Faculty of Engineering

Z7_NQ5E12C0LOF160QDKRNCOGGJA1

Research group

Spanish

Research Group on Applied Telecommunications - GITA

Academic Unit: Faculty of Engineering

Colombian Ministry of Science

A1

Call

894 GrupLAC

OECD

Area

Engineering and technology

Subarea

Electrical engineering, electronic engineering, information engineering

Download Fact Sheet

Strategic Focus

GITA group seeks to be an outstanding regional group in applied optics-related developments, communication systems modeling, and pattern analysis. We expect to have an impact on industries and the private sector by offering effective solutions for the specific problems that businesspeople and governments may have.

Research Lines and/or Areas

Optical communications.
Communication systems modeling.
Digital Signal Processing.

Sustainable Development Goals (SDGs)

Group Coordinator

Juan Rafael Orozco Arroyave, Ph.D.

Ph.D. in Computer Science.

University of Erlangen, Nuremberg.

Coordinator's Email

rafael.orozco@udea.edu.co

Scientific Cooperation

Collaborative Relationships

Konecta Group.
Pratech Group.
IMEC (Antwerp, Belgium).
LME Lab (Erlangen, Germany).
IDIAP (EPFL, Switzerland).
SAMI (Czech Technical University in Prague, Czech Republic).

BDA Lab (Antwerp, Belgium).
MAD Lab (Erlangen, Germany).
MackGraphe (São Paulo, Brazil).
Universidad Nacional (Medellin and Manizales).
GES Group [Health Economy Group] (UdeA).
GOF Group [Optics and Photonics Group] (UdeA).

Highlighted Projects

Speech and Movement Analysis using your SMArt phone for neurological diseases (SMA^2).
Tormenta: Intelligent management of cloud-based electronic services (Tormenta: Gestión Inteligente de servicios eléctricos en la nube).
Asynchronous multi-modal analysis of bio-signals for the automatic evaluation of the neurological state of Parkinson's disease patients.
Analysis of the fields of application of optic pulses generated through the filtering of various portions of the ultra-short optical pulse spectrum.

Key Research Findings

Multimodal assessment of Parkinson’s disease: A deep learning approach. DOI: https://bit.ly/3g8VawQ
Efficient graphene saturable absorbers on D-shaped optical fiber for ultrashort pulse generation. DOI: https://bit.ly/3g9g1jp
Defining a Reliable Network Topology in Software-Defined Power Substations. DOI: https://bit.ly/36gEaAd
Analysis and evaluation of handwriting in patients with Parkinson’s disease using kinematic, geometrical, and non-linear features. DOI: https://bit.ly/3g5n6BA