Research statement
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| << TO BE UPDATED, PLEASE VISIT AGAIN>> |
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The
Research Statement
of
Dr. Ricardo Rodriguez Jorge
is updated to July 2019. The completed and signed version of
my Research Statement is available upon request. |
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My research bridges the
areas of signal processing,
machine learning,
and Intelligent Computing.
The overarching goal of
my research is to achieve
effective and efficient
signal processing methods on
non-stationary and
complex signals, especially in the presence
of missing and noisy data. I am interested in exploring
applications on different problem domains, and I enjoy to
board problems with practical impact. I have realized that
the ability to link theoretical models with practical
real-world applications is essential to successful research.
This involves analyzing a problem and then applying
effective techniques for solving it. According to my
experience, several different problems might share some
common characteristics. Having the ability to understand
such inherent characteristics have enabled me to approach
problems with different views and to develop better
solutions. |
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My previous joint position as full-time Ph.D. Student at the
Department of Instrumentation and Control Engineering in
Czech Technical University in Prague (CTU), Czech Republic,
has provided me with extraordinary opportunities to work on
challenges focused on
biomedical disciplines. This has inspired my
signal processing
research with the application of
machine learning
techniques, integral and discrete transforms, and
intelligent computing. |
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In addition, my experience in CTU and my
research visit to
Yoshizawa-Homma laboratory (in 2011) at Tohoku University in
Japan have been of great experience to
enhance my research; currently my joint position as
Titular
Professor/Researcher at Institute of Engineering and
Technology in the Autonomous University of Ciudad Juarez
in Mexico has provided me with excellent opportunities to
continue my research in the signal processing field. I have
focused on developing novel techniques for
highly accurate
prediction methods,
noise reduction methods in
real-time signals, dimension
reduction methods, detecting features by
adaptive thresholds, and
highly accurate classification
methods. |
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I have established several fruitful
cross-disciplinary collaborations
since the past 9 years with
Yoshizawa-Homma laboratory (Japan),
Department of Instrumentation and
Control Engineering in CTU,
Opole University,
Technological Institute of Ciudad Victoria,
Hanoi University of Industry,
Autonomous University of Morelos State,
University of
Guadalajara,
and Autonomous University of Ciudad Juarez. My
largest ongoing projects are in collaboration with them.
Accordingly, most of my research has been in collaboration
with colleagues, and it has been greatly enhanced by their
insights and support. |
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