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 Doctoral thesis catalog is presented in the following table
<< TO BE UPDATED, PLEASE VISIT AGAIN >> 
 
 

Doctoral thesis
Virtual laboratory for teaching dynamic neural networks of retro-propagation in the control area.

Brain computational interface using recurrent neural networks and multivariate analysis.

Dynamic discrete neural architectures for the prediction of time series (tentative title)
Digital signal processing using empirical decomposition and the wavelet transform (tentative title).
Search methods based on examples for Adaptive-Bayesian planning
Adaptive control using reinforcement learning
Neural unit for the prediction of human dynamic movement in real time
Bayesian Neural Networks based on GPU
Fast Hamiltonian Monte Carlo using GPU computation