Dr. Ricardo Rodríguez Jorge

Research Scientist

Department of Information and Communications Technologies
Ceit Research Center · “Researching Today, Creating the Future”
Donostia – San Sebastián, Spain

Institutional website: portalcientifico.unav.edu/investigadores/1113189
Research group: Data Analysis and Information Management Group

Contact me Curriculum vitae Publications

Education

1. 2009–2012

   PhD in Mechanical Engineering
   Czech Technical University in Prague (CTU), Faculty of Mechanical Engineering, Department of Instrumentation and Control Engineering.

   Field of study: Control and Systems Engineering.
   Thesis: “Lung tumor motion prediction by neural networks”.

2. 28 May – 28 Jul 2011

   Visiting student for a research project (scientific research)
   Tohoku University, Research Division on Advanced Information Technology, Cyberscience Center (Graduate School of Engineering & Graduate School of Biomedical Engineering), Sendai, Japan.

   Host: Prof. Noriyasu Homma, Yoshizawa-Homma Laboratory.
   Project: Intelligent Prediction Method of Lung Tumor Motion for Highly Accurate Radiation Therapy.

3. 2005–2007

   Master of Science in Computer Science
   National Center of Research and Technological Development (CENIDET), Department of Computer Sciences.

   Field of study: Artificial Intelligence. Average: 96.33.
   Thesis: “Validation and Verification Automatic Module of Extracted Rules of a Neural-Symbolic Hybrid System”.

4. 2000–2004

   Bachelor’s Degree in Computational Systems Engineering
   Technological Institute of Lázaro Cárdenas, Department of Computer and Systems.

   Field of study: Distributed systems and networks. Average: 94.28.
   Internship project: “Exploitation of Resources of a CMU Camera for its Start-up on a ROMIC Robot”.

5. 28 Jun – 31 Aug 2004

   Visiting student for a research project (Summer of Scientific Research)
   National Institute of Nuclear Research (ININ), Department of Applied Sciences, Ocoyoacac, Mexico.

   Host: Dr. Armando Segovia, researcher.
   Project: “Exploitation of Resources of a CMU Camera for its Start-up on a ROMIC Robot”.

Awards

• Cátedras de la Diáspora Mexicana 2026: Candidate, National System of Researchers (SNII), Secihti, Mexico. Recognition granted in the 2026 call, effective from 1 January 2027.
• VUB Ambassador in the Big Data area: appointed VUB Ambassador in the Big Data area for the study field 9.2.9 Applied Informatics at the Institute of Informatics and Mathematics, Faculty of Electrical Engineering and Information Technology, Slovak University of Technology in Bratislava (8 August 2019).
• Desirable profile recognition (2017–2020): recognized as a higher-education lecturer with desirable profile by the Undersecretariat for Higher Education, General Directorate of University Higher Education, PRODEP-DSA, SEP (Ministry of Public Education), Mexico.
• Academic body UACJ-CA-75 Mechatronics: recognized as a consolidated research group (CAC) by the Undersecretariat for Higher Education, General Directorate of University Higher Education, PRODEP-DSA, SEP (Ministry of Public Education), Mexico.
• Desirable profile recognition (2014–2017): recognized as a higher-education lecturer with desirable profile by the Undersecretariat for Higher Education, General Directorate of University Higher Education, PRODEP, SEP (Ministry of Public Education), Mexico.
• Best paper award in the field of Computer Sciences for the paper “Preparation and integration of population data in the data mining process: a case of study”, 6th International Conference on Research, CIPITECH 2013, 9–11 October 2013, Chihuahua, Mexico.
• Extraordinary prize: extraordinary scholarship awarded by the Dean of the Faculty of Mechanical Engineering, CTU, for submitting the PhD dissertation before the deadline and for its quality, 2012, Czech Republic.
• First place in the competition of postgraduate students – Faculty of Mechanical Engineering, 2012, Kraków, Poland, with the paper: Ricardo Rodriguez, Jiri Bila, Ivo Bukovsky, “Comparison of MLP and Quadratic Neural Unit for Lung Tumor Motion Prediction”, Sesja studenckich Kół Naukowych – Wydział Mechaniczny PK – 27 IV 2012, Poland, 27 April 2012.
• Second place in the competition for postgraduate students, STC 2012, with the paper: Ricardo Rodriguez, Jiri Bila, Ivo Bukovsky, “Comparison of MLP and Quadratic Neural Unit for Lung Tumor Motion Prediction”, STC 2012, 28 March 2012, Prague, Czech Republic.
• Extraordinary prize for being one of the PhD students who passed the national exam with a high score at the first attempt and finished the PhD courses on time, awarded by the Dean of the Faculty of Mechanical Engineering, CTU, Czech Republic.
• Advisor of a creative project that won 1st place: “Robotic Arm Controlled through Software for the Classification of Industrial Parts”, internal creativity competition, Technological Institute of Ciudad Juárez, 2008, Mexico.
• Advisor of a creative project that won 3rd place in the XXIII National Creativity Event: “Robotic Arm Controlled through Software for the Classification of Industrial Parts”, 2008, Parral, Chihuahua, Mexico.

Software and operating systems

Programming languages

C/C++, Python, LaTeX, MATLAB, R, Java, SQL, HTML, Prolog (logic programming)

Statistical software

SPSS

Math software

Maple

Operating systems

GNU/Linux, macOS

Distributed storage (Big Data)

Azure Data Lake, Amazon Web Services (AWS)

Processing (Big Data)

Apache Spark, Hadoop

Data ingestion (Big Data)

Apache Kafka, Apache NiFi

Cybersecurity

Elasticsearch, Wireshark

Machine learning libraries

PyTorch, TensorFlow, Keras, scikit-learn

Platforms

Docker, OpenStack, OpenMANO, Grafana, Prometheus

Skills

• Predictive modelling, adaptive control
• Cybersecurity, extended Kalman filters, artificial intelligence
• Research and publication in cybersecurity, virtualization, adaptive control, signal processing, computational fluid dynamics, differential-algebraic models, grey-box modelling, time-series prediction and auto-scaling
• Development of machine learning algorithms
• Data pre-processing techniques
• Team management and leadership
• Workflow streamlining
• Automated data collection and cleaning
• Integration of models into production
• Data warehouse set-up

Book

Rodríguez-Jorge, R. (2025). Signal Processing and Machine Learning for Innovation Engineering: Understanding grey box and neural models. OmniaScience. DOI: 10.3926/oms.418

Abstract

This book presents recent advances in signal processing and artificial neural network (ANN) applications aimed at driving innovation in engineering. The proposed developments constitute advanced IT solutions for research, data access and knowledge management, built primarily on Internet of Things (IoT)-assisted architectures.

The techniques described integrate signal processing with wireless neural-network implementations. Several signal-processing, feature-selection and feature-extraction approaches are explored, including band-pass filters combined with numerical derivatives, the Hilbert transform, adaptive thresholding, moving-average filters, autocorrelation functions, wavelet transforms and the Hilbert–Huang transform.

For feature selection, methods such as feature normalization and the False Nearest Neighbor (FNN) technique are examined, while principal component analysis (PCA) is applied for feature extraction. The book also presents real-time tests of IoT-assisted architectures using acquired signals, focusing on the accuracy and performance of ANN models in tasks such as prediction, modelling, control, monitoring and classification.

The applications discussed include fault diagnosis, arrhythmia classification, electrocardiogram (ECG) analysis for global health monitoring, auto-scaling systems and anomaly detection. Overall, this work offers a comprehensive overview of how integrating signal processing and ANN techniques within IoT frameworks can advance intelligent engineering systems.

Upcoming events

Recent keynotes

• Dr. Ricardo Rodríguez Jorge, Real-time adaptive model for advanced control of wastewater treatment plants, lecture series “Computer sciences and their applications in our environment”, Technological Institute of Ciudad Victoria, Mexico, 17 November 2024 (in Spanish).
• Dr. Ricardo Rodríguez Jorge, Impact of uncertainty analysis and feature selection on data science, 11th International Conference on Emerging Internet, Data & Web Technologies (EIDWT-2023), Universitas Islam Sultan Agung (UNISSULA), Semarang, Indonesia, 23–25 February 2023.

  

• Dr. Ricardo Rodríguez Jorge, Data science and machine learning perspectives, International Conference on Intelligence-based Transformations of Technology and Business Trends (ICITTB), Canadian Institute of Technology, Tirana, Albania, 13 October 2022.

  

• Dr. Ricardo Rodríguez Jorge, Machine Learning: Challenges in Data Science Applications, Symposium of Advances in Artificial Intelligence and Digital Applications Development, Technological Institute of Ciudad Victoria, Mexico, 17 November 2021 (in Spanish).

Recent publications

• Rodríguez-García, C., Arenas-Prado, C., Arrizabalaga, S., Elduayen-Echave, B., Varcárcel, L. V., Rodríguez-Jorge, R., & Errandonea, I. (2026). A review of optimization systems and methods for wastewater treatment plants operation. Environmental Modelling & Software, 204, 107051. Indexed in JCR, Impact Factor: 5.2, Q1, Elsevier.
• Dean Oses, M., Domec Paz, A., Figueroa-Lorenzo, S., Arrizabalaga, S., & Rodríguez-Jorge, R. (2026). Anomaly Detection Using Machine Learning for Robotics Environments on 5G Networks. Technologies (2227-7080), 14(2), 108. Indexed in JCR, Impact Factor: 5.2, Q1.
• Binary Pattern Descriptors for Scene Classification. IEEE Latin America Transactions, Vol. 18, No. 1, January 2020. Indexed in JCR, Impact Factor: 0.967.
• R. Rodriguez-Jorge, I. De Leon-Damas, J. Bila, J. Skvor, Internet of things-assisted architecture for QRS complex detection in real time, Journal of Internet of Things, Vol. 14 (2021), Elsevier, p. 100395. Indexed in JCR, Impact Factor: 5.711, Q1.
• Rotating machinery fault diagnosis using a quadratic neural unit, 2022, DOI: 10.1504/IJGUC.2022.10047657. Indexed in JCR, Impact Factor: 0.5, Q4, Elsevier.
• Mexicano, Adriana; Rodriguez Jorge, Ricardo; Montes, Pascual; Pérez, Joaquín, “Acceleration of the K-Means algorithm by removing stable items”, Int. J. of Space-Based and Situated Computing (IJSSC), Vol. 7, No. 2, 2017. Indexed in JCR, Impact Factor: 0.42, Q3.

Upcoming publications

Ricardo Rodríguez Jorge, A grey-box model for real-time control and monitoring, Lecture Notes in Networks and Systems – Proceedings of the 19th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC-2024), Springer Nature Switzerland AG, San Benedetto del Tronto, Italy, 13–15 November 2024 (Web of Science, Scopus).

Prospective students

Upcoming lectures

Ricardo Rodríguez Jorge, A grey-box model for real-time control and monitoring, Lecture Notes in Networks and Systems – Proceedings of the 19th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC-2024), Springer Nature Switzerland AG, San Benedetto del Tronto, Italy, 13–15 November 2024.