Prof. Dr. Lorena Barona López, EPN, Ecuador
Lorena Isabel Barona López is a researcher and professor specializing in computer science and telecommunications, currently affiliated with the Escuela Politécnica Nacional in Quito, Ecuador. She holds a Ph.D. in Computer Science from the Universidad Complutense de Madrid, Spain, where she developed a situational awareness model for 5G mobile networks within the SELFNET architecture. Her academic background also includes a Master’s in Telematic Services and Networking Engineering from Universidad Politécnica de Madrid and a Bachelor’s degree in Electronic and Information Network Engineering from Escuela Politécnica Nacional. Dr. Barona’s research interests encompass 5G networks, software-defined networking (SDN), virtualization, and data analysis. She is an accredited Level 1 researcher by the Ecuadorian Secretariat for Higher Education, Science, and Technology and a member of various international research networks, including Ciencia Digital and Indra Digital Lab. With extensive teaching experience at both national and international universities, she has lectured in areas such as cybersecurity, network security, embedded systems, and system architecture. Dr. Barona also serves as the Executive Editor of the Ciencia Digital journal and has professional experience in systems administration and IT support. She is proficient in both Spanish and English and actively pursues professional development in artificial intelligence, machine learning, programming, and digital pedagogy.
Professional Profile:
GOOGLE SCHOLAR
ORCID
Summary of Suitability for Best Researcher Award
Dr. Lorena Isabel Barona López is a distinguished academic and researcher in the fields of Computer Science, 5G networks, Data Analysis, Software-Defined Networks (SDN), and Virtualization. Her extensive research background, innovative contributions to next-generation networking technologies, and commitment to both education and scientific advancement make her an exceptionally qualified candidate for the Best Researcher Award.
👩🎓 Education
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🎓 Ph.D. in Computer Science
Universidad Complutense de Madrid, Spain
(Nov 2013 – Sep 2017)
📘 Thesis: Modelo de Conciencia Situacional para el Análisis de Datos en Redes Móviles 5G
🔍 Research Areas: 5G, Data Analysis, SDN, Virtualization
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🎓 Master’s in Telematic Services & Networking Engineering
Universidad Politécnica de Madrid, Spain
(Sep 2012 – Jul 2013)
📘 Thesis: Propuesta de Escenarios Virtuales con la Herramienta VNX para Pruebas del Protocolo OpenFlow
🔍 Focus: OpenFlow, Networks, SDN, Virtualization
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🎓 Bachelor’s in Electronic and Information Network Engineering
Escuela Politécnica Nacional, Ecuador
(Oct 2004 – Oct 2010)
📘 Project: IP-based Surveillance System for Condominiums in Ambato
🔍 Focus: IP, Networks
💼 Work & Teaching Experience
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🧠 Researcher, GASS Group
Universidad Complutense de Madrid
(Nov 2013 – Jul 2017)
🧪 Focus on cybersecurity, 5G, and data analysis.
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📝 Executive Editor, Ciencia Digital Journal
(Sep 2017 – Present)
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👩🏫 Teaching Roles (2011–2025):
Courses in:
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Communication Systems, Embedded Systems, Cybersecurity 🔐
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Network Security, Software Engineering 💻
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Extended Databases, Operating Systems 🖥️
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MOOCs and online teaching platforms 🎓
📍 Institutions:
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Escuela Politécnica Nacional
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Universidad Internacional de la Rioja (Spain)
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Universidad Técnica de Ambato
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Universidad Metropolitana
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Universidad de las Américas
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🖥️ System Administrator, COMDECSA
(May 2011 – Sep 2012)
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🧪 Lab Assistant, Escuela Politécnica Nacional
(Sep 2009 – Aug 2010)
🏅 Achievements, Accreditations, and Honors
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🥇 Aggregated Researcher Level 1, Ecuador’s Secretaría de Educación Superior, Ciencia y Tecnología (2018)
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🌐 Member of:
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📜 Extensive professional certifications in:
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AI & Machine Learning 🤖
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ICT in Education 💡
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Cloud Dashboards ☁️
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Programming (Python 🐍, Java ☕, R 📊)
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Educational tools and Moodle platforms 🎓
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🎖️ Expert in Pedagogical Innovation: flipped classrooms, digital teaching tools, and virtual course design.
Publication Top Notes:
A Systematic Literature Review of Machine Unlearning Techniques in Neural Networks
Heterogeneity Challenges of Federated Learning for Future Wireless Communication Networks
A comparison of EMG-based hand gesture recognition systems based on supervised and reinforcement learning
Recognition of Hand Gestures Based on EMG Signals with Deep and Double-Deep Q-Networks
Hand Gesture and Arm Movement Recognition for Multimodal Control of a 3-DOF Helicopter
Hand Gesture Recognition Using EMG-IMU Signals and Deep Q-Networks
A Hand Gesture Recognition System Using EMG and Reinforcement Learning: A Q-Learning Approach