocardiogram signal processing
Non-stationary analysis of biomedical signals
A predictive model using the Hilbert-Huang transform and Fuzzy Logic
Comparative analysis of noise filtering in biomedical signals using wavelets and Hilbert-Huang transform.
Extraction of characteristics in electrocardiograms applying independent component analysis (ICA) and Fourier transform
Non-stationary analysis in neonatal electrophysiological signals
Extraction of characteristics in spinograms signals and the analysis of their non-stationarity
SARIMA model for the prediction of climate change
Time series machine learning using embedded time-delay and precision Annealing
Deep learning for computer vision with Python. 
Neural Network Machine Translation Technology
Applied Control
Signal Processing for ECG
 
 
If you are interested in doing Master's thesis with me, please write me an email to ricardo.rodriguezjorge.mx@ieee.org or you can visit me in my office.
 
 
The area of ​​signal processing, control and neural networks belongs to the research group “Informatics” and has several active projects. To work successfully in signal processing, control and artificial neural networks requires very good bases in programming, ability to write well in English and Spanish, ability to read well in English, good mathematical foundation and a good attitude to efficiently develop teamwork and independently. Consult the Publications and Research Projects sections of Dr. Rodriguez Jorge to obtain more detailed information about the current projects. If you are interested in learning more about the projects or obtaining a graduate degree working in this area, please write an email to Dr. Ricardo Rodríguez Jorge or visit our facilities in Usti nad Labem, Czech Republic.
 
In case of entering as a thesis student, in the research activities you will perform you will use the following operating systems, software and programming languages:
 

       ° Linux

       ° Python

       ° C/C++

       ° LaTeX

 
An adequate way to find out if a Master's degree with a focus on research is for you, is doing your internships or professional residencies in our group. For more information about this aspect consult my personal page www.rodriguezricardo.net.
 
For information on calendar procedures, admission procedures and other aspects related to postgraduate studies at the UJEP see the page of the Informatics Department.
 
 
 
Thanks for your interest.