Juan Manuel Vargas García is a research scientist in the Electrical Engineering department
within the CEMSE Division at King Abdullah University of Science and Technology. In 2019,
he got her B.E. in Bioengineering at the University El Bosque, Bogota, Colombia, where he
learned about signals and image processing applied with machine learning and deep
learning in the monitoring, diagnosis, and rehabilitation of biological entities. In 2020 and
early 2021, he joins the ongoing research made by the gincibo group about new
computational methods for Stroke segmentation in magnetic resonance images (MRI). Also,
during this year, he worked as a data scientist for the Communication and Analysis group for
the president of la Republica de Colombia. Finally, in June of 2021, he joined professor's
Meriem EMAN group as a Visiting student at King Abdullah University of Science and
Technology (KAUST). His research field of interest is quantum signal processing applied to
biological signals and images, and machine learning and deep learning methods applies to
different fields in biology like medicine, agriculture, or bioacoustics.
One of my projects consist a multiple linear regression model for estimating the Carotid to
femoral pulse wave velocity (cf-PWV) from a single non-invasive peripheral pulse wave,
namely blood pressure or photoplethysmography,extracted from one of the peripheral areas
Radial, Digital or Brachial. The training and testing datasets were extracted from in-silico,
publicly available, pulse waves and hemodynamics data. The proposed model relies on a
preprocessing and features extraction steps, which are performed using a semi-classical
signal analysis (SCSA) method which is proposed as an n-dimesion featrure extraction
method with the special cases of one and two dimension. The obtained results provide more
evidence for the feasibility of machine learning and the SCSA method as a smart tool for the
efficient assessment of the cf-PWV.

Additionally, I’m collaborating on the development of a user interface for the different projects
related to the Cardiovascular system made by students of the EMANG group. The main
objective of this interface is to create a tool to help doctors and medical students to sense
different physiological parameters relevant to the understanding of the Cardiovascular
system as the cf-PWV or the Systolic and Diastolic blood pressure. Furthermore, this
interface has multiple machine learning models and state-of-the-art feature extraction
methods allowing researchers and students interested in Biosignal processing and artificial
intelligence to learn more about different methods applied to the cardiovascular system and
applies to their own investigation.

Finally, in parallel with the interface, I am studying the properties of the parameters from the
2D-SCSA and some possible applications to improve the quality of the image reconstructed
and the understanding of the behavior of the SCSA applies to images.

B.E. in Bioengineering January 2015 - November 2019 University El Bosque, Bogotá
Certifications and achievements
•Teaching Assistant for "Electronic circuits" teaching the basic of Ohm and Kirchoff law
applied to biological circuit analyisis to Bioengineering students . January 2016 – June 2017
• Investigation group: Renewable and Sustainable Energy. September 2017

•President of RAS chapter (Robotics and Automation Society) of IEEE from University El
Bosque, Bogotá. January 2018 – January 2019

•Teaching Assistant for "Transductors" teaching to use arduino and the most common
transductor used in application relatied with biology to Bioengineering students . June 2018
•Teaching Assistant for "Control systems" teaching the control system design techniques and
their applications in biology to Bioengineering students. January 2019